- Sirdaryo viloyati Guliston shahar
- Dushanba-Shanba: 9.00 - 18.00
Nazarov Maqsud Geldiyorovich
Qurbonova Shabnam Istamali qizi
10.5281/zenodo.23360618
Annotatsiya
Ushbu maqolada Qashqadaryo viloyati hududida yer degradatsiyasi va cho‘llanish jarayonlarini masofadan zondlash (MZ) hamda geografik axborot tizimlari (GIS) texnologiyalari asosida baholashning ilmiy-metodik yondashuvlari tahlil qilingan. Tadqiqotda Landsat va Sentinel sun’iy yo‘ldosh ma’lumotlaridan foydalanib, o‘simlik qoplami, tuproqning ochiqligi, namlik holati, yer yuzasi harorati, sho‘rlanish va yer qoplamining o‘zgarishini tavsiflovchi masofaviy indikatorlardan foydalanish imkoniyatlari asoslangan. NDVI, SAVI, BSI, NDWI va LST kabi indikatorlarning degradatsiyaning turli komponentlarini aniqlashdagi o‘rni ko‘rib chiqilgan. GIS muhitida ushbu indikatorlarni hududiy birlashtirish, ko‘p mezonli ekologik baholash va degradatsiya xavfi yuqori bo‘lgan hududlarni ajratish metodikasi taklif etilgan. Shuningdek, UNCCD tomonidan qo‘llaniladigan yer qoplami, yer unumdorligi va tuproq organik uglerodi indikatorlarini integratsiyalash tamoyillari Qashqadaryo sharoitiga moslashtirish imkoniyati tahlil qilingan. Tadqiqot natijalari viloyat miqyosida yer degradatsiyasini ko‘p yillik monitoring qilish, degradatsiya o‘choqlarini aniqlash va ekologik xavf xaritalarini yaratish uchun metodik asos bo‘lib xizmat qiladi.
Kalit so'zlar:
yer degradatsiyasi, cho‘llanish, masofadan zondlash, GIS, NDVI, SAVI, BSI, NDWI, LST, sho‘rlanish, ekologik baholash, monitoring, Qashqadaryo viloyati.
Foydalanilgan adabiyotlar
2.Sims N.C., Barger N., Metternicht G., England J.R. A Land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality. Environmental Science & Policy, 2020, Vol. 114, pp. 1–6. 3.AbdelRahman M.A.E. An overview of land degradation, desertification and sustainable land management using GIS and remote sensing applications. Rendiconti Lincei. Scienze Fisiche e Naturali, 2023, Vol. 34, pp. 767–808. 4.Remote sensing of soil degradation: Progress and perspective. International Soil and Water Conservation Research, 2023, Vol. 11, Issue 3, pp. 429–454. DOI: 10.1016/j.iswcr.2023.03.002. 5.The use of remote sensing for desertification studies: A review. ScienceDirect, 2022. 6.Metternicht G.I., Zinck J.A. Remote sensing of soil salinity: potentials and constraints. Remote Sensing of Environment, 2003, Vol. 85, Issue 1. DOI: 10.1016/S0034 4257(02)00188-8. 7.Huete A.R. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 1988. 8.Rouse J.W., Haas R.H., Schell J.A., Deering D.W. Monitoring vegetation systems in the Great Plains with ERTS. NASA, 1974. 9.Gorelick N. et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 2017. 10.Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, Vol. 164, pp. 152 170. DOI: 10.1016/j.isprsjprs.2020.04.001. 11.Alshehri B., Zhang Z., Liu X. A Review of Google Earth Engine for Land Use and Land Cover Change Analysis: Trends, Applications, and Challenges. ISPRS International Journal of Geo-Information, 2025, 14(11), 416. DOI: 10.3390/ijgi14110416. 12.Review of Desert Mobility Assessment and Desertification Monitoring Based on Remote Sensing. Remote Sensing, 2023, 15(18), 4412. 13.Krupavathi Y.R., Anusha B.N., Raghu Babu K., Padma Sree P. Remote Sensing and GIS-Based Approaches for Soil Salinization Assessment: A Comprehensive Review. Journal of Remote Sensing & GIS, 2024, 15(03), 29–38.