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Comparative Analysis of the Global Forest/Non-Forest Maps Derived from SAR and Optical Sensors. Case Studies from Brazilian Amazon and Cerrado Biomes

Sano, Edson and Rizzoli, Paola and Koyama, Christian and Watanabe, Manabu and Adami, Marcos and Shimabukuro, Yosio E. and Bayma, Gustavo and Freitas, Daniel M. (2021) Comparative Analysis of the Global Forest/Non-Forest Maps Derived from SAR and Optical Sensors. Case Studies from Brazilian Amazon and Cerrado Biomes. Remote Sensing. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs13030367. ISSN 2072-4292.

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Abstract

Global-scale forest/non-forest (FNF) maps are of crucial importance for applications like biomass estimation and deforestation monitoring. Global FNF maps based on optical remote sensing data have been produced by the wall-to-wall satellite image analyses or sampling strategies. The German Aerospace Center (DLR) and the Japan Aerospace Exploration Agency (JAXA) also made available their global FNF maps based on synthetic aperture radar (SAR) data. This paper attempted to answer the following scientific question: how comparable are the FNF products derived from optical and SAR data? As test sites we selected the Amazon (tropical rainforest) and Cerrado (tropical savanna) biomes, the two largest Brazilian biomes. Forest estimations from 2015 derived from TanDEM-X (X band; HH polarization) and ALOS-2 (L band; HV polarization) SAR data, as well as forest cover information derived from Landsat 8 optical data were compared with each other at the municipality and image sampling levels. The optical-based forest estimations considered in this study were derived from the MapBiomas project, a Brazilian multi-institutional project to map land use and land cover (LULC) classes of an entire country based on historical time series of Landsat data. In addition to the existing forest maps, a set of 1619 Landsat 8 RGB color composites was used to generate new independent comparison data composed of circular areas with 5-km diameter, which were visually interpreted after image segmentation. The Spearman rank correlation estimated the correlation among the data sets and the paired Mann–Whitney–Wilcoxon tested the hypothesis that the data sets are statistically equal. Results showed that forest maps derived from SAR and optical satellites are statistically different regardless of biome or scale of study (municipality or image sampling), except for the Cerrado´s forest estimations derived from TanDEM-X and ALOS-2. Nevertheless, the percentage of pixels classified as forest or non-forest by both SAR sensors were 90% and 80% for the Amazon and Cerrado biome, respectively, indicating an overall good agreement.

Item URL in elib:https://elib.dlr.de/141555/
Document Type:Article
Title:Comparative Analysis of the Global Forest/Non-Forest Maps Derived from SAR and Optical Sensors. Case Studies from Brazilian Amazon and Cerrado Biomes
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Sano, EdsonBrazilian Institute of Environment and Renewable Natural Resources—IBAMAUNSPECIFIEDUNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Koyama, ChristianSchool of Science and Engineering Ishizaka, Tokyo Denki UniversityUNSPECIFIEDUNSPECIFIED
Watanabe, ManabuSchool of Science and Engineering Ishizaka, Tokyo Denki UniversityUNSPECIFIEDUNSPECIFIED
Adami, MarcosCentro Regional da Amazônia, National Institute for Space Research—INPEUNSPECIFIEDUNSPECIFIED
Shimabukuro, Yosio E.National Institute for Space Research—INPEUNSPECIFIEDUNSPECIFIED
Bayma, GustavoBrazilian Agricultural Research Corporation—Embrapa Meio AmbienteUNSPECIFIEDUNSPECIFIED
Freitas, Daniel M.Brazilian Institute of Environment and Renewable Natural Resources—IBAMAUNSPECIFIEDUNSPECIFIED
Date:21 January 2021
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.3390/rs13030367
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:Forest Mapping, SAR, TanDEM-X, Alos Palsar, Amazonas
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Projekt TanDEM-X (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Rizzoli, Paola
Deposited On:26 Mar 2021 16:25
Last Modified:05 Dec 2023 09:32

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