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Featured researches published by Izaya Numata.


Remote Sensing | 2013

Ten-Year Landsat Classification of Deforestation and Forest Degradation in the Brazilian Amazon

Carlos Souza; João Victor Siqueira; Marcio H. Sales; Antônio V. Fonseca; Júlia G. Ribeiro; Izaya Numata; Mark A. Cochrane; Christopher P. Barber; Jos Barlow

Forest degradation in the Brazilian Amazon due to selective logging and forest fires may greatly increase the human footprint beyond outright deforestation. We demonstrate a method to quantify annual deforestation and degradation simultaneously across the entire region for the years 2000–2010 using high-resolution Landsat satellite imagery. Combining spectral mixture analysis, normalized difference fraction index, and knowledge-based decision tree classification, we mapped and assessed the accuracy to quantify forest (0.97), deforestation (0.85) and forest degradation (0.82) with an overall accuracy of 0.92. We show that 169,074 km2 of Amazonian forest was converted to human-dominated land uses, such as agriculture, from 2000 to 2010. In that same time frame, an additional 50,815 km2 of forest was directly altered by timber harvesting and/or fire, equivalent to 30% of the area converted by deforestation. While average annual outright deforestation declined by 46% between the first and second halves of the study period, annual forest degradation increased by 20%. Existing operational monitoring systems (PRODES: Monitoramento da Florestal Amazonica Brasileira por Satelite) report deforestation area to within 2% of our results, but do not account for the extensive forest degradation occurring throughout the region due to selective logging and forest fire. Annual monitoring of forest degradation across tropical forests is critical for developing land management policies as well as the monitoring of carbon stocks/emissions and protected areas.


Environmental Research Letters | 2011

Carbon emissions from deforestation and forest fragmentation in the Brazilian Amazon

Izaya Numata; Mark A. Cochrane; Carlos Souza; Marcio H. Sales

Forest-fragmentation-related edge effects are one of the major causes of forest degradation in Amazonia and their spatio-temporal dynamics are highly influenced by annual deforestation patterns. Rapid biomass collapse due to edge effects in forest fragments has been reported in the Brazilian Amazon; however the collective impacts of this process on Amazonian carbon fluxes are poorly understood. We estimated biomass loss and carbon emissions from deforestation and forest fragmentation related to edge effects on the basis of the INPE (Brazilian National Space Research Institute) PRODES deforestation data and forest biomass volume data. The areas and ages of edge forests were calculated annually and the corresponding biomass loss and carbon emissions from these forest edges were estimated using published rates of biomass decay and decomposition corresponding to the areas and ages of edge forests. Our analysis estimated carbon fluxes from deforestation (4195 Tg C) and edge forest (126–221 Tg C) for 2001–10 in the Brazilian Amazon. The impacts of varying rates of deforestation on regional forest fragmentation and carbon fluxes were also investigated, with the focus on two periods: 2001–5 (high deforestation rates) and 2006–10 (low deforestation rates). Edge-released carbon accounted for 2.6–4.5% of deforestation-related carbon emissions. However, the relative importance of carbon emissions from forest fragmentation increased from 1.7–3.0% to 3.3–5.6% of the respective deforestation emissions between the two contrasting deforestation rates. Edge-related carbon fluxes are of increasing importance for basin-wide carbon accounting, especially as regards ongoing reducing emissions from deforestation and forest degradation (REDD) efforts in Brazilian Amazonia.


PLOS ONE | 2012

Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

Jos Barlow; Juliana M. Silveira; Luiz Augusto Macedo Mestre; Rafael B. Andrade; Gabriela Camacho D'Andrea; Julio Louzada; Fernando Z. Vaz-de-Mello; Izaya Numata; Sébastien Lacau; Mark A. Cochrane

Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR) calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001) community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions.


Earth Interactions | 2011

Analyzing the Impacts of Frequency and Severity of Forest Fire on the Recovery of Disturbed Forest using Landsat Time Series and EO-1 Hyperion in the Southern Brazilian Amazon

Izaya Numata; Mark A. Cochrane; Lênio Soares Galvão

AbstractEstimation of fire impacts and forest recovery using remote sensing is difficult because of the heterogeneity of fire history (frequency, severity, and time since last fire) across burned forest landscapes. The authors analyzed impacts of fire frequency and severity within recovering forests in the Amazon region using remote sensing. A multispectral Landsat time series dataset was used to reconstruct the fire history from 1990 to 2002 in a portion of Mato Grosso, Brazil. Five narrowband vegetation indices were then calculated from a hyperspectral Earth Observing One (EO-1) Hyperion image for spectral analysis of physiological characteristics of fire-disturbed forests and their recovery. A total of 30% of the forests burned during the study period, with 72% burned once, 24% burned twice, and less than 4% burned three times. In terms of severity, 70% of burned forest was lightly burned, 21.1% was moderately burned, and 9.1% was severely burned. Analyses of spectral indices [normalized difference veg...


Earth Interactions | 2007

Regional Characterization of Pasture Changes through Time and Space in Rondônia, Brazil

Izaya Numata

Abstract Although pasture degradation has been a regional concern in Amazonian ecosystems, our ability to characterize and monitor pasture degradation under different environmental and human-related conditions is still limited. Regional analysis of pasture dynamic patterns was conducted using high-frequency temporal satellite data and ancillary data to better understand pasture degradation under varied soil, environmental, and pasture management conditions in the state of Rondonia, Brazil. The 10-day normalized difference vegetation index (NDVI) composite derived from Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m resolution was used to characterize different grass phenological patterns for 32 counties in Rondonia between 2001 and 2003. Six pasture greenness classes showed that high greenness pasture classes dominated in young pastures, while low greenness pasture classes were least common. As pastures aged, the proportion of high greenness pasture classes decreased and the proportion of low ...


Remote Sensing | 2017

Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests

Izaya Numata; Kul Khand; Jeppe Kjaersgaard; Mark A. Cochrane; Sonaira Souza da Silva

While forest evapotranspiration (ET) dynamics in the Amazon have been studied both as point estimates using flux towers, as well as spatially coarse surfaces using satellite data, higher resolution (e.g., 30 m resolution) ET estimates are necessary to address finer spatial variability associated with forest biophysical characteristics and their changes by natural and human impacts. The objective of this study is to evaluate the potential of the Landsat-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model to estimate high-resolution (30 m) forest ET by comparing to flux tower ET (FT ET) data collected over seasonally dry tropical forests in Rondonia, the southwestern region of the Amazon. Analyses were conducted at daily, monthly and seasonal scales for the dry seasons (June–September for Rondonia) of 2000–2002. Overall daily ET comparison between FT ET and METRIC ET across the study site showed r2 = 0.67 with RMSE = 0.81 mm. For seasonal ET comparison, METRIC-derived ET estimates showed an agreement with FT ET measurements during the dry season of r2 >0.70 and %MAE <15%. We also discuss some challenges and potential applications of METRIC for Amazonian forests.


Remote Sensing | 2017

Dry Season Evapotranspiration Dynamics over Human-Impacted Landscapes in the Southern Amazon Using the Landsat-Based METRIC Model

Kul Khand; Izaya Numata; Jeppe Kjaersgaard; George L. Vourlitis

Although seasonal and temporal variations in evapotranspiration (ET) in Amazonia have been studied based upon flux-tower data and coarse resolution satellite-based models, ET dynamics over human-impacted landscapes are highly uncertain in this region. In this study, we estimate ET rates from critical land cover types over highly fragmented landscapes in the southern Amazon and characterize the ET dynamics during the dry season using the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC, a Landsat-based ET model, that generates spatially continuous ET estimates at a 30 m spatial resolution widely used for agricultural applications, was adapted to the southern Amazon by using the NDVI indexed reference ET fraction (ETrF) approach. Compared to flux tower-based ET rates, this approach showed an improved performance on the forest ET estimation over the standard METRIC approach, with R2 = 0.73 from R2 = 0.70 and RMSE reduced from 0.77 mm/day to 0.35 mm/day. We used this approach integrated into the METRIC procedure to estimate ET rates from primary, regenerated, and degraded forests and pasture in Acre, Rondonia, and Mato Grosso, all located in the southern Amazon, during the dry season in 2009. The lowest ET rates occurred in Mato Grosso, the driest region. Acre and Rondonia, both located in the southwestern Amazon, had similar ET rates for all land cover types. Dry season ET rates between primary forest and regenerated forest were similar (p > 0.05) in all sites, ranging between 2.5 and 3.4 mm/day for both forest cover types in the three sites. ET rates from degraded forest in Mato Grosso were significantly lower (p < 0.05) compared to the other forest cover types, with a value of 2.03 mm/day on average. Pasture showed the lowest ET rates during the dry season at all study sites, with the dry season average ET varying from 1.7 mm/day in Mato Grosso to 2.8 mm/day in Acre.


Remote Sensing of Environment | 2004

Sources of error in accuracy assessment of thematic land-cover maps in the Brazilian Amazon

Rebecca Powell; Nicholas J. Matzke; C de Souza; Matthew L. Clark; Izaya Numata; Laura L. Hess


Journal of Geophysical Research | 2002

Large area mapping of land-cover change in Rondônia using multitemporal spectral mixture analysis and decision tree classifiers

Izaya Numata; Karen W. Holmes; G. Batista; T. Krug; A. Monteiro; B. Powell; Oliver A. Chadwick


Remote Sensing of Environment | 2007

Characterization of pasture biophysical properties and the impact of grazing intensity using remotely sensed data

Izaya Numata; Oliver A. Chadwick; Josh Schimel; Fernando R. Sampaio; Francisco das Chagas Leônidas; João Vianei Soares

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João Vianei Soares

National Institute for Space Research

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Jeppe Kjaersgaard

South Dakota State University

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Francisco das Chagas Leônidas

Empresa Brasileira de Pesquisa Agropecuária

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Marcio H. Sales

Wageningen University and Research Centre

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