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Abstract
This study examines changes in vegetation cover (NDVI) and its relationship with land surface temperature (LST) in the Khas Kunar, Nur Gul, and Sawki districts of Kunar province from 2001 to 2024. Vegetation cover and land surface temperature are key indicators of environmental and climate change. Using Remote Sensing (RS) and Geographic Information System (GIS), Landsat satellite images were analyzed to extract NDVI and LST values for 2001, 2013, and 2024. The results show a decline in vegetation cover mainly due to deforestation, agricultural expansion, and urbanization. In areas with reduced vegetation, LST has generally increased, demonstrating an inverse relationship between NDVI and LST. However, some areas experienced slight decreases in temperature between 2013 and 2024, possibly due to environmental conditions or conservation efforts. The study highlights the need for sustainable land management, reforestation, and the development of urban green spaces to reduce rising temperatures and environmental degradation. These findings offer policymakers and ecological planners in the region helpful guidance.
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References
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References
احمدزی، ش. (2020). د افغانستان د ځنګلونو د تخریب او اقلیمي بدلونونو تحلیل. کابل: د کابل پوهنتون چاپ.
بارکزی، ف. (2018). د نباتي پوښښ د بدلونونو تحلیل د GIS او RS په وسیله. هرات: د هرات پوهنتون تحقیقاتي مرکز.
جلالزی، ن. (2019). د ځمکې د سطحي تودوخې او د نباتي پوښښ ترمنځ اړیکه. جغرافیه، 5(2), 45-60.
رحیمي، م. (2017). د افغانستان د اقلیم بدلونونه او د هغوی اغیزې. ننګرهار: د ننګرهار پوهنتون چاپ.
ستانکزی، ک. (2021). د ښاري سیمو پراخوالی او د حرارت درجې زیاتوالی. کندهار: د کندهار پوهنتون خپرونه.
ظاهر، ح. (2016). د کونړ د ځنګلونو د تخریب عوامل او پایلې. جغرافیایي څېړنه، 3(1), 88-101.
عبیدي، س. (2022). د افغانستان د ایکولوژیکي چاپېریال تحلیل. کابل: د علومو اکاډمۍ.
فایق، ی. (2023). د RS تخنیکونه د چاپېریالي ارزونو لپاره. کابل: د کابل پوهنتون جغرافیایي څېړنیز مرکز.
کریمي، ب .(2015) .د اقلیمي بدلونونو د کمولو لپاره د نباتي پوښښ ارزښت. ننګرهار پوهنتون.
نوری، س. (2020). د کونړ سیند پر چاپېریال اغېزې او د نباتي پوښښ بدلونونه. جغرافیه، 7(1), 112-125.
Anderson, J. R., Hardy, E. E., Roach, J. T., & Witmer, R. E. (2020). A Land Use and Land Cover Classification System for Remote Sensing Applications. US Geological Survey. https://doi.org/10.1016/j.jum.2020.05.004
Carlson, T. N., & Ripley, D. A. (2019). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1
Chen, X., & Dirmeyer, P. A. (2021). Impacts of Land Cover Change on Regional Climate. Climate Dynamics, 45(1-2), 303-319. https://doi.org/10.1155/2013/317678
Hansen, M. C., & Loveland, T. R. (2012). A review of large area monitoring of land cover change. Remote Sensing of Environment, 67(2), 23-45. https://doi.org/10.1016/j.rse.2011.08.024
IPCC. (2021). Climate Change 2021: The Physical Science Basis. Cambridge University Press. https://search.informit.org/doi/abs/10.3316/informit.315096509383738
Li, Z., Tang, B., Wu, H., Ren, H., & Yan, G. (2013). Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing, 14(10), 2155. https://doi.org/10.1016/j.rse.2012.12.008
NASA Earth Observatory. (2023). The Role of Vegetation in Surface Temperature Regulation. Retrieved from: www.earthobservatory.nasa.gov
Peng, S., Piao, S., Ciais, P., Friedlingstein, P., & Zhou, L. (2020). Surface Urban Heat Islands across 419 global big cities. Environmental Research Letters, 7(3), 034009. https://pubs.acs.org/doi/abs/10.1021/es2030438
Tucker, C. J. (2017). Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sensing of Environment, 8(2), 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
Weng, Q. (2022). Remote sensing of impervious surfaces and its environmental impacts. International Journal of Remote Sensing, 26(7), 1265-1275. https://doi.org/10.1016/j.rse.2011.02.030