Evaluation of Land Use Land Cover Changes in Response to Land Surface Temperature With Satellite Indices and Remote Sensing Data

被引:0
|
作者
Zhao, Qun [1 ]
Haseeb, Muhammad [2 ]
Wang, Xinyao [1 ]
Zheng, Xiangtian [1 ]
Tahir, Zainab [3 ]
Ghafoor, Sundas [3 ]
Mubbin, Muhammad [4 ]
Kumar, Ram Pravesh [5 ]
Purohit, Sanju [6 ]
Soufan, Walid [7 ]
Almutairi, Khalid F. [7 ]
机构
[1] Nanjing Inst Technol, Sch Comp Engn, Nanjing 211167, Peoples R China
[2] Univ Punjab, Dept Space Sci, Lahore 54780, Pakistan
[3] Univ Punjab, Ctr Geog Informat Syst CGIS, Lahore 54780, Pakistan
[4] Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, Johannesburg, South Africa
[5] Jawaharlal Nehru Univ, Sch Environm Sci, New Delhi 110067, India
[6] Akamai Univ, Dept Environm Ecol Studies & Sustainabil, Waimea, HI 96743 USA
[7] King Saud Univ, Coll Food & Agr Sci, Plant Prod Dept, Riyadh 11451, Saudi Arabia
关键词
Soil degradation; Climate change; Geospatial techniques; Pakistan; USE/COVER CHANGE; GIS; CLASSIFICATION; URBANIZATION; CYCLES; WATER; CITY; LST;
D O I
10.1016/j.rama.2024.07.003
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Land use and land cover (LULC) changes are known as the main factors causing soil degradation, which presents considerable obstacles to maintaining soil quality and the resilience of ecosystems. Human activities substantially impact LULC changes, particularly in areas experiencing rapid development. The objective of this study is to assess the changes in LULC, land surface temperature (LST), Normalized Differentiate Vegetation Index (NDVI), and Normalized Differentiate Built-up Index (NDBI) in Kasur District from 1991 to 2021. The study analyzed five major LULC classes: Water bodies, Urban areas, barren land, forest Cover, and vegetated areas. Our analysis revealed that the Urban area of Kasur expanded by around 16.27%. The vegetation cover experienced a slight decline of just 1%, while water bodies declined by 0.26%. Forest cover experienced a decrease of about 0.54%, and bare land decreased significantly by 14.4%. The imagery classification achieved an overall accuracy of 88% to 92%. The highest NDVI value was observed in 1991 ( + 0.89), while the lowest was in 2021 ( + 0.56). Similarly, the highest NDBI recorded was + 0.83 in 2021, while the lowest was + 0.65 in 1991. The linear regression analysis revealed a strong negative association between the NDVI and NDBI. LST results exhibited a 0.55 degrees C increase between the years 1991 and 2021. The study's findings align with the Sustainable Development Goals (SDGs), particularly SDG-15, which aims to protect, restore, and promote sustainable use of terrestrial ecosystems, sustain- ably manage forests, combat desertification, and halt land degradation and biodiversity loss. (c) 2024 The Society for Range Management. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:183 / 196
页数:14
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