Mapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry

Autor: Heiko Balzter, Matteo Pardini, Kevin Tansey, Igor Rizaev, Polyanna da Conceição Bispo, Luciana Spinelli Araujo, Konstantinos Papathanassiou, Dominik Rains, Florian Kugler, Maiza Nara dos Santos, João Roberto dos Santos
Přispěvatelé: POLYANNA DA CONCEICAO BISPO, University of Leicester, MATTEO PARDINI, German Aerospace Center, KONSTANTINUS P PAPATHANASSIOU, German Aerospace Center, FLORIAN KUGLER, German Aerospace Center, HEIKO BALTZER, Ghent University, DOMINIK RAINS, University of Leicester, JOAO ROBERTO DOS SANTOS, INPE, IGOR G RIZAEV, University of Bristol, KEVIN TANSEY, University of Leicester, MAIZA FERREIRA DA SILVA, SGE, LUCIANA SPINELLI DE ARAUJO, CNPMA.
Jazyk: angličtina
Rok vydání: 2019
Předmět:
010504 meteorology & atmospheric sciences
Tropical forests
0208 environmental biotechnology
Soil Science
Context (language use)
02 engineering and technology
01 natural sciences
Synthetic Aperture Radar
BAND
CLASSIFICATION
POLINSAR
TanDEM-X
Floresta Tropical
Interferometric synthetic aperture radar
Tropical vegetation
POL-INSAR
Mapa
INVERSION
Computers in Earth Sciences
Digital elevation model
SECONDARY FORESTS
0105 earth and related environmental sciences
Remote sensing
geography
geography.geographical_feature_category
Radar
Height
Synthetic Aperture
Geology
synthetic aperture radar
15. Life on land
Old-growth forest
020801 environmental engineering
Forest height
Lidar
Forest succession
Interferometry
Successional stages
Earth and Environmental Sciences
Spatial ecology
Environmental science
Secondary forest
TROPICAL-FOREST
INTEGRATION
ABOVEGROUND BIOMASS
PARAMETER-ESTIMATION
Sensoriamento Remoto
Zdroj: Bispo, P D C, Pardini, M, Papathanassiou, K P, Kugler, F, Balzter, H, Rains, D, Dos Santos, J R, Rizaev, I G, Tansey, K, Dos Santos, M N & Spinelli Araujo, L 2019, ' Mapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry ', Remote Sensing of Environment, vol. 232, pp. 111194 . https://doi.org/10.1016/j.rse.2019.05.013
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
Bispo, P D C, Pardini, M, Papathanassiou, K P, Kugler, F, Balzter, H, Rains, D, dos Santos, J R, Rizaev, I G, Tansey, K, dos Santos, M N & Spinelli Araujo, L 2019, ' Mapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry ', Remote Sensing of Environment, vol. 232, 111194 . https://doi.org/10.1016/j.rse.2019.05.013
REMOTE SENSING OF ENVIRONMENT
ISSN: 0034-4257
1879-0704
DOI: 10.1016/j.rse.2019.05.013
Popis: Knowledge of the spatial patterns of successional stages (i.e., primary and secondary forest) in tropical forests allows to monitor forest preservation, mortality and regeneration in relation to natural and anthropogenic disturbances. Different successional stages have also different capabilities of re-establishing carbon stocks. Therefore, a successful discrimination of successional stages over wide areas can lead to an improved quantification of above ground biomass and carbon stocks. The reduction of the mapping uncertainties is especially a challenge due to high heterogeneity of the tropical vegetation. In this framework, the development of innovative remote sensing approaches is required. Forests (top) height (and its spatial distribution) are an important structural parameter that can be used to differentiate between different successional stages, and can be provided by Interferometric Synthetic Aperture Radar (InSAR) acquisitions. In this context, this paper investigates the potential of forest heights estimated from TanDEM-X InSAR data and a LiDAR digital terrain model (DTM) for separating successional stages (primary or old growth and secondary forest at different stages of succession) by means of a maximum likelihood classification. The study was carried out in the region of the Tapajós National Forest (Pará, Brazil) in the Amazon biome. The forest heights for three years (2012, 2013 and 2016) were estimated from a single-polarization in bistatic mode using InSAR model-based inversion techniques aided by the LiDAR digital terrain model. The validation of the TanDEM-X forest heights with independent LiDAR H100 datasets was carried out in the location of seven field inventory plots (measuring 50?×?50?m, equivalent to 0.25?ha), also allowing for the validation of the LiDAR datasets against the field data. The validation of the estimated heights showed a high correlation (r?=?0.93) and a low uncertainty (RMSE?=?3?m). The information about the successional stages and forest heights from field datasets was used to select training samples in the LiDAR and TanDEM-X forest heights to classify successional stages with a maximum likelihood classifier. The identification of different stages of forest succession based on TanDEM-X forest heights was possible with an overall accuracy of about 80%. Made available in DSpace on 2019-11-27T18:14:02Z (GMT). No. of bitstreams: 1 ARAUJOSPINELLIMappingForest2019.pdf: 3208805 bytes, checksum: 7902ab1e9e1d3da159d912e43abb2a28 (MD5) Previous issue date: 2019
Databáze: OpenAIRE
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