Time-series dataset on land surface temperature, vegetation, built up areas and other climatic factors in top 20 global cities (2000-2018).

ABSTRACT: Time-series datasets of Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Normalized Difference Built Index (NDBI) and other climatic factors are of significance due to their application in tracking climate change in cities. In this paper, new data processing methods are presented using the application of Google Earth Engine (GEE) and GIS. Different variables including LST (both daytime and nighttime), NDVI, NDBI, rainfall, wind speed, evapotranspiration, and surface soil moisture were computed for 18 years from 2000 to 2018 with of use of GEE platform. The study areas cover 20 top global cities which were mentioned in the global cities index report in 2018 [1]. The data sources used on GEE are: MODIS Terra LST and Emissivity 8-Day Global 1km; MODIS Terra Veget

SUBMITTER: Jamei Y 

PROVIDER: S-EPMC6660608 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature