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A New Spatiotemporal Model for Analyzing the Variations of Urban Heat Islands Using Remotely Sensed Multi Spectral Images: The Case of Mashhad City, Iran
Journal of the Indian Society of Remote Sensing ( IF 2.5 ) Pub Date : 2021-07-16 , DOI: 10.1007/s12524-021-01404-8
Rana Nanjam 1 , Farshid Farnood Ahmadi 1
Affiliation  

Urban heat islands (UHIs) refer to areas of the earth’s surface with higher temperatures than neighboring regions. The spread of this phenomenon varies according to spatial and temporal dimensions, and these variations are affected mainly by changes in land cover and heat emissions from human activities. Due to the high variations in the unit of time, the spatial continuity, and expansion of this phenomenon, remote sensing is a suitable tool for studying it. The purpose of this study is to present a fixed model with general thresholds for studying UHIs. Therefore, the fixed model was adjusted based on the features that exhibit similar behaviors to respond to the temporal and spatial variations of the urban heat and cool islands. To achieve this objective, one of the cities of Iran with high UHIs intensity and vastity was assigned as the study area. Therefore, the UHIs of Iranian cities were investigated from the Moderate Resolution Imaging Spectroradiometer (MODIS) production by applying the Getis-ord algorithm on the land surface temperature (LST) map obtained by the split-window method. Then, the UHIs of Mashhad were studied by applying clustering on the LST map of Landsat images. In this study, the UHIs of different seasons of 2018 for Mashhad were interpreted based on the LST, and the results showed that the UHIs show different behavior in different seasons in terms of location and intensity. Therefore, it is necessary to extract features that exhibit similar behavior for UHIs. Features or the emergence of UHIs were analyzed by statistical methods, principal component analysis (PCA), and regression. The results of the principal component analysis showed that the four indices (Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI), Normalized Difference Bareness Index (NDBaI), and Normalized Difference Water Index (NDWI) are useful features for studying UHIs. On the other hand, these features were suitable for presenting a fixed model for examining the UHIs of different seasons. The results of the fixed multivariate regression model with different thresholds had an average overall accuracy (OA) of 82.15% for different seasons, and the results for the fixed model with fixed thresholds had an average overall accuracy of 83.54% for summer and winter and 59.1% for spring and autumn.



中文翻译:

使用遥感多光谱图像分析城市热岛变化的新时空模型:伊朗马什哈德市的案例

城市热岛 (UHI) 是指地球表面温度高于邻近地区的区域。这种现象的传播因时空维度而异,而这些变化主要受土地覆盖变化和人类活动热排放的影响。由于这种现象的单位时间变化大、空间连续性和扩展性强,遥感是研究它的合适工具。本研究的目的是提出一个具有通用阈值的固定模型,用于研究 UHI。因此,固定模型根据表现出相似行为的特征进行调整,以响应城市热岛和冷岛的时空变化。为了实现这一目标,伊朗的一个城市 UHI 强度和面积都很大,被指定为研究区域。因此,通过将 Getis-ord 算法应用于通过分裂窗口方法获得的地表温度 (LST) 地图,从中分辨率成像光谱仪 (MODIS) 产品中研究了伊朗城市的 UHI。然后,通过在 Landsat 图像的 LST 地图上应用聚类来研究马什哈德的 UHI。本研究基于 LST 对马什哈德 2018 年不同季节的 UHI 进行了解释,结果表明 UHI 在不同季节在位置和强度方面表现出不同的行为。因此,有必要为 UHI 提取表现出相似行为的特征。通过统计方法、主成分分析 (PCA) 和回归分析了 UHI 的特征或出现。和归一化差异水指数 (NDWI) 是研究 UHI 的有用特征。另一方面,这些特征适合呈现一个固定的模型来检查不同季节的 UHI。具有不同阈值的固定多元回归模型的结果对于不同季节的平均总体准确度(OA)为82.15%,具有固定阈值的固定模型的结果对于夏季和冬季的平均总体准确率为83.54%和59.1 % 春季和秋季。和归一化差异水指数 (NDWI) 是研究 UHI 的有用特征。另一方面,这些特征适合呈现一个固定的模型来检查不同季节的 UHI。具有不同阈值的固定多元回归模型的结果对于不同季节的平均总体准确度(OA)为82.15%,具有固定阈值的固定模型的结果对于夏季和冬季的平均总体准确率为83.54%和59.1 % 春季和秋季。

更新日期:2021-07-18
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