Azər­bay­can əra­zi­lə­ri­nin uzun müddət ər­zin­də er­mə­ni iş­ğalı altın­da qal­ması, so­si­al-iq­ti­sa­di sarsıntı­ların həd­din­dən artıq ağrılı for­ma­ları, həm­çi­nin bit­ki örtüyü və tor­paq­dan is­ti­fa­də də da­xil ol­maq­la, ət­raf mühit­də aş­kar dağıdıcı ge­oe­ko­lo­ji də­yi­şik­lik­lər­lə nə­ti­cə­lən­di. Bu­na görə də, 2016-cı il­dən 2021-ci ilə­dək çə­kil­miş yüksək həl­let­mə qa­bi­liy­yə­ti­nə ma­lik “Sen­ti­nel-2” çoxs­pekt­ral peyk təs­vir­lə­ri­nin, həm­çi­nin bit­ki­lə­rin (NDVI) və su­ların (NDWI) nor­mal­laşdırılmış müxtə­lif­lik in­deks­lə­ri­nin iş­lə­nil­mə me­tod­ların­dan is­ti­fa­də edil­miş­dir. Seq­men­ta­si­ya pro­ses­lə­ri və eCog­ni­ti­on De­ve­lo­per təs­ni­fat­ları və Terr­Set ID­RI­SI Sel­va proq­ram tə­mi­natı tət­biq olun­maq­la, (OBIA) təs­vir­lə­rin ob­yekt­lər üzrə səmt­lən­miş təh­li­li kor­rek­tə edil­miş, eh­ti­mal olu­nan qay­da­lar­la, qə­fəs av­to­mat­larının Mar­kov zən­ci­ri­nin (CA-MC) mo­de­li ya­radılmışdı. Da­ha son­ra OB­İA me­tod­ları təs­diq­lə­di ki, bu əra­zi­nin er­mə­ni qo­şun­ları tə­rə­fin­dən iş­ğalının son il­lə­rin­də (2016-2020) mən­fi də­yi­şik­lik­lə­rin ək­sə­riy­yə­ti əsa­sən me­şə­lər­də (-4.7%) və ot­laq örtüklə­rin­də (-4.6%) aş­kar edil­miş­dir). Bun­dan əla­və, eti­barlı CA-MA proq­nos­tik xə­ri­tə­si, yaxın il­lər­də həm is­ti­fa­də­yə ya­rasız tor­paq­lar­da (+4.8%), həm də tərk edil­miş (+5%) əra­zi­lər­də nə­zə­rə­çar­pa­caq artım­ların ola­cağını göstə­rir. Nə­ti­cə eti­ba­ri­lə, höku­mə­tin ye­ni­dən­qur­ma və bər­pa la­yi­hə­lə­ri­nə baş­la­ması ilə əla­qə­dar coğ­ra­fi­yaçı­ların, eko­sis­tem alim­lə­ri­nin və uzaq­dan zond­la­ma mütə­xəs­sis­lə­ri­nin ən ak­tu­al və­zi­fə­si Azər­bay­canın iş­ğal­dan azad edil­miş tor­paq­ları üzrə mövcud peyk görüntülə­ri­nin də­qiq iş­lən­mə­si və müva­fiq xə­ri­tə­lə­rin hazır­lan­ması ol­malıdır.

Açar sözlər: tor­paq örtüyü və tor­paq is­ti­fa­də­sin­də­ki də­yi­şik­lik­lər, Sen­ti­nel-2 peyk görüntülə­ri, di­na­mik və hüdud spekt­ral in­deks­lə­mə­si, el­mi əsaslı OBIA təs­ni­fatı, CA-MC proq­noz xə­ri­tə­lə­ri

ƏDƏBİYYAT

Adhikari S., Southworth J.  Simulating forest cover changes of Bannerghatta National Park based on a CA-Markov model: a remote sensing approach. Remote Sens., Vol. 4, No. 10, 2012, pp. 3215-3243.

Baatz M., Schape A. Multi-resolution segmentation – an optimization approach for high quality multi-scale segmentation. In: (Strobl J. et al. eds.) Angewandte Geographische Informations verarbeitung XII, Beiträgezum AGIT Symposium Salsburg 2000, Karlruhe, Herbert Wichmann Verlag, 2000, pp. 12-23.

Bahadur K. Improving Landsat and IRS image classification: evaluation of unsupervised and supervised classification through band ratios and DEM in a mountainous landscape in Nepal. Remote Sensing, Vol. 1, No. 4, 2009, pp. 1257-1272.

Baumann M., Radeloff V., Avedian V., Kuemmerle T. Land-use change in the Caucasus during and after the Nagorno-Karabakh conflict. Reg. Environ. Change, Vol. 15, 2015, pp. 1703-1716.

Benz U., Hofmann P., Willhauck G., Lingenfelder I., Heynen M. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogram­metry and Remote Sensing, Vol. 58, No. 3, 2004, pp. 239-258.

Berger  M., Moreno J., Johannessen  J.A., Levelt  P.F., Hanssen R.F. ESA’s Sentinel missions in support of Earth system science. Remote Sens. Environ., Vol. 120, 2012, pp. 84-90.

Blaschke T. Object-based image analysis for remote sensing. ISPRS International Journal of Photogrammetry and Remote Sensing, Vol. 65, No. 1, 2010, pp. 2-16.

Caballero I., Ruiz J., Navarro G. Sentinel-2 satellites provide near-real time evaluation of catastrophic floods in the West Mediterranean. Water, Vol. 11, No. 12, 2019, p. 2499.

Chander G., Markham B.L., Helder D.L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1, ALI sensors. Remote sensing of environment, Vol. 113, No. 5, 2009, pp. 893-903.

Clark Labs, Clark University. “TerrSet Geospatial Monitoring and Modeling System”. Clark University, USA, Accessed 21 February 2017, https://clarklabs.org/wp-content/uploads/ 2016/03/TerrSet18-2_Brochure_WEB.pdf.

Copernicus, Sentinel-2, Satellite Missions – eoPortal Directory. Directory.eoportal.org. Retrieved 5 March 2020, https://eoportal.org/web/eoportal/satellite-missions/c-missions/copernicus-sentinel-2-2020.

Dozier J. Spectral signature of Alpine snow cover from LANDSAT Thematic Mapper. Remote Sensing of Environment, Vol. 45, 1989, pp. 9-22.

Drusch M., Del Bello U., Carlier S., Colin O., Fernandez V., Gascon F., Hoersch B., Isola C., Laberinti P., Martimort P. Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sens. Environ., Vol. 120, 2012, pp. 25-36.

Duarte D., Nex F., Kerle N. Vosselman G. Satellite image classification of building damages using airborne and satellite image samples in a deep learning approach. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, Vol. 4-2, 2018, pp. 89-96.

Eastman J.R. IDRISI taiga guide to GIS and image processing. Clark Labs for Cartographic Technology and Geographic Analysis, Clark University, Worcester, MA, USA, 2009, 141 p.

eCognition Reference Book. eCognition Developer for Windows operating system, Version 9.5.1, Trimble, 2019, https://ecognition.blog/whats-new-in-ecognition-9-5-1/.

FAOSTAT. Statistical database of the Food and Agricultural Organization. 2014, Available at: http://faostat.fao.org/.

Foody G.M. Status of land cover classification accuracy assessment. Remote Sensing of Environment, Vol. 80, No. 1, 2002, pp. 185-201.

Franklin S.E., Wulder M.A. Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas. Progress in Physical Geography, Vol. 26, No. 2, 2002, pp.173-205.

General Assembly Security Council. Letter dated 30 September 2009 from the Permanent Representative of Azerbaijan to the United Nations addressed to the Secretary-General, Protracted conflicts in the GUAM area and their implications for international peace, security and development. The situation in the occupied territories of Azerbaijan. Security Council Sixty-fourth session, 2009.

Giovarelli R., Bledsoe D. Land reform in Eastern Europe: Western CIS, Transcaucuses, Balkans, and EU Accession Countries. Prepared for FAO (Food and Agriculture Organization) by the Rural Development Institute (RDI), Seattle, Washington, 2001, http://www.fao.org/3/AD878E/AD878E00.htm.

Hasanov Z.M., Ibrahimov Z.A., Nabiyev V.R. Beech forests of Azerbaijan: The modern condition, age structure and regeneration. Annals of Agrarian Science, Vol. 15, No. 4, 2017, pp. 453-457.

Hay G.J., Castilla G. Object-based image analysis, strengths, weaknesses, opportunities, and threats (SWOTs). From OBIA 2006 International Archives of Photogrammetry, Remote sensing, and Spatial Information Science, 2006.

Hay G.J., Castilla G. Geographic object-based image analysis (GEOBIA): a new name for a new discipline. In: (Blaschke T., Lang S., Hay G.J. eds.) Object-based image analysis: spatial concepts for knowledge-driven remote sensing applications. Springer. Berlin, Germany, 2008, pp. 75-89.

Hussain M., Chen D., Cheng A., Wel H., Stanley D. Change detection from remotely sensed images: from pixel-based to object-based approaches. ISPRS J. Photogramm. Remote Sens., Vol. 80, 2013, pp. 91-106.

Ikokou G., Smit J. A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes. South Afr. J. of Geomatics, Vol. 2, No. 4, 2013, pp. 358-369.

Kamusoko C. Remote sensing image classification in R. (Springer Geography) 1st ed. Springer .2019, 237 p.

Kato L. Integrating open-street map data: in object-based land-cover and land-use classification for disaster recovery. LAP LAMBERT Academic Publishing. 2020, 76 p.

Keshtkar H., Voigt W. A spatiotemporal analysis of landscape change using an integrated Markov chain and cellular automata models. Model. Earth Syst. Environ., Vol. 2, No. 10, 2016.

Khandelwal P., Singh K., Mehrotra A. Unsupervised change detection from satellite images using KCN. LAP LAMBERT Academic Publishing. 2014, 100 p.

Khatami R., Mountrakis G., Stehman S.V. A meta-analysis of remote sensing research on supervised pixel-based land cover image classification processes: general guidelines for practitioners and future research. Remote Sens. Environ., Vol. 177, 2016, pp. 89-100.

Langat P.K., Kumar L., Koech R., Ghosh M.K. Monitoring of land use/land-cover dynamics using remote sensing: A case of Tana River Basin, Kenya. Geocarto Intern., Vol. 36, No. 13, 2019, pp. 1470-1488.

Lillesand T., Kiefer R. Chipman J. Remote sensing and image interpretation. 5th ed. John Wiley and Sons Inc. New York, 2004, 763 p.

Liu S. Qi Z. Li X. Gar-On A. Integration of convolutional neural networks and object-based post-classification refinement for land use and land cover mapping with optical and SAR data. Journal of Remote Sensing, Vol. 11, No. 6, 2019, pp. 690, https://doi.org/10.3390/rs11060690.

Lobo A., Chick O.A., Casterad A. Classification of Mediterranean crops with multisensor data: Per-pixel versus per-object statistics and image segmentation. International Journal of Remote Sensing, Vol. 17, No.12, 1996, pp. 2385-2400.

Mammadov R., Rasouli A.A. Practical satellite image processing inside the ERDAS imagine. Provided for the Fast Training Program. Publisher: “The Institute of Geography of Azerbaijan National Academy of Sciences”.  Baku, Azerbaijan, 2021, 350 p.

Mammadov R., Rasouli A.A., Mobasher H. Applying an object-based classification approach through a cellular automata-Markov method in land-cover/landuse change detection procedure, case of the Urmia Lake. Proceeding of the Eurasian GIS 2018 Congress 04-07 September 2018 – Baku, Azerbaijan. Published by Nobel Akademik Yayıncılık Eğitim Danışmanlık Tic. Ltd. Şti Baku/Azerbaijan. 2018, pp. 272-284.

Meer F.D., Werff H.M.A., Ruitenbeek F.J.A. Potential of ESA’s Sentinel-2 for geological applications. Remote Sens. Environ., Vol. 148, 2014, pp.124-133.

Nagorno-Karabakh conflict: finding common ground in respect of the dead. International Displacement Monitoring Centre (IDMC). News and Press Release ICRC, 2021, 16 April.

Nelson S., Khorram S. Image processing and data analysis with ERDAS IMAGINE. 1st ed. CRC Press. 2018, 350 p.

Pettorelli N.  The normalized difference vegetation index. 1st Edition, Kindle Edition. OUP Oxford. 2013, 224 p.

Platt R.V., Rapoza L. An evaluation of an object-oriented paradigm for land use/land cover classification. The Professional Geographer, Vol. 60, No.1, 2008, pp. 87-100.

Pontius R.G., Malanson J. Comparison of the structure and accuracy of two land change models. International Journal of Geographical Information Science, Vol.19, No. 2, 2005, pp. 745-748.

Rasouli A.A., Mammadov G.Sh., Asgarova M.M. Mastering spatial data analysis inside the GIS setting. Elm. Baku, 2021a, 396 p.

Rasouli A.A., Mammadov R., Asgarova M.M. Application of satellite image processing methods in mapping of landcover/landuse changes inside the Karabakh liberated territories. Materials of the On-line Conference of the Azerbaijan National Academy of sciences “Biodiversity of Karabakh, land and water resources: past, present and future”, 2021b, p.132.

Rasouli A., Mammadov R. Preliminary satellite image analysis processing the Landsat imagery inside the ArcGIS setting. Lambert Academy Publishing. Germany, 2020, 264 p.    

Rasouli A.A., Mammadov R., Aliyev V. Detection of Caspian Sea coastline changes by Fuzzy-based object-oriented image analysis. Abbstracts of The Second Eurasian RISK-2020 Conference and Symposium, 12-19 April, 2020 – Tbilisi / GEORGIA, 2020, https://books.aijr.org/index.php/press/catalog/book/93.

Rasouli A.A., Mammadov R., Mobasher H. Object-based water bodies extraction method by processing of Sentinel satellite imagery case study: Baku City, Azerbaijan. Proceeding of Eurasian GIS 2018 Congress 04-07 September 2018 – Baku, Azerbaijan. Published by Nobel Akademik Yayın­cılık Eğitim Danışmanlık Tic. Ltd. Şti Baku/Azerbaijan. 2018a, pp. 284-290. 

Rasouli A.A., Mammadov R., Pishnamaz M., Hushmand A., Safarov  E. Assessment of forest cover changes by applying object-oriented procedures inside the Qarabağ Occupied Region. Eurasian GIS 2018 Congress 04-07 September 2018 – Baku, Azerbaijan. Published by Nobel Akademik Yayıncılık Eğitim Danışmanlık Tic. Ltd. Şti Baku/Azerbaijan. 2018b, p. 74.    

Rasouli A.A., Mammadov R., Safarov E., Mohammadzadeh K. Fuzzy object-based landcover/use mapping of The Karabagh region by processing of Sentinel satellite imageries. Eurasian GIS 2018 Congress 04-07 September 2018 – Baku, Azerbaijan. Published by Nobel Akademik Yayıncılık Eğitim Danışmanlık Tic. Ltd. Şti Baku/Azerbaijan. 2018c, p.73.   

Rehman S., Hussain M. Fuzzy C-means algorithm based satellite image segmentation. Indonesian Journal of electrical engineering and computer science, Vol. 9, No. 2, 2018, pp. 332-334.

Report: Investigating the environmental dimensions of the 2020 Nagorno-Karabakh conflict. Conflict and Environment Observatory, Published: February 2021, Categories: Publications, Law and Policy.

Roy S., Farzana K., Papia M., Hasan M. Monitoring and prediction of land use/land cover change using the integration of Markov chain model and cellular automation in the Southeastern Tertiary Hilly Area of Bangladesh. Int. J. Sci. Basic Appl. Res., Vol. 24, No. 4, 2015, pp. 125-148.

Sayilan M.O. 1988-95 Arası dağlık Karabağ Sorunu. Master Project. Ankara University, Ankara, 2007, 54 p.

Scheffer M. Foreseeing tipping points. Nature, Vol. 467, No. 7314, 2010, pp.  411-412.

Sentinel Online. MultiSpectral Instrument (MSI) Overview, European Space Agency. Retrieved 3 December 2018, https://www.esa.int/.

Sentinel-2 MSI User Guides. Radiometric Resolutions, Sentinel-2 MSI, Sentinel Online. Sentinel.ESA.int. Retrieved 5 March 2020,   https://sentinels.copernicus.eu/web/sentinel/user-guides/ sentinel-2-msi/resolutions/radiometric.

Song X., Duan Z., Jiang X. Comparison of artificial neural networks and support vector machine classifiers for land cover classification in Northern China using a SPOT-5 HRG image. International Journal of Remote Sensing, Vol. 33, No. 10, 2012, pp. 3301-3320.

Sylven M., Reinvang R., Andersone-Lilley Z. Climate change in southern Caucasus: impacts on nature, people and society. Report WWF Norway. 2009, pp. 1-35.

Teodoro A., Araujo R. Exploration of the OBIA methods available in SPRING non-commercial software to UAV data processing. In: Proceedings of the Earth Resources and Environmental Remote Sensing/GIS Applications V, Amsterdam, the Netherlands, Vol. 9245, 2014.

Thenkabail P.S., Lyon J.G.,  Huete A. Fundamentals, sensor systems, spectral libraries, and data mining for vegetation (hyperspectral remote sensing of vegetation). The 2nd ed., CRC Press. 2018, 489 p.

Tiede D., Krafft P., Fureder, P., Lang S. Stratified template matching to support refugee camp analysis in OBIA-Workflows. Remote Sens., Vol. 9, No. 4, 2017, 326 .p

Valigholizadeh A., Karimi M. Geographical explanation of the factors disputed in the Karabakh geopolitical crisis. Journal of Eurasian Studies, Vol.7, 2016, pp. 172-180.

Yagoub M., Bizreh A. Prediction of land cover change using Markov and cellular automata models: the case of Al-Ain, UAE, 1992-2030. Journal of the Indian Society of Remote Sensing, Vol.42, No. 3, 2014, pp. 665-671.

“Azərbaycan Respublikasında iqtisadi rayonların yeni bölgüsü haqqında” Azərbaycan Respublikası Prezidentinin 2021-ci il 7 iyul tarixli 1386 nömrəli Fərmanı, 2021, https://president.az/articles/52389.