{"id":6686,"date":"2017-06-22T10:59:56","date_gmt":"2017-06-22T08:59:56","guid":{"rendered":"http:\/\/www.geology.com.ua\/?page_id=6686"},"modified":"2021-06-21T11:31:29","modified_gmt":"2021-06-21T09:31:29","slug":"geoinformatika-2017-262-32-43","status":"publish","type":"page","link":"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-262-32-43\/","title":{"rendered":"Geoinformatika 2017; 2(62) : 32-43"},"content":{"rendered":"

Geoinformatika 2017; 2(62) : 32-43\u00a0<\/em>(in Ukrainian)<\/em><\/p>\n

APPROACHES TO INCREASE SPATIAL RESOLUTION OF SATELLITE IMAGES<\/h4>\n
V.G. Burachek<\/em>1<\/sup>, V.I. Zatserkovnyi<\/em>2<\/sup>, Ye.K. Uhlytskykh<\/em>2<\/sup><\/h5>\n

1<\/sup>University of the New Technologies, 28, Mashinobudivnikiv Str., Kyiv, 03067, Ukraine
\n<\/em>2<\/sup>Taras Shevchenko National University of Kyiv, Institute of Geology, 90, Vasylkivska Str., Kyiv, 03022, Ukraine e-mail: vbur2008@ukr.net, vitalii.zatserkovnyi@gmail.com, uglitskih_evgeniy_1993@mail.ru<\/em><\/p>\n

Purpose. <\/strong>One of the main unsolved problems in the use of aerospace images is the problem of developing new, more effective methods and software tools for automated interpretation of these data. With the modern processing of space images, there can be often a problem of interpreting small objects in the desired territory or increasing the accuracy of research. However, not all images have a good spatial resolution or are difficult to access. This problem can be solved by methods for improving the spatial resolution of space images by using subpixel technology. The purpose of the article is to develop and analyze the existing methods to increase the spatial resolution of space imagesand to select the most appropriate and accurate ones for modern research.<\/p>\n

Design\/methodology\/approach. <\/strong>The general methodology for increasing spatial resolution based on subpixel recording provides for a sequential transition from pixel grids of low-resolution input images to a subpixel grid of an enhanced spatial resolution created on their basis. Thus, within the same general field of view, n images are formed, geometri\u00adcally offset relative to each other by 1 \/ n pixel fraction.<\/p>\n

Findings. <\/strong>The above examples of solving the problem of increasing the resolution of aerospace images shows the reality and effectiveness of using sub-pixel technology. Among the proposed methods, we should emphasize allocated pan\u00adsharpening in the ENVI software package and the method of geometric comparison. They have fewer flaws compared to the rest. In addition, the subpixel recording method deserves special attention. Besides, in the analyzed methods, there is a description of increasing the spatial resolution for aerial photography.<\/p>\n

Practical value\/implications. <\/strong>It should be noted that in solving problems of large-scale mapping, digital cameras used today for aerial photography are inferior to photographic resolution, but they have many advantages, such as the possibility of automating the photogrammetric process, reducing its laboriousness, etc. In addition, increasing the resolution of space images after their processing with the software can help in solving modern problems in geology that need remote sensing. The work carried out makes it possible to apply the findings of the study to practical activities of geological enterprises and companies engaged in remote sensing research, to reduce the cost of obtaining quality information, and to effectively support decision-making in the management and monitoring processes.<\/p>\n

Keywords: <\/strong>aerospace photography, remote sensing, the sub-pixel technology.<\/p>\n

The full text of papers <\/span><\/a> <\/strong><\/em><\/span><\/p>\n

References:<\/strong><\/p>\n

    \n
  1. Baysa D.F., Burachek V.G., Zatserkovnyy V.I., Belenok V.Yu. Nauchno-issledovatel\u2019skaya rabota \u00abPriminenie tekhnologiy distantsionnogo zondirovaniya Zemli dlya resheniya zadach kadastra i monitoringa zemel\u2019\u00bb. Chernigov; Kiev, 2011 [In Russian].<\/li>\n
  2. Burachek V.Gh., Zacerkovnyj V.I., Belenok V.Ju. Analiz mozhlyvosti pidvyshhennja jakosti deshyfruvannja aerokosmich\u00adnykh znimkiv. Visnyk Chernighivsjkogho Derzhavnogho tekhnologhichnogho universytetu. Serija \u201cTekhnichni nauky\u201d<\/em>, 2010, no. 42, pp. 204-212 [In Ukrainian].<\/li>\n
  3. Burshtynsjka Kh.V., Stankevych S.A. Aerokosmichni znimaljni systemy. Lviv, Ljvivsjka politekhnika, 2010, 288 p. [In Ukrainian].<\/li>\n
  4. Selivanov A.S. Subpiksel\u2019naya obrabotka kak sposob povysheniya razreshayushchey sposobnosti v sistemakh distantsion\u00adnogo zondirovaniya. \u201cSovremennye problemy DZZ iz kosmosa\u201d. Vtoraya otkrytaya vserossiyskaya konferentsiya, <\/em>2004, p. 47 [In Russian].<\/li>\n
  5. Sposib cyfrovogho aerofotoznimannja: patent 79505 Ukraine. G02V 13\/08, GO3V 37\/00; 25.06.2007, Bjul. 9, 4 p. [In Ukrainian].<\/li>\n
  6. Tokareva O.S. Obrabotka i interpretatsiya dannykh distantsionnogo zondirovaniya Zemli. Tomsk, Izdatelstvo Tomskogo politekhnicheskogo universiteta, 2010, pp. 52-55 [In Russian].<\/li>\n
  7. Belenok V., Burachek V., Zatserkovniy V., Popov M., Stankevich S. Subpixel Image Acquisition for Detailed Aerospace Imaging. The Eights International Conference on Digital Technologies 2011. <\/em>Zilina, 2011, vol. 7, pp. 1-25.<\/li>\n
  8. Grodecki J., Dial G. Block Adjustment of High-Resolution Satellite Images described by Rational Polynomials. Photo\u00adgrammetric Engineering & Remote Sensing, <\/em>2003, vol. 69, pp. 59-68.<\/li>\n
  9. Herbert J. Kramer. Observation of the Earth and its Environment. Survey of Missions and Sensors. 4th Edition, <\/em>2002, 1510 p.<\/li>\n
  10. Liu H.Y., Zhang Y.S., Ji S. Study on the methods of super-resolution image reconstruction. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, <\/em>2008, vol. 37, part B2, pp.461-466.<\/li>\n
  11. Qian S.-E. A decadal P s D of near lossless data compression on-board satellites at Canadian Space Agency. Journal of Applied Remote Sensing<\/em>, 2010, vol. 4, pp. 21-22.<\/li>\n
  12. Rodriguez-Galiano V.F., Pardo-Iquizquiza E., Chica-Olmo M., Rigol-Sanchez J.P. Increasing the spatial resolution of thermal infrared images using cocriging. Science Direct, Procedia Environmental Sciences<\/em>, 2011, vol. 3, pp. 117-122.<\/li>\n
  13. SPEAR Pan Sharpening in ENVI. Available at: www.harrisgeospatial.com\/docs\/SPEARPPansharpenning.html (Accessed 27 November 2014).<\/li>\n
  14. Sushma Lalwani, Urma Ansari. A new approach for increase resolution of satellite image. IJETAE, <\/em>2012, vol. 2, pp. 47-55.<\/li>\n
  15. Ward K., Tough R., Watts S. Sea clutter: scattering, the K distribution and radar performance. Croydon, CPI Group Ltd, 2013, vol. 10, 586 p.<\/li>\n<\/ol>\n

    <\/p>","protected":false},"excerpt":{"rendered":"

    Geoinformatika 2017; 2(62) : 32-43\u00a0(in Ukrainian) APPROACHES TO INCREASE SPATIAL RESOLUTION OF SATELLITE IMAGES V.G. Burachek1, V.I. Zatserkovnyi2, Ye.K. Uhlytskykh2 1University of the New Technologies, 28, Mashinobudivnikiv Str., Kyiv, 03067, Ukraine 2Taras Shevchenko National University of Kyiv, Institute of Geology, 90, Vasylkivska Str., Kyiv, 03022, Ukraine e-mail: vbur2008@ukr.net, vitalii.zatserkovnyi@gmail.com, uglitskih_evgeniy_1993@mail.ru Purpose. One of the main unsolved problems in the use of aerospace images is the problem of developing new, more effective methods and software tools for automated interpretation of these data. With the modern processing of space images, there can be often a problem of interpreting small objects in the desired territory or increasing the accuracy of research. However, not all images have a good spatial resolution or are difficult to access. This problem can be solved by methods for improving the spatial resolution of space images by using subpixel technology. The purpose of the article is to develop and analyze the existing methods to increase the spatial resolution of space imagesand to select the most appropriate and accurate ones for modern research. Design\/methodology\/approach. The general methodology for increasing spatial resolution based on subpixel recording provides for a sequential transition from pixel grids of low-resolution input images to a subpixel grid of an enhanced spatial resolution created on their basis. Thus, within the same general field of view, n images are formed, geometri\u00adcally offset relative to each other by 1 \/ n pixel fraction. Findings. The above examples of solving the problem of increasing the resolution of aerospace images shows the reality and effectiveness of using sub-pixel technology. Among the proposed methods, we should emphasize allocated pan\u00adsharpening in the ENVI software package and the method of geometric comparison. They have fewer flaws compared to the rest. In addition, the subpixel recording method deserves special attention. Besides, in the analyzed methods, there is a description of increasing the spatial resolution for aerial photography. Practical value\/implications. It should be noted that in solving problems of large-scale mapping, digital cameras used today for aerial photography are inferior to photographic resolution, but they have many advantages, such as the possibility of automating the photogrammetric process, reducing its laboriousness, etc. In addition, increasing the resolution of space images after their processing with the software can help in solving modern problems in geology that need remote sensing. The work carried out makes it possible to apply the findings of the study to practical activities of geological enterprises and companies engaged in remote sensing research, to reduce the cost of obtaining quality information, and to effectively support decision-making in the management and monitoring processes. Keywords: aerospace photography, remote sensing, the sub-pixel technology. The full text of papers References: Baysa D.F., Burachek V.G., Zatserkovnyy V.I., Belenok V.Yu. Nauchno-issledovatel\u2019skaya rabota \u00abPriminenie tekhnologiy distantsionnogo zondirovaniya Zemli dlya resheniya zadach kadastra i monitoringa zemel\u2019\u00bb. Chernigov; Kiev, 2011 [In Russian]. Burachek V.Gh., Zacerkovnyj V.I., Belenok V.Ju. Analiz mozhlyvosti pidvyshhennja jakosti deshyfruvannja aerokosmich\u00adnykh znimkiv. Visnyk Chernighivsjkogho Derzhavnogho tekhnologhichnogho universytetu. Serija \u201cTekhnichni nauky\u201d, 2010, no. 42, pp. 204-212 [In Ukrainian]. Burshtynsjka Kh.V., Stankevych S.A. Aerokosmichni znimaljni systemy. Lviv, Ljvivsjka politekhnika, 2010, 288 p. [In Ukrainian]. Selivanov A.S. Subpiksel\u2019naya obrabotka kak sposob povysheniya razreshayushchey sposobnosti v sistemakh distantsion\u00adnogo zondirovaniya. \u201cSovremennye problemy DZZ iz kosmosa\u201d. Vtoraya otkrytaya vserossiyskaya konferentsiya, 2004, p. 47 [In Russian]. Sposib cyfrovogho aerofotoznimannja: patent 79505 Ukraine. G02V 13\/08, GO3V 37\/00; 25.06.2007, Bjul. 9, 4 p. [In Ukrainian]. Tokareva O.S. Obrabotka i interpretatsiya dannykh distantsionnogo zondirovaniya Zemli. Tomsk, Izdatelstvo Tomskogo politekhnicheskogo universiteta, 2010, pp. 52-55 [In Russian]. Belenok V., Burachek V., Zatserkovniy V., Popov M., Stankevich S. Subpixel Image Acquisition for Detailed Aerospace Imaging. The Eights International Conference on Digital Technologies 2011. Zilina, 2011, vol. 7, pp. 1-25. Grodecki J., Dial G. Block Adjustment of High-Resolution Satellite Images described by Rational Polynomials. Photo\u00adgrammetric Engineering & Remote Sensing, 2003, vol. 69, pp. 59-68. Herbert J. Kramer. Observation of the Earth and its Environment. Survey of Missions and Sensors. 4th Edition, 2002, 1510 p. Liu H.Y., Zhang Y.S., Ji S. Study on the methods of super-resolution image reconstruction. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, vol. 37, part B2, pp.461-466. Qian S.-E. A decadal P s D of near lossless data compression on-board satellites at Canadian Space Agency. Journal of Applied Remote Sensing, 2010, vol. 4, pp. 21-22. Rodriguez-Galiano V.F., Pardo-Iquizquiza E., Chica-Olmo M., Rigol-Sanchez J.P. Increasing the spatial resolution of thermal infrared images using cocriging. Science Direct, Procedia Environmental Sciences, 2011, vol. 3, pp. 117-122. SPEAR Pan Sharpening in ENVI. Available at: www.harrisgeospatial.com\/docs\/SPEARPPansharpenning.html (Accessed 27 November 2014). Sushma Lalwani, Urma Ansari. A new approach for increase resolution of satellite image. IJETAE, 2012, vol. 2, pp. 47-55. Ward K., Tough R., Watts S. Sea clutter: scattering, the K distribution and radar performance. Croydon, CPI Group Ltd, 2013, vol. 10, 586 p.<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-6686","page","type-page","status-publish","hentry"],"yoast_head":"\nGeoinformatika 2017; 2(62) : 32-43 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-262-32-43\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Geoinformatika 2017; 2(62) : 32-43 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\" \/>\n<meta property=\"og:description\" content=\"Geoinformatika 2017; 2(62) : 32-43\u00a0(in Ukrainian) APPROACHES TO INCREASE SPATIAL RESOLUTION OF SATELLITE IMAGES V.G. Burachek1, V.I. Zatserkovnyi2, Ye.K. Uhlytskykh2 1University of the New Technologies, 28, Mashinobudivnikiv Str., Kyiv, 03067, Ukraine 2Taras Shevchenko National University of Kyiv, Institute of Geology, 90, Vasylkivska Str., Kyiv, 03022, Ukraine e-mail: vbur2008@ukr.net, vitalii.zatserkovnyi@gmail.com, uglitskih_evgeniy_1993@mail.ru Purpose. One of the main unsolved problems in the use of aerospace images is the problem of developing new, more effective methods and software tools for automated interpretation of these data. With the modern processing of space images, there can be often a problem of interpreting small objects in the desired territory or increasing the accuracy of research. However, not all images have a good spatial resolution or are difficult to access. This problem can be solved by methods for improving the spatial resolution of space images by using subpixel technology. The purpose of the article is to develop and analyze the existing methods to increase the spatial resolution of space imagesand to select the most appropriate and accurate ones for modern research. Design\/methodology\/approach. The general methodology for increasing spatial resolution based on subpixel recording provides for a sequential transition from pixel grids of low-resolution input images to a subpixel grid of an enhanced spatial resolution created on their basis. Thus, within the same general field of view, n images are formed, geometri\u00adcally offset relative to each other by 1 \/ n pixel fraction. Findings. The above examples of solving the problem of increasing the resolution of aerospace images shows the reality and effectiveness of using sub-pixel technology. Among the proposed methods, we should emphasize allocated pan\u00adsharpening in the ENVI software package and the method of geometric comparison. They have fewer flaws compared to the rest. In addition, the subpixel recording method deserves special attention. Besides, in the analyzed methods, there is a description of increasing the spatial resolution for aerial photography. Practical value\/implications. It should be noted that in solving problems of large-scale mapping, digital cameras used today for aerial photography are inferior to photographic resolution, but they have many advantages, such as the possibility of automating the photogrammetric process, reducing its laboriousness, etc. In addition, increasing the resolution of space images after their processing with the software can help in solving modern problems in geology that need remote sensing. The work carried out makes it possible to apply the findings of the study to practical activities of geological enterprises and companies engaged in remote sensing research, to reduce the cost of obtaining quality information, and to effectively support decision-making in the management and monitoring processes. Keywords: aerospace photography, remote sensing, the sub-pixel technology. The full text of papers References: Baysa D.F., Burachek V.G., Zatserkovnyy V.I., Belenok V.Yu. Nauchno-issledovatel\u2019skaya rabota \u00abPriminenie tekhnologiy distantsionnogo zondirovaniya Zemli dlya resheniya zadach kadastra i monitoringa zemel\u2019\u00bb. Chernigov; Kiev, 2011 [In Russian]. Burachek V.Gh., Zacerkovnyj V.I., Belenok V.Ju. Analiz mozhlyvosti pidvyshhennja jakosti deshyfruvannja aerokosmich\u00adnykh znimkiv. Visnyk Chernighivsjkogho Derzhavnogho tekhnologhichnogho universytetu. Serija \u201cTekhnichni nauky\u201d, 2010, no. 42, pp. 204-212 [In Ukrainian]. Burshtynsjka Kh.V., Stankevych S.A. Aerokosmichni znimaljni systemy. Lviv, Ljvivsjka politekhnika, 2010, 288 p. [In Ukrainian]. Selivanov A.S. Subpiksel\u2019naya obrabotka kak sposob povysheniya razreshayushchey sposobnosti v sistemakh distantsion\u00adnogo zondirovaniya. \u201cSovremennye problemy DZZ iz kosmosa\u201d. Vtoraya otkrytaya vserossiyskaya konferentsiya, 2004, p. 47 [In Russian]. Sposib cyfrovogho aerofotoznimannja: patent 79505 Ukraine. G02V 13\/08, GO3V 37\/00; 25.06.2007, Bjul. 9, 4 p. [In Ukrainian]. Tokareva O.S. Obrabotka i interpretatsiya dannykh distantsionnogo zondirovaniya Zemli. Tomsk, Izdatelstvo Tomskogo politekhnicheskogo universiteta, 2010, pp. 52-55 [In Russian]. Belenok V., Burachek V., Zatserkovniy V., Popov M., Stankevich S. Subpixel Image Acquisition for Detailed Aerospace Imaging. The Eights International Conference on Digital Technologies 2011. Zilina, 2011, vol. 7, pp. 1-25. Grodecki J., Dial G. Block Adjustment of High-Resolution Satellite Images described by Rational Polynomials. Photo\u00adgrammetric Engineering & Remote Sensing, 2003, vol. 69, pp. 59-68. Herbert J. Kramer. Observation of the Earth and its Environment. Survey of Missions and Sensors. 4th Edition, 2002, 1510 p. Liu H.Y., Zhang Y.S., Ji S. Study on the methods of super-resolution image reconstruction. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, vol. 37, part B2, pp.461-466. Qian S.-E. A decadal P s D of near lossless data compression on-board satellites at Canadian Space Agency. Journal of Applied Remote Sensing, 2010, vol. 4, pp. 21-22. Rodriguez-Galiano V.F., Pardo-Iquizquiza E., Chica-Olmo M., Rigol-Sanchez J.P. Increasing the spatial resolution of thermal infrared images using cocriging. Science Direct, Procedia Environmental Sciences, 2011, vol. 3, pp. 117-122. SPEAR Pan Sharpening in ENVI. Available at: www.harrisgeospatial.com\/docs\/SPEARPPansharpenning.html (Accessed 27 November 2014). Sushma Lalwani, Urma Ansari. A new approach for increase resolution of satellite image. IJETAE, 2012, vol. 2, pp. 47-55. Ward K., Tough R., Watts S. Sea clutter: scattering, the K distribution and radar performance. Croydon, CPI Group Ltd, 2013, vol. 10, 586 p.\" \/>\n<meta property=\"og:url\" content=\"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-262-32-43\/\" \/>\n<meta property=\"og:site_name\" content=\"\u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\" \/>\n<meta property=\"article:modified_time\" content=\"2021-06-21T09:31:29+00:00\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/geoinformatika-2017-262-32-43\\\/\",\"url\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/geoinformatika-2017-262-32-43\\\/\",\"name\":\"Geoinformatika 2017; 2(62) : 32-43 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\",\"isPartOf\":{\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/#website\"},\"datePublished\":\"2017-06-22T08:59:56+00:00\",\"dateModified\":\"2021-06-21T09:31:29+00:00\",\"breadcrumb\":{\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/geoinformatika-2017-262-32-43\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[[\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/geoinformatika-2017-262-32-43\\\/\"]]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/geoinformatika-2017-262-32-43\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Geoinformatika 2017; 2(62) : 32-43\"}]},{\"@type\":\"WebSite\",\"@id\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/#website\",\"url\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/\",\"name\":\"\u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb\",\"description\":\"\u0426\u0435\u043d\u0442\u0440 \u043c\u0435\u043d\u0435\u0434\u0436\u043c\u0435\u043d\u0442\u0443 \u0442\u0430 \u043c\u0430\u0440\u043a\u0435\u0442\u0438\u043d\u0433\u0443 \u0432 \u0433\u0430\u043b\u0443\u0437\u0456 \u043d\u0430\u0443\u043a \u043f\u0440\u043e \u0417\u0435\u043c\u043b\u044e\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"http:\\\/\\\/www.geology.com.ua\\\/en\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Geoinformatika 2017; 2(62) : 32-43 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"http:\/\/www.geology.com.ua\/en\/geoinformatika-2017-262-32-43\/","og_locale":"en_US","og_type":"article","og_title":"Geoinformatika 2017; 2(62) : 32-43 - \u0421\u0430\u0439\u0442 \u0436\u0443\u0440\u043d\u0430\u043b\u0443 \u00ab\u0413\u0435\u043e\u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0442\u0438\u043a\u0430\u00bb","og_description":"Geoinformatika 2017; 2(62) : 32-43\u00a0(in Ukrainian) APPROACHES TO INCREASE SPATIAL RESOLUTION OF SATELLITE IMAGES V.G. Burachek1, V.I. Zatserkovnyi2, Ye.K. Uhlytskykh2 1University of the New Technologies, 28, Mashinobudivnikiv Str., Kyiv, 03067, Ukraine 2Taras Shevchenko National University of Kyiv, Institute of Geology, 90, Vasylkivska Str., Kyiv, 03022, Ukraine e-mail: vbur2008@ukr.net, vitalii.zatserkovnyi@gmail.com, uglitskih_evgeniy_1993@mail.ru Purpose. One of the main unsolved problems in the use of aerospace images is the problem of developing new, more effective methods and software tools for automated interpretation of these data. With the modern processing of space images, there can be often a problem of interpreting small objects in the desired territory or increasing the accuracy of research. However, not all images have a good spatial resolution or are difficult to access. This problem can be solved by methods for improving the spatial resolution of space images by using subpixel technology. The purpose of the article is to develop and analyze the existing methods to increase the spatial resolution of space imagesand to select the most appropriate and accurate ones for modern research. Design\/methodology\/approach. The general methodology for increasing spatial resolution based on subpixel recording provides for a sequential transition from pixel grids of low-resolution input images to a subpixel grid of an enhanced spatial resolution created on their basis. Thus, within the same general field of view, n images are formed, geometri\u00adcally offset relative to each other by 1 \/ n pixel fraction. Findings. The above examples of solving the problem of increasing the resolution of aerospace images shows the reality and effectiveness of using sub-pixel technology. Among the proposed methods, we should emphasize allocated pan\u00adsharpening in the ENVI software package and the method of geometric comparison. They have fewer flaws compared to the rest. In addition, the subpixel recording method deserves special attention. Besides, in the analyzed methods, there is a description of increasing the spatial resolution for aerial photography. Practical value\/implications. It should be noted that in solving problems of large-scale mapping, digital cameras used today for aerial photography are inferior to photographic resolution, but they have many advantages, such as the possibility of automating the photogrammetric process, reducing its laboriousness, etc. In addition, increasing the resolution of space images after their processing with the software can help in solving modern problems in geology that need remote sensing. The work carried out makes it possible to apply the findings of the study to practical activities of geological enterprises and companies engaged in remote sensing research, to reduce the cost of obtaining quality information, and to effectively support decision-making in the management and monitoring processes. 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