Evaluating the Spatiotemporal Dynamics of Land Surface Temperature in Relation to the Land Use/Land Cover changes in Nag-Hammadi District, Egypt, using Remote Sensing and GIS

Q4 Social Sciences International Journal of Geoinformatics Pub Date : 2023-05-05 DOI:10.52939/ijg.v19i3.2599
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Abstract

In this study, three multi-temporal remotely sensed data acquired from Landsat-5 Thematic Mapper (TM) and Landsat -8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) in 1990, 2005, and 2020 were used. The maximum likelihood classifier (MLC) was opted to classify land use and land cover (LULC). Land surface temperature (LST) and LULC spectral indices i.e., Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Latent Heat Index (NDLI) and Bare Soil Index (BSI) have been computed and their relationships were examined. The overall accuracy of LULC was more than 93%. The analyses showed a notable transformation in LULC over the study period. For instance, built-up areas increased 103.7% with a rate of 45.5 ha/year and agriculture land increased by 28.9% with a rate of 186.4 ha/year. Whereas, bare soil was sharply decreased by 36.4% at a rate of 227.7ha/year. The minimum and maximum LST values increased by 2.9°C and 4.9°C, respectively, from 1990 to 2020. Furthermore, LST has a negative relationship with NDVI and NDLI (NDVI: 1990: r2 = 0.62; 2005: r2 = 0.62; 2020: r2 = 0.65. NDLI: 1990: r2 = 0.79; 2005: r2 = 0.78; 2020: r2 = 0.61) and a positive relationship with NDBI and BSI (NDBI: 1990: r2 = 0.68; 2005: r2 = 0.73; 2020: r2 = 0.44. BSI: 1990: r2 = 0.77; 2005: r2 = 0.78; 2020: r2 = 0.53). These results provided useful information about LULC changes and its impact on LST, which are necessary for experts and land-use planners to formulate sustainable LST mitigation policies, create an environmental comfort in Nag-Hammadi district, and other geographical locations with similar conditions.
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基于遥感和GIS的埃及纳格-哈马迪地区地表温度与土地利用/覆被变化的时空动态评价
利用Landsat-5主题成像仪(TM)和Landsat -8操作陆地成像仪/热红外传感器(OLI/TIRS)在1990年、2005年和2020年采集的3个多时相遥感数据进行研究。采用最大似然分类器(MLC)对土地利用和土地覆盖进行分类。计算了地表温度(LST)和LULC光谱指数,即归一化植被指数(NDVI)、归一化建筑指数(NDBI)、归一化潜热指数(NDLI)和裸土指数(BSI),并分析了它们之间的关系。LULC的总体准确度在93%以上。分析表明,在研究期间,LULC发生了显著的变化。例如,建成区面积增加了103.7%,以45.5公顷/年的速度增长,农业用地增加了28.9%,以186.4公顷/年的速度增长。裸地以227.7ha/年的速度急剧减少36.4%。1990 ~ 2020年,最小和最大地表温度分别上升2.9°C和4.9°C。此外,地表温度与NDVI和NDLI呈负相关(NDVI: 1990: r2 = 0.62;2005: r2 = 0.62;2020年:r2 = 0.65。NDLI: 1990: r2 = 0.79;2005: r2 = 0.78;2020年:r2 = 0.61),与NDBI和BSI呈正相关(NDBI: 1990年:r2 = 0.68;2005: r2 = 0.73;2020年:r2 = 0.44。BSI: 1990: r2 = 0.77;2005: r2 = 0.78;2020年:r2 = 0.53)。这些结果提供了关于土地土地覆盖面积变化及其对土地温度影响的有用信息,这些信息对于专家和土地利用规划者制定可持续的土地温度缓解政策、在纳格-哈马迪县和其他具有类似条件的地理位置创造舒适的环境是必要的。
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International Journal of Geoinformatics
International Journal of Geoinformatics Social Sciences-Geography, Planning and Development
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