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首页> 外文期刊>Climate >Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq
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Urban Land Use Land Cover Changes and Their Effect on Land Surface Temperature: Case Study Using Dohuk City in the Kurdistan Region of Iraq

机译:城市土地利用的土地覆盖变化及其对地表温度的影响:以伊拉克库尔德地区的多胡克市为例

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The growth of urban areas has a significant impact on land use by replacing areas of vegetation with residential and commercial areas and their related infrastructure; this escalates the land surface temperature (LST). Rapid urban growth has occurred in Duhok City due to enhanced political and economic growth during the period of this study. The objective is to investigate the effect of land use changes on LST; this study depends on data from three Landsat images (two Landsat 5-TM and Landsat OLI_TIRS-8) from 1990, 2000 and 2016. Supervised classification was used to compute land use/cover categories, and to generate the land surface temperature (LST) maps the Mono-window algorithm was used. Images were also used to create the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBAI) and normalized difference water index (NDWI) maps. Linear regression analysis was used to generate relationships between LST with NDVI, NDBI, NDBAI and NDWI. The study outcome proves that the changes in land use/cover have a significant role in the escalation of land surface temperatures. The highest temperatures are associated with barren land and built-up areas, ranging from 47°C, 50°C, 56°C while lower temperatures are related to water bodies and forests, ranging from 25°C, 26°C, 29°C respectively, in 1990, 2000 and 2016. This study also proves that NDVI and NDWI correlate negatively with low temperatures while NDBI and NDBAI correlate positively with high temperatures.
机译:城市地区的增长通过用住宅和商业区及其相关基础设施代替植被来对土地利用产生重大影响;这会升高陆地表面温度(LST)。在此研究期间,由于政治和经济增长的增强,杜霍克市出现了快速的城市增长。目的是调查土地利用变化对土地使用税的影响;这项研究基于1990年,2000年和2016年的三张Landsat影像(两张Landsat 5-TM和Landsat OLI_TIRS-8)中的数据。监督分类用于计算土地使用/覆盖类别,并生成地表温度(LST)映射使用了Mono-window算法。图像还用于创建归一化差异植被指数(NDVI),归一化差异累积指数(NDBI),归一化差异裸露指数(NDBAI)和归一化差异水指数(NDWI)图。线性回归分析用于生成LST与NDVI,NDBI,NDBAI和NDWI之间的关系。研究结果证明,土地利用/覆盖面积的变化在土地表面温度的升高中起着重要作用。最高温度与荒芜土地和建成区相关,范围为47°C,50°C,56°C,而较低温度与水体和森林相关,范围为25°C,26°C,29°分别在1990年,2000年和2016年达到C。这项研究还证明NDVI和NDWI与低温呈负相关,而NDBI和NDBAI与高温呈正相关。

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