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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Discriminating Land Use and Land Cover Classes in Brazil Based on the Annual PROBA-V 100 m Time Series

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Author(s):
Shimabukuro, Yosio Edemir [1] ; Arai, Egidio [1] ; Duarte, Valdete [1] ; Dutra, Andeise Cerqueira [1] ; Godinho Cassol, Henrique Luis [1] ; Sano, Edson Eyji [2] ; Hoffmann, Tania Beatriz [1]
Total Authors: 7
Affiliation:
[1] Brazilian Natl Inst Space Res, Remote Sensing Div, BR-12227010 Sao Paulo, SP - Brazil
[2] Embrapa Cerrados, BR-73301970 Planaltina, DF - Brazil
Total Affiliations: 2
Document type: Journal article
Source: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING; v. 13, p. 3409-3420, 2020.
Web of Science Citations: 0
Abstract

Brazil, with more than 8 million km(2), presents six different biomes, ranging from natural grasslands (Pampa biome) to tropical rainfall forests (Amazonia biome), with different land-use types (mostly pasturelands and croplands) and pressures (mainly in the Cerrado biome). The objective of this article is to present a new method to discriminate the most representative land use and land cover (LULC) classes of Brazil, based on the PROBA-V images. The images were converted into vegetation, soil, and shade fraction images by applying the linear spectral mixing model. Then, the pixel-based, highest proportion, annual mosaics of the fraction images, and their corresponding standard deviation images were derived and classified using the random forest algorithm. The following LULC classes were considered: forestlands, shrublands, grasslands, croplands, pasturelands, water bodies, and others. An agreement analysis was conducted with two available LULC maps derived from the Landsat satellite, the MapBiomas, and the Finer Resolution Observation and Monitoring-Global Land Cover (FROM-GLC) projects. Forestlands (412 million ha) and pasturelands (242 million ha) were the two most representative LULC classes; and croplands accounted for 30 million ha. The results presented an overall agreement of 69% and 58% with the MapBiomas and FROM-GLC projects, respectively. The proposed method is a good alternative to support operational projects of LULC map production that are important for planning biodiversity conservation or environmentally sustainable land occupation. (AU)

FAPESP's process: 16/19806-3 - Mapping and monitoring forest degradation using remote sensing data with medium and moderate spatial resolution
Grantee:Yosio Edemir Shimabukuro
Support type: Regular Research Grants
FAPESP's process: 18/14423-4 - Modeling a decade of carbon gross emissions from forest fires in the Amazon: Conciliating the bottom-up and top-down views of the problem
Grantee:Henrique Luis Godinho Cassol
Support type: Scholarships in Brazil - Post-Doctorate