Automated Method for Artificial Impervious Surface Area Mapping in Temperate, Tropical, and Arid Environments Using Hyperlocal Training Data With Sentinel-2 Imagery

Automated Method for Artificial Impervious Surface Area Mapping in Temperate, Tropical, and Arid Environments Using Hyperlocal Training Data With Sentinel-2 Imagery

This study presents an automated methodology to generate training data to map up-to-date artificial impervious surface (AIS) extent maps using two dates (winter and nonwinter) of a Sentinel-2 granule across six international sites (Egypt, India, Qatar, U.K., Eastern USA, and Western USA). It uses a...

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Bibliographic Details
Main Authors: Kristofer Lasko, Francis D. O'Neill
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Built-up
global impervious surface area (GISA)
global manmade impervious surface (GMIS)
image classification
impervious surface
machine learning
Online Access:https://ieeexplore.ieee.org/document/10301600/

Internet

https://ieeexplore.ieee.org/document/10301600/

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