Maximum Fraction Images Derived from Year-Based Project for On-Board Autonomy-Vegetation (PROBA-V) Data for the Rapid Assessment of Land Use and Land Cover Areas in Mato Grosso State, Brazil

Maximum Fraction Images Derived from Year-Based Project for On-Board Autonomy-Vegetation (PROBA-V) Data for the Rapid Assessment of Land Use and Land Cover Areas in Mato Grosso State, Brazil

This paper presents a new approach for rapidly assessing the extent of land use and land cover (LULC) areas in Mato Grosso state, Brazil. The novel idea is the use of an annual time series of fraction images derived from the linear spectral mixing model (LSMM) instead of original bands. The LSMM was...

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Bibliographic Details
Main Authors: Henrique Luis Godinho Cassol, Egidio Arai, Edson Eyji Sano, Andeise Cerqueira Dutra, Tânia Beatriz Hoffmann, Yosio Edemir Shimabukuro
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Land
Subjects:
spectral unmixing
machine learning
fraction images
cloud computing
Online Access:https://www.mdpi.com/2073-445X/9/5/139

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https://www.mdpi.com/2073-445X/9/5/139

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