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本文引用的文献

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Sci Data. 2020 Jul 20;7(1):242. doi: 10.1038/s41597-020-00580-5.

东南亚大都市地表温度及选定环境与社会经济特征的网格化数据集。

Gridded dataset on land surface temperature and selected environmental and socioeconomic features in Southeast Asian metropolises.

作者信息

Pagkalinawan Homer, Delina Laurence L, Macagba Sharon Feliza Ann

机构信息

Macroeconomics Research Division, Asian Development Bank, Mandaluyong City, Philippines.

Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.

出版信息

Data Brief. 2024 Aug 29;57:110848. doi: 10.1016/j.dib.2024.110848. eCollection 2024 Dec.

DOI:10.1016/j.dib.2024.110848
PMID:39290428
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11404075/
Abstract

As Southeast Asia grapples with extreme heat occurrences in recent years, mapping which areas are clustered with elevated temperatures is crucial for monitoring the at-risk population. Identifying the contributing factors to the warming trends in these areas is also vital in formulating adaptation and mitigation strategies. This dataset comprises land surface temperature (LST) in three metropolises in the region - Metropolitan Manila, Bangkok Metropolitan Area, and Greater Jakarta - downloaded and processed from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. We used MODIS' inherent grid system to map LST values at the satellite image's most granular level. We combined them with selected environmental and socioeconomic variables, including building and built-up areas, areas of greeneries, industrial zones, and water bodies, nighttime light (to approximate areas of economic activities), gridded population, distance from water bodies, and indicators on which urban infrastructures, i.e. roads and airports, are present in each grid. Available in shapefile and comma-separate variable file format, this dataset is useful for urban studies in these three cities. The dataset can be easily updated as additional data on LST and other variables becomes available.

摘要

近年来,东南亚地区面临极端高温天气,绘制高温聚集区域地图对于监测高危人群至关重要。识别这些地区变暖趋势的影响因素对于制定适应和缓解策略也至关重要。该数据集包含该地区三个大都市——马尼拉大都会、曼谷都会区和大雅加达——的陆地表面温度(LST),这些数据是从中等分辨率成像光谱仪(MODIS)仪器下载并处理的。我们使用MODIS的固有网格系统在卫星图像的最精细级别绘制LST值。我们将这些数据与选定的环境和社会经济变量相结合,包括建筑和建成区、绿地面积、工业区和水体、夜间灯光(用于估算经济活动区域)、网格化人口、与水体的距离以及每个网格中城市基础设施(即道路和机场)的指标。该数据集以shapefile和逗号分隔变量文件格式提供,对这三个城市的城市研究很有用。随着LST和其他变量的更多数据可用,该数据集可以轻松更新。