Urban Land Use and Land Cover Change Analysis Using Random Forest Classification of Landsat Time Series

Urban Land Use and Land Cover Change Analysis Using Random Forest Classification of Landsat Time Series

Efficient implementation of remote sensing image classification can facilitate the extraction of spatiotemporal information for land use and land cover (LULC) classification. Mapping LULC change can pave the way to investigate the impacts of different socioeconomic and environmental factors on the E...

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Detaylı Bibliyografya
Asıl Yazarlar: Saeid Amini, Mohsen Saber, Hamidreza Rabiei-Dastjerdi, Saeid Homayouni
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: MDPI AG 2022-06-01
Seri Bilgileri:Remote Sensing
Konular:
cloud computing
Google Earth Engine
Landsat time series
LULC change detection
pan-sharpening
pixel-based image classification
Online Erişim:https://www.mdpi.com/2072-4292/14/11/2654

Internet

https://www.mdpi.com/2072-4292/14/11/2654

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