Mapping deforestation and land use in amazon rainforest by using SIR-C imagery

Saatchi, S. S.; Soares, João Vianei; Alves, Diógenes Salas

doi:10.1016/s0034-4257(96)00153-8

Cited by 108 publications

(77 citation statements)

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“…Those areas of primary forest present σ 0 hh = -7.51 dB± 3.34, σ 0 hv = -12.25dB ±3.15 and σ 0 vv = -7.53dB ± 3.24; secondary succession areas, which represent intermediate and advanced phases (characterized by the old regeneration age and also by the vertical structure) present σ 0 hh = -7.38 dB± 2.34, σ 0 hv = -11.95dB ± 2.27 and σ 0 vv = -7.06dB ± 2.29. The values found in this study are coherent with those obtained by Hoekman and Quiñones (2000), SAATCHI et al (1997), SANTOS et al (2002), whose variability can be attributed to general differences in the horizontal and vertical structure of the strata from the forest typologies. This also shows that the sensor SAR-R99B presents an adequate radiometric response.…”

Section: Methodssupporting

confidence: 90%

“…There are several interaction mechanisms of the radar signal with forest targets, such as: multiple backscatter within the canopy (volumetric scattering), direct scattering from the tree trunks, scattering from the interaction canopy-soil, scattering from the interaction trunk-soil (double bounce), whose intensities depend on the SAR wavelengths, on the polarization, on the angle of incidence and on the terrain parameters. (CLOUDE and POTTIER, 1997;FREEMAN and DURDEN, 1998) According several studies (SAATCHI et al, 1997;HOEKMAN and QUINÕNES, 2000;SANTOS et al, 2002), SAR data are also used to model forest volume and biomass estimation, using the polarimetric backscatter attributes. Depending on the frequency of the sensor, there is a saturation of radar signal for those areas with high biomass concentration.…”

Section: Introductionmentioning

confidence: 99%

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Análise dos parâmetros estruturais de tipologias florestais utilizando dados SAR em banda L

2010

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The main objective of this work is the investigation of the relationship between the polarimetric L-band backscatter (σº) from different incidence angles (collected by the airborne sensor R99-B/SIPAM) and the structural parameters of the primary and secondary forest typologies. The area under study is located at the Tapajós National Forest and surroundings (Pará State, Brazil). Using the Freeman-Durden target decomposition technique, the basic backscatter mechanisms are presented to verify the contributions of the physiognomic-structural components of these forest stands in the L-band signal responses. As a conclusion, it is possible to verify that the variable "tree height" has better relations with the backscatter values, when compared to other structural variables, especially when the model also includes variations of the incidence angle of the stripes imaged. The Freeman-Durden decomposition technique indicates that the volumetric scattering component has the strongest influence on the L-band at primary and secondary tropical forests at incidence angles between 52 and 70 degrees, mainly due to the high incidence angle and, consequently the low depth vertical penetration. Keywords: Forest Inventory; L-Band; SAR Data; Mapping; Tropical Forest; Amazon.Bol. Ciênc. Geod., sec. Artigos, Curitiba, v. 16, n o 3, p.475-489, jul-set, 2010.Analysis of structural parameters of forest typologies using ... 4 7 6 RESUMO O objetivo principal desse trabalho é investigar a relação entre o retroespalhamento (σ°) de dados SAR polarimétricos de banda L, em diferentes ângulos de incidência (coletado pelo sensor aerotransportado R99-B/SIPAM) e os parâmetros estruturais de sítios de floresta primária e sucessão secundária. A área selecionada para esse estudo está localizada na região da Floresta Nacional do Tapajós (Estado do Pará, Brasil) e áreas circunvizinhas. É utilizada a técnica de decomposição de alvos de Freeman-Durden na avaliação dos mecanismos básicos de espalhamento, para verificar a contribuições das componentes fisionômico-estruturais dos alvos florestais na resposta-radar de banda L. Como conclusão, é possível verificar que a variável "altura das árvores" teve melhor relação com os valores de retroespalhamento, quando comparado com outras variáveis biofísicas, especialmente quando o modelo também incluiu variações do ângulo de incidência na direção em range. A técnica de decomposição de Freeman-Durden indicou que a componente volumétrica de espalhamento tem uma forte influência na resposta em banda L para florestas tropicais primárias e secundárias,em ângulos de incidência entre 52 e 70 graus, devido principalmente ao elevado ângulo de incidência e, consequentemente a baixa profundidade de penetração vertical da onda incidente.

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Section: Methodssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Análise dos parâmetros estruturais de tipologias florestais utilizando dados SAR em banda L

2010

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“…In addition to measuring one-time biomass densities, pol-SAR also provides the 589 capability of monitoring biomass changes resulting from clear-cutting, forest fires, insect 590 disturbance, wind damage, and to some extent more subtle changes in forest structure 591 (Saatchi et al 1997;Rignot et al 1994;Couturier et al 2001;Siegert et al 2001;Salas et 592 al. 2002;Ranson et al 2003).…”

mentioning

confidence: 99%

Characterizing 3D vegetation structure from space: Mission requirements

Hall¹,

Bergen²,

Blair³

et al. 2011

Remote Sensing of Environment

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18Human and natural forces are rapidly modifying the global distribution and 19 structure of terrestrial ecosystems on which all of life depends, altering the global carbon 20 cycle, affecting our climate now and for the foreseeable future, causing steep reductions 21 in species diversity, and endangering Earth's sustainability. 22To understand changes and trends in terrestrial ecosystems and their functioning 23 as carbon sources and sinks, and to characterize the impact of their changes on climate, 24 habitat and biodiversity, new space assets are urgently needed to produce high spatial 25 resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass 26 above ground, the carbon stored within and the implications for atmospheric green house 27 gas concentrations and climate. These needs were articulated in a 2007 National 28Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, 29DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a 30 multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives 31 of this paper are to articulate the importance of these new, multi-year, 3D vegetation 32 structure and biomass measurements, to briefly review the feasibility of radar and lidar 33 remote sensing technology to meet these requirements, to define the data products and 34 measurement requirements, and to consider implications of mission durations. The paper 35 addresses these objectives by synthesizing research results and other input from a broad 36 community of terrestrial ecology, carbon cycle, and remote sensing scientists and 37 working groups. We conclude that: 38(1) current global biomass and 3-D vegetation structure information is unsuitable 39 for both science and management and policy. The only existing global datasets of 40 biomass are approximations based on combining land cover type and representative 41 carbon values, instead of measurements of actual biomass. Current measurement attempts 42 based on radar and multispectral data have low explanatory power outside low biomass 43areas. There is no current capability for repeatable disturbance and regrowth estimates. 44(2) The science and policy needs for information on vegetation 3D structure can 45 be successfully addressed by a mission capable of producing (i) a first global inventory of 46 forest biomass with a spatial resolution 1km or finer and unprecedented accuracy (ii) 47 annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass 48 accumulation rates at resolutions of 1km or finer, and (iii) transects of vertical and 49 horizontal forest structure with 30 m along-transect measurements globally at 25 m 50 spatial resolution, essential for habitat characterization. 51 We also show from the literature that lidar profile samples together with wall-to-52 wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together 53 to satisfy these vegetation 3D structure and biomass measurement requirements. ...

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“…A sobreposição entre as densidades das classes é quase total nas polarizações HH e VV e um pouco menor na polarização HV. A melhor separação das classes em HV se deve ao contraste criado pela sensibilidade da polarização cruzada ao espalhamento volumétrico, produzido no interior das copas das árvores, e pela baixa resposta de solos expostos ou cobertos por vegetação baixa (Saatchi et al, 1997). A grande sobreposição entre as densidades indica que pode ser A Tabela 2 apresenta os valores de índice kappa de cada uma das classificações realizadas.…”

Section: Resultsunclassified

Discriminação de incrementos de desflorestamento na Amazônia com dados SAR R99B em banda L

2010

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RESUMOO uso de dados de sensoriamento remoto óptico em projetos de monitoramento de extensas áreas de floresta tropical é limitado devido à intensa cobertura por nuvens. Os dados SAR (Synthetic Aperture Radar) podem ser uma alternativa interessante para detectar desflorestamento nas regiões de floresta tropical onde a cobertura por nuvens é permanente. Neste contexto, o objetivo deste trabalho é avaliar o potencial do dado SAR adquirido em banda L pelo sistema aerotransportado R99B da Força Aérea Brasileira (FAB) para discriminar incremento de desflorestamento na Amazônia. Para tanto, foram realizadas classificações MAXVER-ICM com dados SAR multipolarizados de uma área teste localizada na região Sudeste do Estado do Acre. As classificações realizadas com a combinação dos canais HH, HV e VV e com o par de polarizações HH+HV obtiveram boa concordância com o mapa produzido no projeto PRODES (k = 0,68, onde k é o índice Kappa), o qual foi adotado como dado de referência. Este resultado indica que o dado SAR multipolarizado em banda L possui bom potencial para discriminar incremento de desflorestamento na Amazônia.PALAVRAS-CHAVE: SAR R99B, banda L, multipolarização, desflorestamento. SAR R99B, L band, multipolarization, desforestation. Discriminating deforestation increment areas in the Amazon rainforest with L band SAR R99B data ABSTRACTThe use of optical remote sensing data in large tropical forest regions has an important limitation due to cloud cover. Synthetic Aperture Radar (SAR) data can be a viable alternative in areas where cloud cover is permanent, because the data acquisition is independent on atmospheric conditions. In this context, the main objective of this work was to evaluate the potential of L band SAR data acquired by R99B Brazilian Air Force (FAB) airborne system to discriminate deforestation increments in the Amazon rainforest. In order to achieve this purpose, we performed Maximum Likelihood classifications with multipolarized SAR data of a test site located in the state of Acre. The classifications performed with the combination of three channels (HH+HV+VV) and with the polarization pair HH+HV obtained good agreement with PRODES reference map (k=0,68, where k is de Kappa index). This result indicates that multipolarized L band SAR data have good potential to discriminate deforestation increments in the Amazon rainforest.

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Mapping deforestation and land use in amazon rainforest by using SIR-C imagery

Cited by 108 publications

References 16 publications

Análise dos parâmetros estruturais de tipologias florestais utilizando dados SAR em banda L

Análise dos parâmetros estruturais de tipologias florestais utilizando dados SAR em banda L

Characterizing 3D vegetation structure from space: Mission requirements

Discriminação de incrementos de desflorestamento na Amazônia com dados SAR R99B em banda L

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