Urbanization in recent years plays an important role in increase in impervious areas with reducing in vegetation cover and pervious areas of natural landscape. This leads to a rise in temperature of urban areas, by se...Urbanization in recent years plays an important role in increase in impervious areas with reducing in vegetation cover and pervious areas of natural landscape. This leads to a rise in temperature of urban areas, by several degrees particularly at night [1,2]. A novel geospatial approach has been adopted to determine the maximum temperature areas (hot spots) over Kamrup Metro District of Assam, which is a gateway for seven neighboring north eastern states of India. The G statistics have been calculated for detecting the presence of hot spot or cold spot over the entire study area which is a new approach in urban heat island studies. The resultant z-scores and p-values show the pixels with either high or low values cluster spatially. For statistically significant positive z-scores, the larger the z-score is, the more intense the clustering of high values (hot spot) and vice versa. Land Surface Temperature (LST) anomaly values and percentage of Impervious Surface Area (ISA) along with climatic data are used to conform the hot spot location. It is one of the densely populated areas with more commercial pockets thereby giving rise to anthropogenic heat discharge which accelerates the heat island phenomenon. Incorporation of socio-economic survey data as well as certain biophysical parameters can be used to know about the cause and future impact of urbanization.展开更多
文摘Urbanization in recent years plays an important role in increase in impervious areas with reducing in vegetation cover and pervious areas of natural landscape. This leads to a rise in temperature of urban areas, by several degrees particularly at night [1,2]. A novel geospatial approach has been adopted to determine the maximum temperature areas (hot spots) over Kamrup Metro District of Assam, which is a gateway for seven neighboring north eastern states of India. The G statistics have been calculated for detecting the presence of hot spot or cold spot over the entire study area which is a new approach in urban heat island studies. The resultant z-scores and p-values show the pixels with either high or low values cluster spatially. For statistically significant positive z-scores, the larger the z-score is, the more intense the clustering of high values (hot spot) and vice versa. Land Surface Temperature (LST) anomaly values and percentage of Impervious Surface Area (ISA) along with climatic data are used to conform the hot spot location. It is one of the densely populated areas with more commercial pockets thereby giving rise to anthropogenic heat discharge which accelerates the heat island phenomenon. Incorporation of socio-economic survey data as well as certain biophysical parameters can be used to know about the cause and future impact of urbanization.