Abstract
Urban areas play a very important role in global climate change. There is increasing need to understand global urban areas with sufficient spatial details for global climate change mitigation. Remote sensing imagery, such as medium resolution Landsat daytime multispectral imagery and coarse resolution Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light imagery, has provided a powerful tool for characterizing and mapping cities, with advantages and disadvantages. Here we propose a framework to merge cloud and cloud shadow-free Landsat Normalized Difference Vegetation Index (NDVI) composite and DMSP/OLS Night Time Light (NTL) to characterize global urban areas at a 30 m resolution, through a Normalized Difference Urban Index (NDUI) to make full use of them while minimizing their limitations. We modify the maximum NDVI value multi-date image compositing method to generate the cloud and cloud shadow-free Landsat NDVI composite, which is critical for generating a global NDUI. Evaluation results show the NDUI can effectively increase the separability between urban areas and bare lands as well as farmland, capturing large scale urban extents and, at the same time, providing sufficient spatial details inside urban areas. With advanced cloud computing facilities and the open Landsat data archives available, NDUI has the potential for global studies at the 30 m scale.
Highlights
Due to broad impacts of the concentrated built environment and human activities, cities are considered agents of global change [1]
Gaps due to SLC-off in the ETM+ images over both sites are filled in the composites generated with the proposed Mixed Normalized Difference Vegetation Index (NDVI) criteria, while they are still visible in the composites generated with the Maximum NDVI criteria
NDVI composites with coarse resolution DMSP/OLS nighttime light (NTL) images to better characterize urban areas, distinguishing them from non-urban land features at a much finer resolution
Summary
Due to broad impacts of the concentrated built environment and human activities, cities are considered agents of global change [1]. Occupying only about 2% of the global land surface [2], cities worldwide are hosting more than 50% of the world’s population [3], producing more than. As a major factor shaping the Earth system, the importance of cities is increasing rapidly [7]. By 2100, 70%–90% of the world’s population, which is projected to add another three billion, will live in urban regions [8]. Practical carbon emission mitigation strategies require knowledge of cities down to the street and individual building level [10]
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