ROSYAYKINA E. A., IVLIEVA N. G.
PROCESSING OF EARTH REMOTE SENSING DATA
IN THE GIS PACKAGE ARCGIS1
Annotation. The article discusses the possibilities of using the ArcGIS GIS package for processing Earth remote sensing data. Particular attention is paid to the determination and analysis of the NDVI vegetation index.
Key words: remote sensing, satellite image, ArcGIS GIS package, NDVI vegetation index.
ROSYAIKINA E. A., IVLIEVA N. G.
PROCESSING OF REMOTELY SENSED DATA BY MEANS OF ARCGIS SOFTWARE
Abstract. The article considers the use of ArcGIS software for processing of remotely sensed data. The authors focus on calculation and analysis of the vegetation index (NDVI).
Keywords: remote sensing, satellite image, ArcGIS software, vegetation index (NDVI).
Remote sensing data processing (RSD) is an area that has been actively developing for many years, and is increasingly being integrated with GIS. Recently, space information has been widely used in student research activities.
Raster data is one of the main types of spatial data in GIS. They can represent satellite images, aerial photographs, regular digital elevation models, thematic grids obtained as a result of GIS analysis and geographic information modeling.
The ArcGIS GIS package includes a set of tools for working with raster data, which allows you to process remote sensing data directly in ArcGIS, as well as perform further analysis using GIS analytical functions. Full integration with ArcGIS allows you to quickly convert spatially coordinated raster data from one map projection to another, transform and georeference images, convert from raster to vector format and vice versa.
In earlier versions of ArcGIS, professional raster image processing required the Image Analysis extension. In latest versions
1 The article was supported by the Russian Foundation for Basic Research (project No. 14-05-00860-a).
ArcGIS has added a number of raster functions to its standard set, many of which are available in the new Image Analysis window. It includes four structural elements: a window with a list of open raster layers; an Options button to set default options for some tools; two sections with tools (“Display” and “Processing”).
The “Display” section brings together settings that improve the visual perception of images on the monitor screen; the “Processing” section presents a number of functions for working with rasters. Our research has shown that the Window Treatment panel in the Image Analysis window greatly simplifies the handling of rasters in ArcMap. ArcGIS also supports supervised and unsupervised classification of digital images. For analysis, you can also use the functions of the additional modules Spatial Analyst and 3D Analyst.
For the study, we used Landsat 4-5 TM images: multispectral (archived set of images in GeoTIFF format) and a synthesized image in natural colors in JPEG format with coordinate reference. The spatial resolution of satellite images is 30 m. The images were obtained through the EarthExplorer service of the US Geological Survey. The processing level of the original multispectral satellite image is L1. This level of processing of Landsat images ensures their radiometric and geometric correction using digital elevation models (“terrestrial” correction). Output map projection UTM, WGS-84 coordinate system.
To form a synthesized image - a widely used brightness transformation of a multispectral image - the "Merge Channels" tool of the "Raster" group of tools was used. Depending on the tasks being solved, the combinations of channels may be different.
When processing a multispectral image, transformations are often performed that build “index” images. Based on mathematical operations with matrices of brightness values in certain channels, a raster image is created, and the calculated “spectral index” is assigned to the pixel values. Based on the resulting image, further research is carried out.
To study and assess the state of vegetation, so-called vegetation indices are widely used. They are based on differences in pixel brightness in images in the visible and near-infrared parts of the spectrum. Currently, there are about 160 options for vegetation indices. They are selected experimentally based on
from known features of spectral reflectance curves of vegetation and soils.
Our study focused on studying the distribution and dynamics of the NDVI vegetation index. The most important area of application of this index is to determine the condition of crops.
Using the NDVI button of the Image Analysis window allows you to convert images in the near-infrared (NIR) and red (RED) shooting zones and calculate the so-called NDVI vegetation index as the normalized difference of their values.
The formula for calculating NDVI used in ArcGIS is modified: NDVI = (NIR - RED) / (NIR + RED)) * 100 + 100.
This results in an 8-bit integer image since the range of the calculated cell values is from 0 to 200.
NDVI can be calculated manually using the Raster Calculator tool in Spatial Analyst. In ArcGIS, the NDVI calculation equation used to create the output is as follows:
NDVI = float (NIR - RED) /float (NIR + RED)).
The work examined multi-temporal values of the NDVI index calculated on agricultural lands of the Krasinskoye farm in the Dubensky district of the Republic of Mordovia. The survey was carried out from the Landsat 4-5 TM satellite in 2009. Survey dates: April 24, May 19, June 4, July 5, August 23, September 29. The dates are selected in such a way that each of them falls on a different period of the plant growing season.
NDVI values were calculated using the Raster Calculator tool in Spatial Analyst. Figure 1 shows the result of the operations performed in a specially selected color scale throughout the Dubno district.
The index is calculated as the difference between the reflectance values in the near-infrared and red regions of the spectrum, divided by their sum. As a result, NDVI values vary in the range from - 1 to 1. For green vegetation, which has high reflectivity in the near-infrared region of the spectrum and absorbs radiation well in the red range, NDVI values cannot be less than 0. The reasons for negative values are mainly cloudiness , ponds and snow cover. Very small NDVI values (less than 0.1) correspond to areas with no vegetation, values from 0.2 to 0.3 represent shrubs and meadows, and large values (from 0.6 to 0.8) represent forests. In the study area, according to the obtained rasters, representing
NDVI values, it is easy to identify water bodies, dense vegetation,
clouds, and also highlight populated areas.
Value scale ШУ1
Rice. 1. Synthesized raster of KOU1 distribution.
Fields occupied by certain agricultural crops are more difficult to determine, especially due to the fact that the growing season varies among different crops, and the maximum phytomass occurs on different dates. Therefore, as a source, the work used a diagram of the agricultural crop fields of the Krasinskoye farm in the Dubensky district for 2009. The map was coordinated in GIS, and the fields occupied by agricultural crops were digitized. To study changes in the values of the COU1 index during the growing season, test plots were identified.
Raster systems software allows for statistical analysis of distribution series compiled from all values of raster elements or from individual values (falling into any study area).
Next, using the “Zonal statistics to table” tool of the “Spatial Analyst” module, using the values of cells lying within the selected zones (areas with different crops), descriptive statistics of the index were obtained - maximum, minimum and average values, scatter, standard deviation and sum (Fig. 2). Such calculations were made for all filming dates.
Rice. 2. Determination of NDVI values using the Spatial Analyst tool “Zonal Statistics to Table”.
On their basis, the dynamics of one or another statistical indicator calculated for individual agricultural crops was studied. Thus, Table 1 presents the change in the average values of the studied vegetation index.
Average values of the NDVI index of agricultural crops
Table 1
Winter wheat 0.213 0.450 0.485 0.371 0.098 0.284
Corn 0.064 0.146 0.260 0.398 0.300 0.136
Barley 0.068 0.082 0.172 0.474 0.362 0.019
Malting barley 0.172 0.383 0.391 0.353 0.180 0.147
Perennial grasses 0.071 0.196 0.443 0.474 0.318 0.360
Annual grasses 0.152 0.400 0.486 0.409 0.320 0.404
Pure steam 0.174 0.233 0.274 0.215 0.205 0.336
The picture of variations in various numerical statistical characteristics of the values of the K0Y1 index during the growing season is more clearly displayed by graphic images. Figure 3 shows charts based on average index values for individual crops.
Winter wheat
August September
Rice. 3. Dynamics of COC1 values in the territory occupied by: a) winter wheat; b) barley; c) corn.
You can notice that the minimums and maximums of the KBU values! fall on different dates due to the different length of the growing season of each crop and the amount of phytomass. For example, the highest KBU value! winter wheat occurs in the second ten days of June, and corn - in early July. A gradual increase in the amount of phytomass is observed in barley and annual grasses. The even values of net fallow throughout the growing season are due to the fact that this is open, cultivated soil, and an increase in the value of the BFC! in September may theoretically be associated with the sowing of winter crops.
KBU values! are related to the location of the study area, in particular, to the exposure and slope angle of the slopes. For clarity, a synthesized raster with KBU values! on August 23 was combined with relief washing, built on the basis of the global digital relief model BYTM (Fig. 4). It can be seen that in places of depression (river valleys, ravines) the BBU values! more.
Rice. 4. Combination of raster with KBU values! and cut-off and relief washing.
In addition to the LapeBa1 images for calculating the BBU values! You can also use other remote sensing data, for example, data from the MOBK spectroradiometer.
Based on calculated multi-temporal BBU values! Various maps can be constructed, for example, maps for assessing the agricultural resources of the region, monitoring crops, assessing the biomass of non-timber vegetation, assessing the effectiveness of reclamation, assessing the productivity of pastures, etc.
The conducted studies clearly demonstrated the possibility of using the ArcGIS GIS package for processing Earth remote sensing data, including the calculation and analysis of the NDVI vegetation index, the most important area of application of which remains the determination of the state of crops.
LITERATURE
1. Abrosimov A.V., Dvorkin B.A. Prospects for the use of remote sensing data from space for
increasing the efficiency of agriculture in Russia // Geomatics. - 2009. - No. 4. - P. 46-49.
2. Antipov T. I., Pavlova A. I., Kalichkin V. A. Examples of automated methods
analysis of geoimages for agroecological assessment of lands // News of higher educational institutions. Geodesy and aerial photography. - 2012. - No. 2/1. - P. 40-44.
3. Belorustseva E. V. Monitoring the condition of agricultural land
Non-chernozem zone of the Russian Federation // Modern problems of remote sensing of the Earth from space. - 2012. - T. 9, No. 1. - P. 57-64.
4. Ivlieva N. G. Creating maps using GIS technologies: textbook. benefit for
students studying in specialty 020501 (013700) “Cartography”. -Saransk: Mordov Publishing House. University, 2005. - 124 p.
5. Manukhov V. F., Varfolomeeva N. A., Varfolomeev A. F. Use of space
information in the process of educational and research activities of students // Geodesy and cartography. - 2009. - No. 7. - P. 46-50.
6. Manukhov V. F., Kislyakova N. A., Varfolomeev A. F. Information technologies in
aerospace training of graduate geographers-cartographers // Pedagogical informatics. - 2013. - No. 2. - P. 27-33.
7. Mozgovoy D.K., Kravets O.V. The use of multispectral images for
classification of agricultural crops // Ecology and noosphere. - 2009. - No. 1-2. -WITH. 54-58.
8. Rosyaykina E. A., Ivlieva N. G. Remote sensing data management
Lands in the environment of the ArcGIS GIS package // Cartography and geodesy in the modern world: materials of the 2nd All-Russian. scientific-practical Conf., Saransk, April 8. 2014 / editorial board: V. F. Manukhov (chief editor) and others - Saransk: Mordov Publishing House. Univ., 2014. - P. 150-154.
9. Serebryannaya O. L., Glebova K. S. On-the-fly processing and dynamic compilation
Raster image mosaics in ArcGIS: a new solution to traditional problems.
[Electronic resource] // ArcReview. - 2011. - No. 4 (59). - Access mode: http://dataplus.ru/news/arcreview/.
10. Chandra A. M., Ghosh. S.K. Remote sensing and geographic information systems / trans. from English - M.: Tekhnosphere, 2008. - 288 p.
11. Cherepanov A. S. Vegetation indices // Geomatics. - 2011. - No. 2. - P. 98-102.
N. B. Yaldygina
Recent years have been marked by the rapid development and spread of remote sensing (ERS) and geoinformation technologies. Satellite images are actively used as a source of information to solve problems in various fields of activity: cartography, municipal administration, forestry and agriculture, water management, inventory and monitoring of the condition of oil and gas production and transportation infrastructure, assessment of environmental conditions, search and forecasting of deposits minerals, etc. Geographic information systems (GIS) and geoportals are used to analyze data for the purpose of making management decisions.
As a result, the task of actively introducing remote sensing and GIS technologies into the educational process and scientific activities has become very urgent for many higher educational institutions. Previously, the use of these technologies was required, first of all, by universities training specialists in the field of photogrammetry and GIS. However, gradually, as remote sensing and GIS technologies were integrated with various applied fields of activity, their study became necessary for a much wider range of specialists. Universities providing training in specialties related to forestry and agriculture, ecology, construction, etc., now also require students to be trained in the basics of remote sensing and GIS, so that future graduates are familiar with advanced methods for solving applied problems within their specialty .
At the initial stage, an educational institution planning to train students in remote sensing and GIS topics needs to solve a number of problems:
- Purchase specialized software and hardware.
- Purchase a remote sensing data set that will be used for training and scientific work.
- Conduct retraining of teachers on remote sensing and GIS issues.
- Develop technologies that will allow solving applied problems corresponding to the specialization of the university/department using remote sensing data.
Without a thoughtful and systematic approach, solving these problems may require significant time and material costs from the university. The simplest and most effective way to overcome difficulties is to interact with companies that supply all the necessary software and hardware for the implementation of remote sensing and GIS technologies, and who have experience in implementing projects for various sectors of the national economy.
An integrated approach to the implementation of remote sensing and GIS technologies at a university will be provided by the Sovzond company, which offers a full range of services, ranging from the supply of software and hardware, their installation and configuration, to the supply of remote sensing data, training of specialists and the development of technological solutions. The basis of the proposed solution is the Earth Remote Sensing Data Processing Center (ERDC).
What is TsODDZZ?
This is a set of software and hardware tools and technologies designed to receive, process and analyze remote sensing data and use geospatial information. TsODDSZ allows you to solve the following main tasks:
- Obtaining remote sensing data (satellite images).
- Primary processing of space images, preparation for automated and interactive interpretation, as well as visual presentation.
- Deep automated analysis of remote sensing data for the preparation of a wide range of analytical cartographic materials on various topics, determination of various statistical parameters.
- Preparation of analytical reports and presentation materials based on satellite imagery data.
The key component of the data acquisition center is specialized software and hardware that has broad functionality for working with remote sensing and GIS data.
TsODDZZ software
The software included in TsODDZZ is designed to perform the following work:
Photogrammetric processing of remote sensing data (geometric correction of images, construction of digital terrain models, creation of image mosaics, etc.). It is a necessary step in the overall technological cycle of processing and analyzing remote sensing data, ensuring that the user receives accurate and up-to-date information.
Thematic processing of remote sensing data (thematic interpretation, spectral analysis, etc.). Provides for the interpretation and analysis of satellite imagery materials for the purpose of creating thematic maps and plans, and making management decisions.
GIS analysis and mapping (spatial and statistical data analysis, map preparation, etc.). Provides identification of patterns, relationships, trends in events and phenomena of the surrounding world, as well as the creation of maps to present the results in a user-friendly form.
Providing access to geospatial information via the Internet and Intranet (organizing data storage, creating web- services with GIS analysis functions for users of internal and external networks). Provides for organizing user access from the internal network and the Internet to information on a given topic for a certain territory (satellite images, vector maps, attribute information).
In table Figure 1 shows the software usage scheme proposed by Sovzond, which makes it possible to fully implement all of the listed types of work.
Table 1. Software usage diagram
|
Type of work |
Software products |
Basic functionality |
| Photogrammetric processing of remote sensing data | INPHO line from Trimble INPHO | Automated aerial triangulation for all types of footage obtained from both analogue and digital cameras Construction of high-precision digital elevation models (DEM) from aerial or space photography, quality control and editing of DEM Orthorectification of remote sensing data Creation of color-synthesized mosaic coverings using images obtained from various satellites Vectorization of terrain objects using stereo pairs of aerial and satellite images |
| Visualization of remote sensing data Geometric and radiometric correction Creation of DEMs based on stereo images Creating mosaics |
||
| Thematic processing of remote sensing data | ENVI line from ITT VIS | Interactive interpretation and classification Interactive spectral and spatial image enhancement Calibration and atmospheric correction Vegetation analysis using vegetation indices (NDVI) Obtaining vector data for export to GIS |
| GIS analysis and mapping | ArcGIS Desktop line (ESRI Inc.) | Creation and editing of spatial data based on an object-oriented approach Creation and design of cards Spatial and statistical analysis of geodata Map analysis, visual report creation |
| Providing access to geospatial information via the Internet | ArcGIS Server family (ESRI Inc.) |
CCentralized management of all spatial data and mapping services
Creating web applications with desktop GIS functionality |
For higher educational institutions, the Sovzond company offers favorable terms for the supply of software. The cost of individual licenses for a university is reduced by two or more times compared to commercial licenses. In addition, special sets of licenses are supplied for equipment in classrooms (Table 2). The cost of a license package for training for 10 or more seats is generally comparable to the cost of a single commercial license. The table below describes the license packages provided by various software providers.
Table 2. Software licenses
Many Russian universities already have positive experience in using software products from ITT VIS, ESRI Inc., Trimble INPHO as part of their educational and scientific activities. Among them are the Moscow State University of Geodesy and Cartography (MIIGAiK), Moscow State Forestry University (MGUL), Mari State Technical University (MarSTU), Siberian State Geodetic Academy (SSGA), etc.
Hardware TsODDZZ
TsODDZZ hardware includes advanced technical means that allow a higher educational institution to organize a research and educational process, and implement various methods of working both with information and with the student audience. The hardware is selected taking into account the scale of the planned work, the number of students being trained and a number of other factors. The data center can be deployed on the basis of one or several premises and include, for example, a classroom, a remote sensing laboratory and a meeting room.
The following equipment can be used as part of the data protection center:
- Workstations for installing specialized software (in classrooms and departments).
- Servers for organizing the storage and management of geospatial data.
- Video walls for displaying and collective viewing of information (Fig. 1).
- Video conferencing systems for the exchange of audio and video information in real time between remote users (located in different rooms).
These tools not only constitute a productive hardware platform for performing remote sensing data processing processes, but also allow for effective interaction between user groups. For example, a video conferencing system and TTS hardware and software system can provide real-time transmission of data prepared by laboratory specialists and video images directly to a screen in a meeting room.
Remote sensing data supply
When deploying a remote sensing data center, one of the important issues is the acquisition of a set of remote sensing data from various satellites, which will be used to train students and carry out various thematic projects. The Sovzond company interacts with leading companies operating remote sensing satellites and supplies digital data received from spacecraft WorldView-1, WorldView-2, GeoEye-1, QuickBird, IKONOS, Resurs-DK1, RapidEye, ALOS, SPOT, TerraSAR -X, RADARSAT-1,2, etc.
It is also possible to deploy a ground-based receiving complex at the university, created with the participation of the Federal Space Agency (Roscosmos), providing direct reception of data from the Resurs-DK1, AQUA, TERRA, IRS-1C, IRS-1D, CARTOSAT-1 (IRS-P5) satellites ), RESOURCESAT-1 (IRS-P6), NOAA, RADARSAT-1,2, COSMO-SkyMed 1–3, etc. In addition, in the case of the deployment of DSDSRS, the Sovzond company provides the educational institution with a set of free remote sensing data from several satellites, having different characteristics (spatial resolution, spectral range, etc.), which can be used as test samples for teaching students.
The deployment of the Center for Remote Sensing of the Earth in a higher educational institution allows us to solve the problem of introducing remote sensing and GIS technologies into the scientific and educational activities of the university and provide training for specialists in a relatively new and relevant area.
TsODDZZ is a flexible and scalable system. At the initial stage of creation, a digital sensing data center can be a small laboratory or even separate workstations with remote sensing data processing functionality. In the future, it is possible to expand the data acquisition center to the size of large laboratories and training centers, the activities of which are not limited to teaching students, but also involve the implementation of commercial projects based on remote sensing data and the provision of information services to Internet users.
Remote sensing data provides important information that helps in monitoring various applications such as image fusion, change detection, and land cover classification. Satellite imagery is a key method used to obtain information related to earth resources and the environment.
The popular thing about satellite imagery data is that it can be easily accessed online through various mapping applications. By simply being able to find the right address, these applications have helped the GIS community in project planning, disaster monitoring in many areas of our lives.
The TerraCloud company provides access to a database of multi-temporal satellite images of the resolution you need from Russian satellites in one online window, around the clock and from anywhere in the world. And on convenient ordering conditions.
The main aspect that affects the accuracy of a ground object is spatial resolution. Temporal resolution helps in creating land cover maps for environmental planning, land use change detection, and transportation planning.
Data integration and analysis of urban areas using medium-resolution remote sensing imagery are primarily focused on documenting human settlements or used to delineate between residential, commercial and industrial areas.
Provides a base map for graphical reference and assistance to planners and engineers
The amount of detail that orthoimaging produces using high-resolution satellite imagery is significant. As it provides a detailed image of the selected area along with the surrounding areas.
Because maps are location-based, they are specifically designed to convey highly structured data and create a complete picture of where you want to go on the earth's surface. There are numerous applications of satellite imagery and remote sensing data.
Today, countries use information obtained from satellite imagery for government decision-making, civil defense operations, police services, and geographic information systems (GIS) in general. These days, data obtained using satellite images, have become mandatory and all government projects must be submitted based on satellite imagery data.
During the preliminary and feasibility stages of mineral exploration, it is important to be aware of the potential mineral usefulness of the area being considered for mining.
In such scenarios, satellite remote sensing based mapping and its integration into a GIS platform helps geologists easily map mineral potential zones, saving time. Using spectral band analysis of satellite images, a scientist can quickly determine and display mineral availability using special indicators.
This will allow the exploration geologist to narrow geophysical, geochemical and test drilling to high potential areas.
The outcome of a natural disaster can be devastating and sometimes difficult to assess. But disaster risk assessment is essential for rescuers. This information must be prepared and executed quickly and accurately.
Object-based image classification using change detection (pre- and post-event) is a fast way to obtain damage assessment data. Other similar applications using satellite imagery in disaster assessments include measuring shadows from buildings and digital surface models.
With the growing population around the world and the need to increase agricultural production, there is a definite need for proper management of the world's agricultural resources.
For this to happen, it is first necessary to obtain reliable data not only on the types, but also on the quality, quantity and location of these resources. Satellite imagery and GIS (geographic information systems) will always remain an important factor in improving existing systems for collecting and mapping agricultural and resource data.
Agricultural mapping and surveys are currently being conducted around the world to collect information and statistics on crops, rangelands, livestock and other related agricultural resources.
The collected information is necessary for implementing effective management decisions. Agricultural survey is necessary for planning and allocation of limited resources among different sectors of the economy.
3D city models are digital models of urban areas that represent terrain surfaces, sites, buildings, vegetation, infrastructure and landscape elements, and associated objects belonging to urban areas.
Their components are described and represented with associated 2D, 3D spatial and georeferenced data. 3D city models support the representation, exploration, analysis and management of tasks across a wide variety of application areas.
3D GIS is a fast and effective solution for large and remote locations where manual surveying is nearly impossible. Various urban and rural planning departments need 3D GIS data such as, drainage, sewerage,
water supply, canal design and much more.
And a few final words. Satellite images have become a necessity in our time. Their accuracy is beyond question - because everything is visible from above. The main thing here is the question of the relevance of the images and the ability to get a photo of exactly the area of the territory that you really need. Sometimes this helps solve really important issues.
09.20.2018, Thu, 10:51, Moscow time , Text: Igor Korolev
The Digital Economy program involves a whole range of measures to ensure the availability of spatial data and Earth remote sensing data with a total cost of ₽34.9 billion. It is planned to create portals for both types of data, build a federal network of geodetic stations and monitor the efficiency of federal budget expenditures from space.HowdevelopspatialdataAnddataremote sensing
The “Information Infrastructure” section of the “Digital Economy” program involves the creation of domestic digital platforms for collecting, processing and distributing spatial data and Earth remote sensing (ERS) data from space, meeting the needs of citizens, businesses and authorities. According to CNews estimates, the costs of the relevant measures will amount to ₽34.9 billion, most of this amount will be taken from the federal budget.
First of all, it is planned to develop a glossary of terms in the field of working with spatial data and remote sensing data from space. In these same areas, including products and services created on their basis, tasks should be set and requirements should be formed for studying the needs of the digital economy for domestic services and technologies for collection, processing, distribution and analysis.
The Ministry of Economic Development, the Ministry of Telecom and Mass Communications, Roscosmos, Rosreestr, Rostelecom, Moscow State University will undertake the relevant work. M.V. Lomonosov and the Aeronet working group of the National Technology Initiative (NTI). RUB 88 million will be spent for these purposes, of which RUB 65 million will be allocated by the federal budget. Note that, according to Russian legislation, remote sensing data does not relate to spatial data.
In parallel, an architecture and roadmap for creating an infrastructure for collection, storage, processing and distribution will be developed for spatial data and remote sensing data from space. The infrastructure will operate on the basis of an interdepartmental unified territorially distributed information system (ETRIS DZZ).
This will be done by Roscosmos, Rostelecom and the Ministry of Economic Development. The cost of the event will be ₽85 million, of which ₽65 million will be allocated by the federal budget.
Certificationdataremote sensing
The use of certified Earth remote sensing data must be legally established. Changes will be made to federal legislation in order to consolidate the status of the federal remote sensing fund.
A roadmap for creating appropriate legal and regulatory framework will also be developed. The requirements for the provision and procedure for the provision in electronic form of spatial data and materials and remote sensing data contained in the relevant federal fund will be approved by regulation.
The regulations will establish the creation of a certification system for remote sensing data from space and algorithms for their processing in order to obtain legally significant data, as well as the procedure for using certified remote sensing data from space and data obtained by other methods of remote sensing of the Earth in economic circulation. These activities will be carried out by Roscosmos, Rostelecom, the Ministry of Telecom and Mass Communications, the Ministry of Economic Development and Trade and NTI Aeronet.
Federalportalspatialdata
Next, methods for providing electronically spatial data and materials contained in the Federal Spatial Data Fund, as well as remote sensing data contained in the corresponding Federal Fund, will be provided.
For this purpose, a state information system, the Federal Spatial Data Portal (GIS FPPD), will be developed, providing access to information contained in the federal spatial data fund.
First, the concept of the corresponding system will be created. Then, by April 2019, it will be put into trial operation, and by the end of 2019 it will be put into commercial operation. The development, launch and modernization of the GIS FPPD will cost the federal budget ₽625 million.
The GIS FPPD will have a subsystem “Digital platform for interdepartmental geoinformation interaction”. Its launch into trial operation will take place in November 2019, it will cost the federal budget another ₽50 million.
Plans will be developed to connect this subsystem to the federal remote sensing data fund, funds of spatial data and materials of government agencies in order to provide electronically the materials at their disposal. The Ministry of Economic Development, Rosreestr and Roscosmos will take relevant measures.
Organsstate powerwill sharespatialdataAnddataremote sensing
It is also planned to provide the ability to automatically provide, using coordinates, an established list of information at the disposal of state authorities and local self-government.
First, an assessment will be made of the economic effects that can be obtained by revising the requirements for the parameters for the disclosure of spatial data and remote sensing data at the disposal of government bodies. Then changes will be made to the list of information (as well as their details and formats) to be provided in an automated mode using coordinates, along with the list of bodies that own such information.
By the end of 2019, an automated mapping service will be developed and put into operation, providing thematic information at the disposal of government bodies using coordinates. The Ministry of Economic Development, Roscosmos, Rosreestr, FSB and the Ministry of Defense will carry out the relevant work; the federal budget will allocate ₽250 million for their implementation.
In addition, the possibility of automated processing, recognition, validation and use of spatial data will be provided. For this purpose, functional requirements will be developed for the above-mentioned tools, including systems for automated generalization of images of spatial objects, as well as for monitoring tools for terrain changes.
The goal is to ensure compliance with the requirements for the frequency of updating spatial data resources. Trial operation of the corresponding facilities should begin in September 2019, industrial operation - before the end of 2020.
An infrastructure of experimental testing sites should also be created for testing robotic systems used for collecting and processing spatial data. The indicated activities will be carried out by the Ministry of Economic Development, Rosreestr and NTI Aeronet.
DomesticgeoinformationBYFororgansstate power
Another direction of the document is to ensure the development and use of domestic geoinformation technologies in state and local government bodies, as well as state-owned companies. Requirements for the relevant software will be developed and published on the Internet.
Then a list of software that meets the established requirements will be generated, taking into account the Unified Register of Russian Software. There will also be a study of promising technologies and management models using geoinformation technologies and domestic remote sensing data in government agencies and methodological recommendations for the transition to domestic software in these areas will be developed.
In addition, monitoring and analysis of the use of software of geographic information systems in the information systems of government agencies and state-owned companies will be carried out. After this, action plans will be developed for federal and regional authorities, local governments and state-owned companies aimed at ensuring the use of domestic software in this area. These activities will be carried out by the Ministry of Economic Development, the Ministry of Telecom and Mass Communications, Roscosmos and Rostelecom.
4,8 billiononfederalnetgeodeticstations
The action plan involves the creation of a unified geodetic infrastructure necessary for defining, clarifying and disseminating state and local coordinate systems. Relevant activities will be carried out by the Ministry of Economic Development, the Ministry of Defense, Rosreestr, Rosstandart, the Federal Agency for Scientific Research, Roscosmos, the state enterprise Center for Geodesy, Cartography and IPD and JSC Roscartography.
To this end, research work will first be carried out to clarify the parameters of the figure and gravitational field, geodetic parameters of the Earth, and other parameters necessary to clarify the state coordinate systems, the state height system, the state gravimetric system and substantiate the development of the geodetic network.
State registration and safety of points of the state geodetic network (GTS), state leveling network, and state gravimetric network will also be ensured. A system for monitoring the characteristics of GTS points, state leveling and gravimetric networks will be organized, and the development of a domestic network of colocated geodetic observation stations will be ensured. The federal budget will allocate for these purposes in 2018-20. ₽3.18 billion
Next, a service will be created to ensure the determination of movements of the earth's crust caused by natural and anthropogenic geodynamic processes, as well as a service to determine and clarify the parameters of the exact orbits of navigation spacecraft and Earth remote sensing spacecraft.
At the next stage, a federal network of geodetic stations will be created that will improve the accuracy of coordinate determination, as well as a center for integrating networks of geodetic stations and processing the information received. First, the concept of the corresponding network will be developed, including services and the geography of their use, technical and economic indicators of creating and operating the network.
By August 2019, “pilot zones” of the federal network of geodetic base stations will be created and put into operation in at least three regions. Also, a center for integrating networks of geodetic stations will be put into trial operation. Taking into account the experience of the “pilot zones”, technical specifications for the future network will be created.
The network itself will be operational by the end of 2020. RUB 1.65 billion will be spent on its creation and launch. At the same time, RUB 1.35 billion will be taken from the federal budget, the remaining RUB 200 million from extra-budgetary sources. The total cost of creating and maintaining geodetic infrastructure will be RUB 4.83 billion.
19 billionsonUnitedelectroniccartographicbasis
Another project included in the document is the creation of a Unified Electronic Cartographic Framework (EECO) and a state system for maintaining EECO. First, a concept, technical specifications and a preliminary design of the GIS EECO will be created. The system should be put into trial operation in April 2019, and into commercial operation by the end of 2019.
Next, the foundation of the GIS EEKO will be created, including on the basis of open digital topographic maps and plans placed in the federal spatial data fund, and the creation of a basic high-precision (scale 1:2000) layer of spatial data of territories with high population density in the interests of accumulating GIS EEKO .
The target composition and structure of EECO data and services, methods and algorithms for using the cartographic framework and spatial data in the interests of various consumer groups, and a list of possibilities for using distributed registry technologies (blockchain) must be developed.
It is also planned to create a promising GIS EEKO model for use by various categories of consumers, including automated and robotic systems. Rosreestr, the Ministry of Economic Development and NTI Aeronet will take the corresponding measures. Activities related to the GIS EEKO will cost the federal budget RUB 19.32 billion.
FederalportaldataremotesoundingEarth
The document involves ensuring the provision in electronic form of Earth remote sensing data and materials contained in the federal remote sensing fund. For this purpose, the information technology mechanisms (as part of the Roscosmos information systems) of the system for providing access to data from Russian Earth remote sensing spacecraft and the geoportal of the Roscosmos state corporation will be modernized.
A concept, terms of reference and preliminary design of the state information system Federal Portal of Earth Remote Sensing Data from Space (GIS FPDDZ) will be developed, providing access to information contained in the federal fund of remote sensing data from space.
The GIS FPDDZ will be put into trial operation by the end of 2019, and into commercial operation by the end of 2020. The project will be carried out by Roscosmos. The federal budget will allocate RUB 315 million for appropriate purposes.
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A single seamless continuous multilayer coverage of remote sensing data from space of various spatial resolutions will also be created. The corresponding activities will be carried out by Roscosmos, Rosreestr and the Ministry of Economic Development; they will cost the federal budget ₽6.44 billion.
To this end, a concept for an appropriate high-resolution (2–3 meter) coverage will first be prepared. By the end of 2018, a technological Set of Continuous high-precision seamless coating of high spatial resolution (SBP-V) will be created according to remote sensing data from Russian spacecraft with an accuracy of no worse than 5 meters. This will include the identification of additional reference points as a result of field work and measurements from satellite images.
In 2018, SBP-V will be deployed in priority areas with a total area of 2.7 million kW km. In 2019, SBP-V will be deployed to the territory of the second stage districts with a total area of 2.9 million sq. km. In 2020, SBP-V will be deployed in the remaining areas, including areas with high population density, with a total area of 11.4 million sq. km.
In parallel, a set of Continuous multiscale coverage for mass use (SBP-M) will be created using multispectral survey data from Russian remote sensing spacecraft with high-resolution plan accuracies of no worse than 15 m.
In 2018, SBP-M will be deployed in priority areas with a total area of 2.7 million kW km. In 2019 - on the territory of the second stage districts with a total area of 2.9 sq. km. In 2020, SBP-M will be deployed in other territories with a total area of 11.4 million kW km.
In 2020, based on the Set of Continuous High-Precision Seamless Coverage of High Spatial Resolution and the Set of Continuous Multi-Scale Coverage for Mass Use, a Unified Seamless Continuous Multilayer Coverage with Earth Remote Sensing Data (EBSRPR) will be created. Also, the state information system (GIS) EBSPVR will be put into trial operation.
The result should be an information basis that ensures the stability and competitiveness of the measurement characteristics of domestic remote sensing data from space and products based on them. A technology and basic information basis will also be created for the formation of a wide range of applied client-oriented services based on remote sensing technologies and information support of third-party information systems.
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It is planned to provide the possibility of automated processing, recognition, confirmation and use of remote sensing data from space. To this end, experimental research, development of technologies and software for automatic streaming and distributed processing of remote sensing data from space will first be carried out with the creation of elements for standardizing output information products.
The corresponding tools and unified software will be put into trial operation by May 2020. Commissioning into commercial operation will take place before the end of 2020. The project will be carried out by Roscosmos, the Ministry of Economic Development and Rosreestr, federal budget expenses will amount to ₽975 million.
Future unified hardware and software tools for primary processing of remote sensing data from space with elements of standardization of information resources will be put into operation on the basis of geographically distributed cloud computing resources of ground-based space remote sensing infrastructure.
In 2018, the concept, nomenclature and technologies for creating specialized industry services based on remote sensing will be developed for the purpose of information support for the following industries: subsoil use, forestry, water management, agriculture, transport, construction and others
Samples of unified complexes for distributed processing and storage of information will be designed to solve the problems of the operator of Russian space remote sensing systems from space with the maximum level of automation and standardization of processing, automatic quality control, and cost-effectiveness in maintenance and operation. The level of unification of special software will be up to 80%.
The introduction of technologies for automatic streaming generation of standard and basic remote sensing information products at the request of users through the subsystem for providing consumer access and delivery within up to 1.5 hours after receiving target information from remote sensing spacecraft will also be ensured.
In addition, field tools for monitoring the spectro-radiometric and coordinate-measuring characteristics of remote sensing spacecraft and verification of remote sensing information products from space will be modernized, as well as instrumental and methodological support for a certification center for remote sensing data from space will be created.
Roscosmos will create a geographically distributed computing resource for streaming remote sensing data processing
Another direction of the implementation plan for the Digital Economy program under the Information Infrastructure section is to ensure the development and use of domestic technologies for processing (including thematic) remote sensing data in state and local government bodies, as well as state-owned companies.
As part of the implementation of this idea, the creation and modernization of a geographically distributed computing resource will be carried out to ensure streaming processing of remote sensing data from space as part of data processing centers and computing clusters of ground-based complexes for receiving, processing and distributing remote sensing data. The project will be carried out by Roscosmos.
In 2019, corresponding events will be held in the European zone of Russia, in 2020 - in the Far Eastern zone. The federal budget will allocate RUB 690 million for these purposes.
Controlexpensesfederalbudgetwill checkfromspace
In parallel, the development and modernization of hardware and software solutions and applied client-oriented services for agriculture and forestry will take place based on remote sensing technologies from space; this will cost the federal budget ₽180 million.
Also in 2018, a concept, nomenclature and technology for creating specialized industry services based on remote sensing will be developed for the purpose of information support for the following industries: subsoil use, forestry, water management, agriculture, transport, construction and others. Together with Roscosmos, these tasks will be solved by the Ministry of Economic Development.
In 2019, other industries will be selected to develop similar services and solutions. In 2020, service solutions will be tested in pilot zones and subsequently put into trial operation; the corresponding activities will cost the federal budget ₽460 million.
In 2018, a control service for space imaging will be designed and created for the targeted and effective use of funds from the federal budget and the budgets of state extra-budgetary funds aimed at financing all types of construction. This will be done by Roscosmos and the Accounts Chamber, the federal budget will allocate ₽125 million for this project.
In a similar way, a service will be created to monitor the use of space imagery from the federal budget funds aimed at financing infrastructure projects and special economic zones. The corresponding resource will be designed and put into trial operation by the end of 2018, and its commercial operation will begin in June 2019. The cost of the project for the federal budget will be RUB 125 million.
A service will also be created to monitor the use of space imagery of federal budget funds aimed at preventing and eliminating emergency situations and the consequences of natural disasters (fires, floods, etc.), as well as eliminating the consequences of pollution and other negative impacts on the environment. The federal budget will spend RUB 170 million on this project.
A service will be created to determine the effectiveness and compliance with regulatory legal acts of the procedure for financing, managing and disposing of federal and other resources: forest, water, mineral, etc. The federal budget will spend ₽155 million on this.
A similar service will be created to ensure control of economic activities in order to identify violations of land legislation, establish facts of land use for other purposes and determine economic damage. The project will cost the federal budget ₽125 million.
Another planned service will provide an assessment of the prospects for involvement in various types of economic activities (agriculture, construction, recreation, etc.). The cost of the project for the federal budget will be ₽145 million.
A service will also be created to identify changes taking place in the regions of Russia using satellite images for the purpose of determining the pace of their development, making planning decisions and optimizing budget funds. The federal budget will allocate RUB 160 million for this project.
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- Introduction
- 1. General characteristics of GIS
- 2. Features of data organization in GIS
- 3. Methods and technologies for modeling in GIS
- 4. Information security
- 5. GIS Applications and Applications
- Conclusion
- Bibliography
- Application
Introduction
Geographic information systems (GIS) form the basis of geoinformatics - a new modern scientific discipline that studies natural and socio-economic geosystems of various hierarchical levels through analytical computer processing of created databases and knowledge bases.
Geoinformatics, like other Earth sciences, is aimed at studying the processes and phenomena occurring in geosystems, but uses its own means and methods for this.
As mentioned above, the basis of geoinformatics is the creation of computer GIS that simulate the processes occurring in the geosystem under study. To do this, you first need information (usually factual material), which is grouped and systematized in databases and knowledge bases. Information can be very diverse - cartographic, point, static, descriptive, etc. Depending on the goal, its processing can be done either using existing software products or using original techniques. Therefore, in the theory of geosystem modeling and the development of spatial analysis methods in the structure of geoinformatics, great importance is attached.
There are several definitions of GIS. In general, they boil down to the following: a geographic information system is an interactive information system that provides collection, storage, access, display of spatially organized data and is focused on the ability to make scientifically based management decisions.
The purpose of creating a GIS can be inventory, cadastral valuation, forecasting, optimization, monitoring, spatial analysis, etc. The most difficult and responsible task when creating a GIS is management and decision making. All stages - from collecting, storing, transforming information to modeling and decision-making in conjunction with software and technological tools are united under the general name - geographic information technologies (GIS technologies).
Thus, GIS technologies are a modern systematic method for studying the surrounding geographic space in order to optimize the functioning of natural-anthropogenic geosystems and ensure their sustainable development.
The abstract discusses the principles of creating and updating geographic information systems, as well as their applications and applications. geographic information economic social
1 . General characteristics of GIS
Modern geographic information systems (GIS) are a new type of integrated information systems, which, on the one hand, include data processing methods of many previously existing automated systems (AS), on the other hand, have specifics in the organization and processing of data. In practice, this defines GIS as multi-purpose, multi-aspect systems.
Based on an analysis of the goals and objectives of various GIS operating currently, the definition of GIS as geographic information systems rather than as geographic information systems should be considered more accurate. This is also due to the fact that the percentage of purely geographic data in such systems is insignificant, data processing technologies have little in common with traditional processing of geographic data, and, finally, geographic data serves only as a basis for solving a large number of applied problems, the goals of which are far from geography.
So, GIS is an automated information system designed for processing spatiotemporal data, the basis for the integration of which is geographic information.
GIS carries out complex processing of information - from its collection to storage, updating and presentation, in this regard, GIS should be considered from various perspectives.
As management systems, GIS is designed to support decision-making on the optimal management of lands and resources, urban management, transport and retail management, the use of oceans or other spatial objects. At the same time, cartographic data is always used among others to make decisions.
Unlike automated control systems (ACS), many new technologies for spatial data analysis are emerging in GIS. Because of this, GIS serve as a powerful tool for transforming and synthesizing a variety of data for management tasks.
As automated information systems, GIS combines a number of technologies or technological processes of well-known information systems such as automated scientific research systems (ASRS), computer-aided design systems (CAD), automated reference information systems (ASIS), etc. The basis for the integration of GIS technologies is CAD technologies. Since CAD technologies have been sufficiently tested, this, on the one hand, has ensured a qualitatively higher level of GIS development, and on the other hand, it has significantly simplified the solution to the problem of data exchange and selection of technical support systems. With this, GIS has become on a par with general-purpose automated systems such as CAD, ASNI, ASIS.
As geosystems, GIS includes technologies (primarily information collection technologies) of such systems as geographic information systems, cartographic information systems (CIS), automated mapping systems (ASC), automated photogrammetric systems (AFS), land information systems (LIS), automated cadastral systems (AKS), etc.
As database systems, GIS are characterized by a wide range of data collected using different methods and technologies. It should be emphasized that they combine both databases of conventional (digital) information and graphic databases. Due to the great importance of expert problems solved with the help of GIS, the role of expert systems included in GIS is increasing.
As modeling systems, GIS uses the maximum number of modeling methods and processes used in other automated systems.
As systems for obtaining design solutions, GIS largely use computer-aided design methods and solve a number of special design problems that are not found in standard computer-aided design
As systems for presenting information, GIS is a development of automated documentation support systems (ADS) using modern multimedia technologies. This determines the greater visibility of GIS output compared to conventional geographic maps. Data output technologies allow you to quickly obtain a visual representation of cartographic information with various loads, move from one scale to another, and obtain attribute data in tabular or graph form.
As integrated systems, GIS is an example of combining different methods and technologies into a single complex, created by integrating technologies based on CAD technologies and integrating data based on geographic information.
As mass-use systems, GIS allows the use of cartographic information at the level of business graphics, which makes them accessible to any schoolchild or businessman, not only to specialist geographers. That is why when making decisions based on GIS technologies, they do not always create maps, but always use cartographic data.
As already mentioned, GIS uses technological advances and solutions applicable in such automated systems as ASNI, CAD, ASIS, and expert systems. Consequently, modeling in GIS is the most complex in relation to other automated systems. But on the other hand, the modeling processes in GIS and in any of the above AS are very close. The AMS is fully integrated into GIS and can be considered as a subset of this system.
At the level of information collection, GIS technologies include methods for collecting spatio-temporal data that are not available in automated control systems, technologies for using navigation systems, real-time technologies, etc.
At the level of storage and modeling, in addition to the processing of socio-economic data (as in automated control systems), GIS technologies include a set of spatial analysis technologies, the use of digital models and video databases, as well as an integrated approach to decision making.
At the presentation level, GIS complements ACS technologies with the use of intelligent graphics (presentation of cartographic data in the form of maps, thematic maps or at the level of business graphics), which makes GIS more accessible and understandable compared to ACS for businessmen, management workers, government officials, etc. .d.
Thus, in GIS, all tasks that were previously performed in automated control systems are fundamentally solved, but at a higher level of integration and data fusion. Consequently, GIS can be considered as a new modern version of automated management systems that use more data and a greater number of analysis and decision-making methods, primarily using spatial analysis methods.
2 . Features of data organization in GIS
GIS uses a variety of data about objects, characteristics of the earth's surface, information about the shapes and relationships between objects, and various descriptive information.
In order to fully display real-world geo-objects and all their properties, an infinitely large database would be needed. Therefore, using generalization and abstraction techniques, it is necessary to reduce a lot of data to a finite volume that can be easily analyzed and managed. This is achieved by using models that preserve the main properties of the objects of study and do not contain secondary properties. Therefore, the first stage in the development of a GIS or the technology for its application is to justify the choice of data models to create the information basis of the GIS.
Choosing a method for organizing data in a geographic information system, and, first of all, a data model, i.e. method of digital description of spatial objects determines many of the functionality of the created GIS and the applicability of certain input technologies. Both the spatial accuracy of the visual representation of information and the possibility of obtaining high-quality cartographic material and organizing control of digital maps depend on the model. The performance of the system greatly depends on the way data is organized in a GIS, for example, when querying a database or rendering (visualization) on a monitor screen.
Errors in choosing a data model can have a decisive impact on the ability to implement the necessary functions in GIS and expand their list in the future, and the efficiency of the project from an economic point of view. The value of the generated databases of geographic and attribute information directly depends on the choice of data model.
Levels of data organization can be represented as a pyramid. A data model is a conceptual level of data organization. Terms such as “polygon”, “node”, “line”, “arc”, “identifier”, “table” refer to this level, just like the concepts “topic” and “layer”.
A more detailed look at the organization of data is often called data structure. The structure contains mathematical and programming terms such as “matrix”, “list”, “link system”, “index”, “information compression method”. At the next most detailed level of data organization, specialists deal with the structure of data files and their immediate formats. The level of organization of a particular database is unique to each project.
GIS, however, like any other information system, has developed means of processing and analyzing incoming data for the purpose of their further implementation in material form. In Fig. 3. A diagram of the analytical work of the GIS is presented. At the first stage, “collecting” of both geographical (digital maps, images) and attribute information is carried out. The collected data fills two databases. The first database stores cartographic data, while the second is filled with descriptive information.
At the second stage, the spatial data processing system accesses databases to process and analyze the required information. In this case, the entire process is controlled by a database management system (DBMS), with which you can quickly search for tabular and statistical information. Of course, the main result of GIS work is a variety of maps.
To organize the connection between geographic and attribute information, four interaction approaches are used. The first approach is georelational or, as it is also called, hybrid. In this approach, geographic and attribute data are organized differently. The connection between the two data types is through an object identifier. As can be seen from Fig. 3., geographic information is stored separately from attribute information in its own database. Attribute information is organized into tables controlled by a relational DBMS.
The next approach is called integrated. This approach involves the use of relational DBMS tools for storing both spatial and attribute information. In this case, GIS acts as a superstructure over the DBMS.
The third approach is called object-based. The advantages of this approach are the ease of describing complex data structures and relationships between objects. The object approach allows you to build hierarchical chains of objects and solve numerous modeling problems.
Recently, the object-relational approach, which is a synthesis of the first and third approaches, has become most widespread.
It should be noted that in GIS there are several forms of object representation:
In the form of an irregular network of points;
In the form of a regular network of points;
In the form of isolines.
Representation in the form of an irregular network of points is randomly located point objects that have some meaning at a given point in the field as attributes.
Representation in the form of a regular network of points is points of sufficient density evenly distributed in space. A regular network of points can be obtained by interpolation from irregular ones or by taking measurements along a regular network.
The most common form of representation in cartography is isoline representation. The disadvantage of this representation is that there is usually no information about the behavior of objects located between the isolines. This method of presentation is not the most convenient for analysis. Let's consider models for organizing spatial data in GIS.
The most common model for organizing data is the layer model. The essence of the model is that objects are divided into thematic layers and objects belonging to the same layer. It turns out that the objects of a separate layer are saved in a separate file and have their own identifier system, which can be accessed as a certain set. As can be seen from Fig. 6, industrial areas, shopping centers, bus routes, roads, and population registration areas are placed in separate layers. Often one thematic layer is also divided horizontally - by analogy with separate sheets of maps. This is done for ease of database administration and to avoid working with large data files.
Within the layer model, there are two specific implementations: vector-topological and vector-non-topological models.
The first implementation is vector-topological, Fig. 7. This model has limitations: not all geometric types of objects can be placed in one sheet of one thematic layer at the same time. For example, in the ARC/INFO system, in one coverage you can place either only point objects, or only linear or polygon objects, or combinations thereof, excluding the case of “point polygonal” and three types of objects at once.
The vector-non-topological model of data organization is a more flexible model, but often only objects of one geometric type are placed in one layer. The number of layers in a layered data organization can be quite large and depends on the specific implementation. When organizing data in layers, it is convenient to manipulate large groups of objects represented by layers as a single whole. For example, you can turn layers on or off for rendering, and define operations based on how layers interact.
It should be noted that the layered data organization model absolutely dominates the raster data model.
Along with the layer model, an object-oriented model is used. This model uses a hierarchical grid (topographic classifier
In an object-oriented model, the emphasis is on the position of objects in some complex hierarchical classification scheme and on the relationships between objects. This approach is less common than the layer model due to the difficulty of organizing the entire system of relationships between objects.
As discussed above, information in a GIS is stored in geographic and attribute databases. Let's consider the principles of organizing information using the example of a vector model for representing spatial data.
Any graphic object can be represented as a family of geometric primitives with certain vertex coordinates, which can be calculated in any coordinate system. Geometric primitives differ in different GIS, but the basic ones are point, line, arc, and polygon. The location of a point object, such as a coal mine, can be described by a pair of coordinates (x, y). Objects such as a river, water supply, railway are described by a set of coordinates (x1, y2; ...; xn, yn), Fig. 9. Areal objects such as river basins, agricultural lands or polling stations are represented as a closed set of coordinates (x1, y1; ... xn, yn; x1, y1). The vector model is most suitable for describing individual objects and least suitable for reflecting continuously changing parameters.
In addition to coordinate information about objects, the geographic database can store information about the external design of these objects. This can be the thickness, color and type of lines, the type and color of the hatching of a polygonal object, the thickness, color and type of its borders. Each geometric primitive is associated with attribute information describing its quantitative and qualitative characteristics. It is stored in the fields of tabular databases, which are designed to store information of different types: text, numeric, graphic, video, audio. A family of geometric primitives and its attributes (descriptions) forms a simple object.
Modern object-oriented GIS work with entire classes and families of objects, which allows the user to gain a more complete understanding of the properties of these objects and their inherent patterns.
The relationship between the image of an object and its attribute information is possible through unique identifiers. They exist in explicit or implicit form in any GIS.
In many GIS, spatial information is presented as separate transparent layers with images of geographic features. The placement of objects on layers depends in each individual case on the characteristics of a particular GIS, as well as the characteristics of the tasks being solved. In most GIS, information on a separate layer consists of data from one database table. It happens that layers are formed from objects composed of homogeneous geometric primitives. These can be layers with point, line or area geographic objects. Sometimes layers are created based on certain thematic properties of objects, for example, layers of railway lines, layers of reservoirs, layers of natural resources. Almost any GIS allows the user to manipulate layers. The main control functions are the visibility/invisibility of the layer, editability, and accessibility. In addition, the user can increase the information content of a digital map by displaying the values of spatial attributes. Many GIS use raster images as the foundation layer for vector layers, which also improves the visual clarity of the image.
3 . Methods and technologies for modeling in GIS
In GIS, four main groups of modeling can be distinguished:
Semantic - at the level of information collection;
Invariant is the basis for the presentation of maps, through the use of special libraries, for example libraries of symbols and libraries of graphic elements;
Heuristic - communication between the user and the computer based on a scenario that takes into account the technological features of the software and the processing features of this category of objects (occupies a leading place in interactive processing and in control and correction processes)
Information - creation and transformation of various forms of information into a form specified by the user (is the main one in documentation support subsystems).
When modeling in GIS, the following software and technology blocks can be distinguished:
Operations for converting formats and presenting data. They are important for GIS as a means of exchanging data with other systems. Format conversion is carried out using special converter programs (AutoVEC, WinGIS, ArcPress).
Projection transformations. They transition from one map projection to another or from a spatial system to a map projection. As a rule, foreign software does not directly support projections common in our country, and information about the type of projection and its parameters is quite difficult to obtain. This determines the advantage of domestic GIS developments containing sets of necessary projection transformations. On the other hand, the various methods of working with spatial data that are widespread in Russia require analysis and classification.
Geometric analysis. For vector GIS models, these are operations of determining distances, lengths of broken lines, searching for points of intersection of lines; for raster - operations of identifying zones, calculating areas and perimeter of zones.
Overlay operations: overlaying layers of different names with the generation of derived objects and inheritance of their attributes.
Functional modeling operations:
calculation and construction of buffer zones (used in transport systems, forestry, when creating protective zones around lakes, when determining pollution zones along roads);
network analysis (allows you to solve optimization problems on networks - path search, allocation, zoning);
generalization (designed to select and display cartographic objects according to scale, content and thematic focus);
digital relief modeling (consists in building a database model that best represents the relief of the area under study).
4 . Information Security
A comprehensive information security system should be built taking into account the four levels of any information system (IS), incl. and geographic information system:
The application software (software) layer responsible for user interaction. Examples of IS elements operating at this level include the WinWord text editor, Excel spreadsheet editor, Outlook email program, Internet Explorer browser, etc.
The level of the database management system (DBMS), responsible for storing and processing information system data. Examples of IS elements operating at this level include Oracle DBMS, MS SQL Server, Sybase and even MS Access.
The operating system (OS) level, responsible for maintaining the DBMS and application software. Examples of IS elements operating at this level include Microsoft Windows NT, Sun Solaris, and Novell Netware.
The network level responsible for the interaction of information system nodes. Examples of IS elements operating at this level include the TCP/IP, IPS/SPX and SMB/NetBIOS protocols.
The security system must function effectively at all these levels. Otherwise, an attacker will be able to carry out one or another attack on GIS resources. For example, to gain unauthorized access to information about map coordinates in a GIS database, attackers may try to implement one of the following capabilities:
Send packets over the network with generated requests to obtain the necessary data from the DBMS or intercept this data during its transmission over communication channels (network level).
In order to prevent this or that attack from being carried out, it is necessary to promptly detect and eliminate information system vulnerabilities. And at all 4 levels. Security assessment systems or security scanners can help with this. These tools can detect and eliminate thousands of vulnerabilities on tens and hundreds of nodes, incl. and remote over considerable distances.
The combination of using various security measures at all levels of the GIS will make it possible to build an effective and reliable system for ensuring the information security of the geographic information system. Such a system will guard the interests of both users and employees of the company providing GIS services. It will reduce, and in many cases completely prevent, possible damage from attacks on the components and resources of the map information processing system.
5 . GIS Applications and Applications
Scientists have calculated that 85% of the information that a person encounters in his life has a territorial reference. Therefore, it is simply impossible to list all areas of application of GIS. These systems can be used in almost any area of human activity.
GIS are effective in all areas where the accounting and management of territory and objects on it is carried out. These are almost all areas of activity of governing bodies and administrations: land resources and real estate, transport, engineering communications, business development, ensuring law and order and security, emergency management, demography, ecology, healthcare, etc.
GIS allows you to accurately take into account the coordinates of objects and areas of sites. Due to the possibility of a comprehensive (taking into account many geographical, social and other factors) analysis of information about the quality and value of the territory and objects on it, these systems allow the most objective assessment of sites and objects, and can also provide accurate information about the tax base.
In the field of transport, GIS have long shown their effectiveness due to the ability to build optimal routes both for individual transportation and for entire transport systems, on the scale of an individual city or an entire country. At the same time, the ability to use the most up-to-date information about the state of the road network and capacity allows you to build truly optimal routes.
Accounting for municipal and industrial infrastructure is not an easy task in itself. GIS not only makes it possible to solve it effectively, but also to increase the impact of this data in case of emergency situations. Thanks to GIS, specialists from different departments can communicate in a common language.
The integration capabilities of GIS are truly limitless. These systems make it possible to keep records of the size, structure and distribution of the population and at the same time use this information to plan the development of social infrastructure, transport networks, optimal placement of healthcare facilities, fire brigades and law enforcement forces.
GIS allows monitoring the environmental situation and accounting for natural resources. They can not only answer where the “thin spots” are now, but also, thanks to the modeling capabilities, suggest where efforts and resources should be directed so that such “thin spots” do not arise in the future.
With the help of geographic information systems, relationships between various parameters (for example, soils, climate and crop yields) are determined, and locations of power grid breaks are identified.
Realtors use GIS to find, for example, all the houses in a certain area that have slate roofs, three rooms and 10-meter kitchens, and then return more detailed descriptions of these structures. The request can be refined by introducing additional parameters, for example, cost parameters. You can get a list of all houses located at a certain distance from a specific highway, forested area or place of work.
A utility company can clearly plan repairs or maintenance work, from obtaining complete information and displaying on a computer screen (or on paper copies) the affected areas, say a water main, to automatically identifying residents who will be affected by the work and notifying them them about the timing of the expected shutdown or interruption in water supply.
For satellite and aerial photographs, it is important that GIS can identify surface areas with a given set of properties reflected in the images in different parts of the spectrum. This is the essence of remote sensing. But in fact, this technology can be successfully applied in other areas. For example, in restoration: photographs of a painting in different areas of the spectrum (including invisible ones).
A geographic information system can be used to inspect both large areas (a panorama of a city, state or country) and a limited space, for example, a casino floor. Using this software, casino management staff receive color-coded cards that reflect the movement of money in games, bet sizes, pot draws, and other data from gambling machines.
GIS helps, for example, in solving such problems as providing a variety of information at the request of planning authorities, resolving territorial conflicts, choosing optimal (from different points of view and according to different criteria) places for placing objects, etc. The information required for decision-making can be presented in a concise cartographic form with additional textual explanations, graphs and diagrams.
GIS are used to graphically construct maps and obtain information about both individual objects and spatial data about areas, for example, the location of natural gas reserves, the density of transport communications, or the distribution of per capita income in a state. Areas marked on a map in many cases reflect the required information much more clearly than dozens of pages of reports with tables.
Conclusion
To summarize, it should be stated that GIS currently represents a modern type of integrated information system used in different directions. It meets the requirements of global informatization of society. GIS is a system that helps solve management and economic problems based on the means and methods of informatization, i.e. promoting the process of informatization of society in the interests of progress.
GIS as a system and its methodology are being improved and developed, its development is carried out in the following directions:
Development of theory and practice of information systems;
Study and generalization of experience in working with spatial data;
Research and development of concepts for creating a system of space-time models;
Improving the technology of automated production of electronic and digital cards;
Development of visual data processing technologies;
Development of decision support methods based on integrated spatial information;
GIS intellectualization.
Bibliography
1 Geoinformatics / Ivannikov A.D., Kulagin V.P., Tikhonov A.N. and others. M.: MAKS Press, 2001.349 p.
2 GOST R 6.30-97 Unified documentation systems. Unified system of organizational and administrative documentation. Documentation requirements. - M.: Standards Publishing House, 1997.
3 Andreeva V.I. Office work in the personnel service. Practical guide with sample documents. 3rd edition, corrected and expanded. - M.: JSC “Business School “Intel-Sintez”, 2000.
4 Verkhovtsev A.V. Record keeping in the personnel service - M.: INFRA-M, 2000.
5 Qualified directory of positions of managers, specialists and other employees / Ministry of Labor of Russia. - M.: “Economic News”, 1998.
6 Pechnikova T.V., Pechnikova A.V. Practice working with documents in an organization. Tutorial. - M.: Association of Authors and Publishers “Tandem”. EKMOS Publishing House, 1999.
7 Stenyukov M.V. Handbook of office work - M.: “Prior”. (edition 2, revised and expanded). 1998.
8 Trifonova T.A., Mishchenko N.V., Krasnoshchekov A.N. Geographic information systems and remote sensing in environmental research: A textbook for universities. - M.: Academic project, 2005. 352 p.
Application
Application
Job description of the chief accountant
The chief accountant performs the following duties:
1. Manages the organization’s accounting employees.
Internal labor regulations
Chief accountant accounting
2. Coordinates the appointment, dismissal and relocation of financially responsible persons of the organization.
Order of dismissal/hiring
HR department, chief accountant, accounting
3. Heads the work on the preparation and adoption of a working chart of accounts, forms of primary accounting documents used to formalize business transactions for which standard forms are not provided, and the development of forms of documents for the organization’s internal accounting financial statements.
Accounts, primary accounting documents
Accounting chief accountant
4. Coordinates with the director the directions for spending funds from the organization’s ruble and foreign currency accounts.
Expense of funds
Chief accountant director
5. Carry out an economic analysis of the economic and financial activities of the organization based on accounting and reporting data in order to identify intra-economic reserves, prevent losses and unproductive expenses.
Indicators for accounting accounting accounting
Financial department, economic department, accounting department, chief accountant
6. Participates in the preparation of internal control system measures to prevent the formation of shortages and illegal expenditure of funds and inventory, violations of financial and economic legislation.
Cash flow report
Accounting Chief Accountant
7. Signs, together with the head of the organization or authorized persons, documents serving as the basis for the acceptance and issuance of funds and inventory, as well as credit and settlement obligations.
Order for the release of funds order for the release of funds
Director, chief accountant, accounting
8. Monitors compliance with the procedure for preparing primary and accounting documents, calculations and payment obligations of the organization.
Primary accounting documents
Accounting chief accountant
9. Monitors compliance with established rules and deadlines for conducting an inventory of funds, inventory, fixed assets, settlements and payment obligations.
Inventory schedule
Chief accountant accounting
10. Monitors the collection of accounts receivable and repayment of accounts payable on time, and compliance with payment discipline.
Debt repayment plan reconciliation reports
Chief accountant accounting customers and suppliers of the organization
11. Controls the legality of writing off shortages, receivables and other losses from accounting accounts.
Invoices, reconciliation statements, invoices
Accounting chief accountant
12. Organizes timely reflection in the accounting accounts of transactions related to the movement of property, liabilities and business transactions.
Reports on the movement of property
Accounting chief accountant
13. Organizes accounting of the organization’s income and expenses, execution of cost estimates, sales of products, performance of work (services), results of the organization’s economic and financial activities.
Cost estimates, reports on services (work) performed
Accounting chief accountant
14. Organizes audits of the organization of accounting and reporting, as well as documentary audits in the structural divisions of the organization.
Memo schedule for checking accounting records
Chief accountant director, deputy accounting department
15. Ensures the preparation of reliable reporting for the organization based on primary documents and accounting records, and its submission to reporting users within the established time frame.
Accounting reports
Accounting chief accountant
16. Ensures the correct calculation and timely transfer of payments to the federal, regional and local budgets, contributions to state social, medical and pension insurance, timely settlements with contractors and wages.
Payment plan pension fund, insurance company
Chief accountant accounting tax office
17. Develops and implements measures aimed at strengthening financial discipline in the organization.
Rules for strengthening financial discipline
Chief accountant accounting
|
No. |
Management functions |
DutyOsti |
RelationshipOsewing departments |
Document |
ShowAteli |
||||
|
entrance |
exit |
entrance |
exit |
entrance |
exit |
||||
|
planning |
chief accountant, accounting |
director, chief accountant |
expenditure of funds, cash flow report, rules for strengthening financial discipline |
expense report |
|||||
|
organization |
2, 3, 7, 12, 13, 14, 15, 16 |
HR department, accounting, director, chief accountant |
chief accountant, accounting department, tax office, pension fund, insurance company |
order of dismissal/hiring, invoices, primary accounting documents, order for the issuance of funds, reports on the movement of property, cost estimates, reports on work (services) performed, memo, accounting reports, payment transfer plan |
order for the issuance of funds, schedule for checking the accounting records, report on the transfer of payments |
||||
|
control |
chief accountant, accounting department, chief accountant |
accounting, chief accountant, customers and suppliers of the organization |
internal labor regulations, primary accounting documentation, inventory schedule, debt repayment plan, accounts, reconciliation reports, invoices |
reconciliation acts |
|||||
|
financial department, economic department, accounting department |
Chief Accountant |
indicators for accounting |
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