Department of GIS-RS and Watershed Management, Maybod Branch, Islamic Azad University, Maybod, Yazd, Iran.
Department of Remote Sensing and GIS, Yazd Branch, Islamic Azad University, Yazd, Iran.
J Environ Manage. 2022 Jan 15;302(Pt A):113970. doi: 10.1016/j.jenvman.2021.113970. Epub 2021 Oct 25.
Land surface temperature (LST) and vegetation cover changes are two indicators of landscapes in a region. The relationship between LST anomalies, elevation, vegetation, and urban growth is significant to conservation. This study addresses this issue using night-time satellite imagery, kernel methods (points aggregation), and the trend analysis for a long-term period (2001-2017) in Iran. Variables for two seasons (summer and winter) in urban and natural land uses were derived using the Google Earth Engine (GEE) and NASA's Giovanni. Point data derived from raster maps were quantified using statistical kernel and trend analysis. As result, it was observed that LST rise in various elevations, seasons, and land uses. The LST was analyzed through kernels (point aggregation in scatter graphs), which shifted to the right. The LST anomaly in the daytime had the highest maximum value (>4 °C) and lowest minimum value (<-5 °C) in forests and mountains and metropolises with the highest population growth rate. Summer and winter seasons had positive trends in LST for forest and mountain land uses. All seasons had positive trends in EVI in the mountain, and desert land uses. This warming and increasing LST can increase vulnerability to drought, dust storms, floods, avalanches, and natural fires. The EVI is increasing over the years due to government projects in green spaces and urban parks. There is a need to protect urban and natural environments to prevent natural disasters and unplanned population growth.
陆地表面温度 (LST) 和植被覆盖变化是一个地区景观的两个指标。LST 异常、海拔、植被和城市增长之间的关系对保护具有重要意义。本研究使用夜间卫星图像、核方法（点聚合）和趋势分析来解决这个问题，研究时间跨度为 2001-2017 年。使用 Google Earth Engine (GEE) 和 NASA 的 Giovanni 从两个季节（夏季和冬季）的城市和自然土地利用中提取变量。从光栅图中提取的点数据使用统计核和趋势分析进行量化。结果表明，在不同海拔、季节和土地利用类型中，LST 呈上升趋势。通过核（散点图中的点聚合）分析 LST，其向右移动。白天的 LST 异常在森林和山区以及人口增长率最高的大都市中具有最高的最大值（>4°C）和最低的最小值（<-5°C）。森林和山区的夏季和冬季 LST 呈正趋势。山区和沙漠土地利用的所有季节的 EVI 都呈正趋势。这种变暖以及 LST 的升高可能会增加对干旱、沙尘暴、洪水、雪崩和自然火灾的脆弱性。由于政府在绿地和城市公园方面的项目，EVI 多年来一直在增加。需要保护城市和自然环境，以防止自然灾害和无计划的人口增长。
