A Multi-Resolution Multi-Temporal Technique for Detecting and Mapping Deforestation in the Brazilian Amazon Rainforest

Arai, Egídio; Shimabukuro, Yosio Edemir; Pereira, Gabriel; Vijaykumar, Nandamudi Lankalapalli

doi:10.3390/rs3091943

Cited by 30 publications

(23 citation statements)

References 40 publications

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“…The segmentation tool is a procedure commonly utilized to separate the targets of the images, facilitating automatic or non-automatic classifications. Several studies have used this procedure, such as [37], which presented a semi-automatic procedure utilizing segmentation for burned area extraction in VEGETATION/SPOT and AVHRR/NOAA imagery; [38], which applied LSMM, segmentation and unsupervised classification to AVHRR/NOAA and TM/Landsat data to map burned forest areas in the Mediterranean, and [39], which used LSMM and segmentation in Landsat images to map deforested areas in the Amazon rainforest.…”

Section: Burned Area Mapping In Tm and Etm+ Images And Field Datamentioning

confidence: 99%

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

et al. 2014

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Abstract:The objective of this study was to analyze the spatial and temporal distribution of burned areas in Rondônia State, Brazil during the years 2000 to 2011 and evaluate the burned area maps. A Linear Spectral Mixture Model (LSMM) was applied to MODIS surface reflectance images to originate the burned areas maps, which were validated with TM/Landsat 5 and ETM+/Landsat 7 images and field data acquired in August 2013. The validation presented a correlation ranging from 67% to 96% with an average value of 86%. The lower correlation values are related to the distinct spatial resolutions of the MODIS and TM/ETM+ sensors because small burn scars are not detected in MODIS images and higher spatial correlations are related to the presence of large fires, which are better identified in MODIS, increasing the accuracy of the mapping methodology. In addition, the 12-year burned area maps of Rondônia indicate that fires, as a general pattern, occur in areas that have already been converted to some land use, such as vegetal extraction, large animal livestock areas or diversified permanent crops. Furthermore, during the analyzed period, land use conversion associated with climatic events significantly influenced the occurrence of fire in Rondônia and amplified its impacts.

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Section: Burned Area Mapping In Tm and Etm+ Images And Field Datamentioning

confidence: 99%

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

et al. 2014

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“…Technical capabilities and statistical tools have advanced since the early 1990s [14] and operational forest monitoring systems at the national level are now a feasible goal for most developing countries in the tropics [15,16]. For our survey we used a systematic sampling grid with sample units (20 …”

Section: Introductionmentioning

confidence: 99%

Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals

et al. 2012

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This paper outlines the methods and results for monitoring forest change and resulting carbon emissions for the 1990-2000 and 200-2005 periods carried out over tropical Central and South America. To produce our forest change estimates we used a systematic sample of medium resolution satellite data processed to forest change maps covering 1230 sites of 20 km by 20 km, each located at the degree confluence. Biomass data were spatially associated to each individual sample site so that annual carbon emissions could be estimated. For our study area we estimate that forest cover in the study area had fallen from 763 Mha (s.e.

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“…Generation of such long-term observation records by merging multiple sensor data requires a considerable amount of scientific investigations on data continuity and compatibility due to differences in both hardware and software configurations, e.g., sensor/platform characteristics and processing algorithms [3][4][5][6][7][8][9]. Systematic differences in VI products among sensors [10] are one such problem to be resolved.…”

Section: Introductionmentioning

confidence: 99%

Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines

2012

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An analytical form of relationship between spectral vegetation indices (VI) is derived in the context of cross calibration and translation of vegetation index products from different sensors. The derivation has been carried out based on vegetation isoline equations that relate two reflectance values observed at different wavelength ranges often represented by spectral band passes. The derivation was first introduced and explained conceptually by assuming a general functional form for VI model equation. This process is universal by which two VIs of different sensors and/or different model equations can be related conceptually. The general process was then applied to the actual case of normalized difference vegetation index (NDVI) from two sensors in a framework of inter-sensor continuity. The derivation results indicate that the NDVI from one sensor can be approximated by a rational function of NDVI from the other sensor as a parameter. Similar result was obtained for the case of soil adjusted VI, enhanced VI, and two-band variance of enhanced VI.

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A Multi-Resolution Multi-Temporal Technique for Detecting and Mapping Deforestation in the Brazilian Amazon Rainforest

Cited by 30 publications

References 40 publications

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals

Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines

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