Pratihast A.K.,Wageningen University |
Pratihast A.K.,Cologne University of Applied Sciences |
Herold M.,Wageningen University |
Avitabile V.,Wageningen University |
And 4 more authors.
Sensors (Switzerland) | Year: 2013
Monitoring tropical deforestation and forest degradation is one of the central elements for the Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD+) scheme. Current arrangements for monitoring are based on remote sensing and field measurements. Since monitoring is the periodic process of assessing forest stands properties with respect to reference data, adopting the current REDD+ requirements for implementing monitoring at national levels is a challenging task. Recently, the advancement in Information and Communications Technologies (ICT) and mobile devices has enabled local communities to monitor their forest in a basic resource setting such as no or slow internet connection link, limited power supply, etc. Despite the potential, the use of mobile device system for community based monitoring (CBM) is still exceptional and faces implementation challenges. This paper presents an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. This paper also assesses the accuracy and reliability of CBM data and proposes a way to fit them into national REDD+ Monitoring, Reporting and Verification (MRV) scheme. The system performance is evaluated at Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were tracked. The results show that the local community is able to provide data with accuracy comparable to expert measurements (index of agreement greater than 0.88), but against lower costs. Furthermore, the results confirm that communities are more effective to monitor small scale forest degradation due to subsistence fuel wood collection and selective logging, than high resolution remote sensing SPOT imagery. © 2013 by the authors; licensee MDPI, Basel, Switzerland.
Walker R.,Michigan State University |
Walker R.,Federal University of Pará |
Arima E.,University of Texas at Austin |
Messina J.,Michigan State University |
And 5 more authors.
Ecological Applications | Year: 2013
This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras devolutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more fragmentation than necessary to access fixed quantities of wood. The paper concludes by considering implications of the approach and findings for Brazil's move to a system of concession logging. © 2013 by the Ecological Society of America.
Bernard E.,Federal University of Pernambuco |
Penna L.A.O.,Federal University of Pernambuco |
Araujo E.,Instituto do Homem e Meio Ambiente da Amazonia IMAZON
Conservation Biology | Year: 2014
Protected areas (PAs) are key elements for biodiversity conservation and ecosystem services. Brazil has the largest PA system in the world, covering approximately 220 million ha. This system expanded rapidly in the mid-1990s to the mid-2000s. Recent events in Brazil, however, have led to an increase in PA downgrading, downsizing, and degazettement (PADDD). Does this reflect a shift in the country's PA policy? We analyzed the occurrence, frequency, magnitude, type, spatial distribution, and causes of changes in PA boundaries and categories in Brazil. We identified 93 PADDD events from 1981 to 2012. Such events increased in frequency since 2008 and were ascribed primarily to generation and transmission of electricity in Amazonia. In Brazilian parks and reserves, 7.3 million ha were affected by PADDD events, and of these, 5.2 million ha were affected by downsizing or degazetting. Moreover, projects being considered by the Federal Congress may degazette 2.1 million ha of PA in Amazonia alone. Relaxing the protection status of existing PAs is proving to be politically easy in Brazil, and the recent increase in frequency and extension of PADDD reflects a change in governmental policy. By taking advantage of chronic deficiencies in financial and personnel resources and surveillance, disputes over land tenure, and the slowness of the Brazilian justice, government agencies have been implementing PADDD without consultation of civil society. If parks and reserves are to maintain their integrity, there will need to be investments in Brazilian PAs and a better understanding of the benefits PAs provide. © 2014 Society for Conservation Biology.
Grogan J.,Yale University |
Grogan J.,Instituto do Homem e Meio Ambiente da Amazonia IMAZON |
Schulze M.,Oregon State University |
Schulze M.,Instituto Floresta Tropical IFT |
And 2 more authors.
New Forests | Year: 2010
Big-leaf mahogany (Swietenia macrophylla) trees are often retained in agricultural fields and pastures for seed and timber production after selective logging and forest clearing in the Brazilian Amazon. At a forest management site in southeast Pará, we censused trees growing scattered across a large open clearing after forest removal and in heavily disturbed forest after selective logging and canopy thinning for survival, stem diameter growth, fruit production, and date of dry season flowering initiation annually during 1997-2003. Trees in the open clearing died at faster rates, grew more slowly, produced fewer fruit, and initiated flowering earlier, on average, than trees in logged and thinned forest during this period. The principal cause of mortality and stem damage in both environments was dry season groundfires. Mahogany trees in logged and thinned forest at the study site grew faster than mahogany trees at a selectively logged but otherwise undisturbed closed-canopy forest site in this region during the same period. This was likely due to vine elimination by groundfires, increased crown exposure after canopy thinning, and soil nutrient inputs due to groundfires. Without effective regulation and control of anthropogenic fires, attempts to manage remnant mahogany trees for future timber yields or to restore commercially viable populations in this region may prove futile. © 2010 Springer Science+Business Media B.V.
West T.A.P.,University of Florida |
West T.A.P.,University of Sao Paulo |
Vidal E.,University of Sao Paulo |
Vidal E.,Instituto do Homem e Meio Ambiente da Amazonia IMAZON |
And 2 more authors.
Forest Ecology and Management | Year: 2014
Growing concerns about unnecessarily destructive selective logging of tropical forests and its impacts on greenhouse gas (GHG) emissions motivated this study on post-logging biomass dynamics over a 16-year period in a control plot and in plots subjected to conventional logging (CL) or reduced-impact logging (RIL) in Paragominas, Pará State, Brazil. All trees >25cm were monitored in 25.4ha plots of each treatment, each with a subplot of 5.25ha for trees >10cmdbh. The commercial timber volumes in felled trees were 38.9 and 37.4m3ha-1 in the RIL and CL plots, respectively, but the extracted volumes were 38.6 and 29.7 m3 ha-1, respectively. Immediately after logging, plots subjected to RIL and CL lost 17% and 26% of their above-ground biomass, respectively. Over the 16years after logging, the average annual increments in above-ground biomass (recruitment plus residual tree growth minus mortality) were 2.8Mgha-1 year-1 in the RIL plot but only 0.5Mgha-1year-1 in the CL plot. By 16years post-logging, the RIL plot recovered 100% of its original above-ground biomass while the CL plot recovered only 77%; over the same period, biomass in the control plot maintained 96% of its initial stock. These findings reinforce the claim that conversion from CL to RIL would represent an efficient forest-based strategy to mitigate climate change under the REDD+ and would be an important step towards sustainable forest management. © 2013 Elsevier B.V.
Macpherson A.J.,University of Florida |
Macpherson A.J.,São Paulo State University |
Schulze M.D.,Instituto do Homem e Meio Ambiente da Amazonia IMAZON |
Carter D.R.,University of Florida |
And 2 more authors.
Forest Ecology and Management | Year: 2010
Using data from a logging experiment in the eastern Brazilian Amazon region, we develop a matrix growth and yield model that captures the dynamic effects of harvest system choice on forest structure and composition. Multinomial logistic regression is used to estimate the growth transition parameters for a 10-year time step, while a Poisson regression model is used to estimate recruitment parameters. The model is designed to be easily integrated with an economic model of decisionmaking to perform tropical forest policy analysis. The model is used to compare the long-run structure and composition of a stand arising from the choice of implementing either conventional logging techniques or more carefully planned and executed reduced-impact logging (RIL) techniques, contrasted against a baseline projection of an unlogged forest. Results from "log and leave" scenarios show that a stand logged according to Brazilian management requirements will require well over 120 years to recover its initial commercial volume, regardless of logging technique employed. Implementing RIL, however, accelerates this recovery. Scenarios imposing a 40-year cutting cycle raise the possibility of sustainable harvest volumes, although at significantly lower levels than is implied by current regulations. Meeting current Brazilian forest policy goals may require an increase in the planned total area of permanent production forest or the widespread adoption of silvicultural practices that increase stand recovery and volume accumulation rates after RIL harvests. © 2010.
Morton D.C.,University of Maryland University College |
DeFries R.S.,Columbia University |
DeFries R.S.,Lamont Doherty Earth Observatory |
Nagol J.,University of Maryland University College |
And 4 more authors.
Remote Sensing of Environment | Year: 2011
Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars <50ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500ha) and large (>500ha) burn scars that accounted for the majority of all fire-damaged forests in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508km2) were an order of magnitude higher than during the 1997-1998 El Niño event (124km2 and 39km2, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series. © 2011.
Ribeiro Sales M.H.,Instituto Do Homem e Meio Ambiente da Amazonia Imazon |
Ribeiro Sales M.H.,Wageningen University |
Souza Jr. C.M.,Instituto Do Homem e Meio Ambiente da Amazonia Imazon |
Kyriakidis P.C.,University of California at Santa Barbara |
Kyriakidis P.C.,University of Aegean
IEEE Transactions on Geoscience and Remote Sensing | Year: 2013
The Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain availability. The first seven bands of MODIS are in the visible, near-infrared, and mid-infrared spectral regions of the electromagnetic spectrum which are sensitive to spectral changes due to deforestation, burned areas, and vegetation regrowth, among other land-use changes, making near-real-time forest monitoring a suitable application. However, the different spatial resolution of the spectral bands placed in these spectral regions imposes challenges to combine them in forest monitoring applications. In this paper, we present an algorithm based on geostatistics to downscale five 500-m MODIS pixel bands to match two 250-m pixel bands. We also discuss the advantages and limitations of this method in relation to existing downscaling algorithms. Our proposed method merges the data to the best spatial resolution and better retains the spectral information of the original data. © 2012 IEEE.
Kumar S.S.,South Dakota State University |
Roy D.P.,South Dakota State University |
Cochrane M.A.,South Dakota State University |
Souza Jr. C.M.,Instituto do Homem e Meio Ambiente da Amazonia Imazon |
And 2 more authors.
International Journal of Wildland Fire | Year: 2014
The Brazilian tropical moist forest biome (BTMFB) is experiencing high rates of deforestation and fire. Previous studies indicate that the majority of fires occur close to roads, however they did not consider the network of unofficial roads and navigable rivers, nor inter-state and inter-annual variability. We examine 8 years of Moderate Resolution Imaging Spectroradiometer (MODIS) active fire detections and the cumulative frequency distribution of the distance of each detection to the closest official road, unofficial road, and navigable river bank. Approximately 50 and 95% of all MODIS active fire detections occurred within 1 and 10km respectively of a road or navigable river. Inter-state and inter-annual variations are discussed and linkages to expansion of the road network are suggested. Comparison of the distance distribution of the MODIS active fire detections and the distance distribution of a 0.5-km spaced geographic grid to the combined roads and navigable river network revealed significant differences for each state and for the BTMFB and indicate that the great majority of fires are anthropogenic. The results provide insights that may be useful for modelling the incidence of fire under future expansion of the Amazonian road network and increased river navigability. © IAWF 2014.
Morton D.C.,NASA |
Sales M.H.,Instituto do Homem e Meio Ambiente da Amazonia Imazon |
Souza Jr C.M.,Instituto do Homem e Meio Ambiente da Amazonia Imazon |
Griscom B.,The Nature Conservancy
Carbon Balance and Management | Year: 2011
Background: Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from credited mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008.Results: Deforestation estimates showed good agreement for multi-year periods of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by > 20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C ha -1, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas.Conclusions: Estimates of source data uncertainties are essential for REDD+. Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions. © 2011 Morton et al; licensee BioMed Central Ltd.