GEOSPATIAL DATA PROCESSING CHARACTERISTICS FOR ENVIRONMENTAL MONITORING TASKS

被引:2
|
作者
Butenko, Olga [1 ]
Horelik, Stanislav [1 ]
Zynyuk, Oleh [2 ,3 ]
机构
[1] Natl Aerosp Univ, Kharkiv Aviat Inst, Dept Geoinformat Technol & Space Monitoring Earth, Fac Rocket & Space Engn, 17 Chkalova Str, UA-61070 Kharkiv, Ukraine
[2] Natl Acad Sci Ukraine, Western Sci Ctr, 4 Matejka Str, UA-79007 Lvov, Ukraine
[3] Minist Educ & Sci Ukraine, 4 Matejka Str, UA-79007 Lvov, Ukraine
关键词
Criterion trees; Geoinformation systems; Photogrammetric processing; Remote sensing; Space monitoring; Hierarchical segmentation;
D O I
10.21307/ACEE-2020-008
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper explores the specifics of working with geospatial data when making decisions about the current environmental status of objects based on Earth space monitoring data. The expediency of sharing statistical data, Earth remote sensing data, and contact measurements is displayed. An analysis of the specifics of this approach to solving the problems of complex processing of multi-temporal a priori data obtained by various shooting equipment was carried out. The existing methods for combining such data are analyzed and possible options for reducing temporary resources and reducing requirements for information resources when working with large volumes of information are considered. It is appropriate to use the method of hierarchical partitioning of multi-temporal image data or images of the analyzed areas obtained at the same time, but from different satellites taking into account the specifics of the shooting equipment and subject to their correspondence to the given a priori geospatial information. One of the criteria for hierarchical partitioning is the identification of areas of greatest correspondence with a priori data with their geographical reference in satellite imagery to reduce the localization time of the corresponding zones throughout the analyzed image array. The economic application effect of this method is substantiated by reducing the computational complexity of costly pattern matching processes, as well as performance improvement of change determination algorithms in topological and geometric characteristics of these objects. An algorithm is shown for detecting changes in heterogeneity in images based on the result of overlay operations with time-differentiated satellite imagery. To confirm the adequacy of the proposed method, the results of its practical implementation are shown on the Ukraine-Poland border area. A comparative analysis of the obtained results with real data is carried out.
引用
收藏
页码:103 / 114
页数:12
相关论文
共 50 条
  • [1] Framework for prioritizing geospatial data processing tasks during extreme weather events
    Hu, Xuan
    Gong, Jie
    ADVANCED ENGINEERING INFORMATICS, 2019, 39 : 157 - 169
  • [2] GeoGPT: An assistant for understanding and processing geospatial tasks
    Zhang, Yifan
    Wei, Cheng
    He, Zhengting
    Yu, Wenhao
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 131
  • [3] Complex Event Processing with Geospatial Support for Monitoring and Controlling Compliance with Environmental Regulations
    Herrera, Federico
    Gonzalez, Laura
    Calegari, Daniel
    PROCEEDINGS OF THE 2016 XLII LATIN AMERICAN COMPUTING CONFERENCE (CLEI), 2016,
  • [4] Annotating Uncertainty in Geospatial and Environmental Data
    Ioup, Elias
    Yang, Zhao
    Barre, Brent
    Sample, John
    Shaw, Kevin B.
    Abdelguerfi, Mahdi
    IEEE INTERNET COMPUTING, 2015, 19 (01) : 18 - 27
  • [5] Research on Dynamic Scheduling of Grid Monitoring Data Processing Tasks Based Storm
    Shao-guang, Yuan
    Yong-li, Zhu
    Guo-liang, Zhou
    Ming-kun, Wang
    MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II, 2014, 651-653 : 1051 - 1055
  • [6] Software packages for automation of environmental monitoring and experimental data processing
    Kachiashvili, KJ
    Gordeziani, DG
    Melikdzhanian, DY
    Khuchua, VI
    Stepanishvili, VA
    GEOECOLOGY AND COMPUTERS, 2000, : 273 - 278
  • [7] Processing High-Volume Geospatial Data: A case of monitoring Heavy Haul Railway operations
    Sangat, Prajwol
    Indrawan-Santiago, Maria
    Taniar, David
    Oh, Beng
    Reichl, Paul
    INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE 2016 (ICCS 2016), 2016, 80 : 2221 - 2225
  • [8] Parallel Processing Strategies for Big Geospatial Data
    Werner, Martin
    FRONTIERS IN BIG DATA, 2019, 2
  • [9] Development of methodology for visualization and processing of geospatial data
    Aleshko, R.A.
    Guriev, A.T.
    Shoshina, K.V.
    Schenikov, V.S.
    Scientific Visualization, 2015, 7 (01): : 20 - 29
  • [10] PROBLEMS OF COLLECTING, PROCESSING AND SHARING GEOSPATIAL DATA
    Wadowska, Agata
    Peska-Siwik, Agnieszka
    Maciuk, Kamil
    ACTA SCIENTIARUM POLONORUM-FORMATIO CIRCUMIECTUS, 2022, 21 (3-4) : 5 - 16