Estimating tropical deforestation from Earth observation data

This article covers the very recent developments undertaken for estimating tropical deforestation from Earth observation data. For the United Nations Framework Convention on Climate Change process it is important to tackle the technical issues surrounding the ability to produce accurate and consistent estimates of GHG emissions from deforestation in developing countries. Remotely-sensed data are crucial to such efforts. Recent developments in regional to global monitoring of tropical forests from Earth observation can contribute to reducing the uncertainties in estimates of carbon emissions from deforestation. Data sources at approximately 30 m × 30 m spatial resolution already exist to determine reference historical rates of change from the early 1990s. Key requirements for implementing future monitoring programs, both at regional and pan-tropical regional scales, include international commitment of resources to ensure regular (at least yearly) pan-tropical coverage by satellite remote sensing imagery at a sufficient level of detail; access to such data at low-cost; and consensus protocols for satellite imagery analysis.

[1]  Douglas C. Morton,et al.  Rapid assessment of annual deforestation in the Brazilian Amazon using MODIS data , 2005 .

[2]  F. Rocca,et al.  The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle , 2011 .

[3]  F. Achard,et al.  Pan-tropical monitoring of deforestation , 2007 .

[4]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[5]  Ake Rosenqvist,et al.  The potential of long-wavelength satellite-borne radar to support implementation of the Ramsar Wetlands Convention , 2007 .

[6]  Stephen V. Stehman,et al.  Comparing estimators of gross change derived from complete coverage mapping versus statistical sampling of remotely sensed data , 2005 .

[7]  P. Defourny,et al.  Monitoring forest changes in Borneo on a yearly basis by an object-based change detection algorithm using SPOT-VEGETATION time series , 2012 .

[8]  Alan Grainger,et al.  Achieving forest carbon information with higher certainty: A five-part plan , 2010 .

[9]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[10]  Josef Kellndorfer,et al.  Large-Area Classification and Mapping of Forest and Land Cover in the Brazilian Amazon: A Comparative Analysis of ALOS/PALSAR and Landsat Data Sources , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[11]  Jeffrey G. Masek,et al.  Large Area Scene Selection Interface (LASSI): Methodology of Selecting Landsat Imagery for the Global Land Survey 2005. , 2009 .

[12]  Kenneth L. Denman Canada Couplings between changes in the climate system and biogeochemistry , 2008 .

[13]  M. Sgrenzaroli,et al.  Tropical forest cover monitoring: Estimates from the GRFM JERS-1 radar mosaics using wavelet zooming techniques and validation , 2002 .

[14]  Stephen V. Stehman,et al.  Sampling designs for accuracy assessment of land cover , 2009 .

[15]  R. B. Jackson,et al.  CO 2 emissions from forest loss , 2009 .

[16]  S. Fritz,et al.  A new land‐cover map of Africa for the year 2000 , 2004 .

[17]  Marc Simard,et al.  Large-scale vegetation maps derived from the combined L-band GRFM and C-band CAMP wide area radar mosaics of Central Africa , 2002 .

[18]  D. Roy,et al.  The suitability of decadal image data sets for mapping tropical forest cover change in the Democratic Republic of Congo: implications for the global land survey , 2008 .

[19]  Pol Coppin,et al.  Review ArticleDigital change detection methods in ecosystem monitoring: a review , 2004 .

[20]  Frédéric Achard,et al.  Pre-processing of a sample of multi-scene and multi-date Landsat imagery used to monitor forest cover changes over the tropics , 2011 .

[21]  C. Justice,et al.  Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005 , 2008 .

[22]  A. Angelsen Moving ahead with REDD: issues, options and implications , 2008 .

[23]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[24]  Belet Weyne Food and Agriculture Organization , 1949, International Organization.

[25]  Achard Frederic,et al.  GOFC-GOLD, 2010, A Sourcebook of Methods and Procedures for Monitoring and Reporting Anthropogenic Greenhouse Gas Emissions and Removals Caused by Deforestation, Gains and Losses of Carbon Stocks in Forests Remaining Forests, and Forestation , 2010 .

[26]  F. Achard,et al.  Challenges to estimating carbon emissions from tropical deforestation , 2007 .

[27]  Thuy Le Toan,et al.  Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets , 2004 .

[28]  R. DeFries,et al.  Deforestation driven by urban population growth and agricultural trade in the twenty-first century , 2010 .

[29]  David E. Knapp,et al.  Automated mapping of tropical deforestation and forest degradation: CLASlite , 2009 .

[30]  Bicheron Patrice,et al.  The Most Detailed Portrait of Earth , 2008 .

[31]  S. Goetz,et al.  Reply to Comment on ‘A first map of tropical Africa’s above-ground biomass derived from satellite imagery’ , 2008, Environmental Research Letters.

[32]  D. Roy,et al.  A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo Basin , 2008 .

[33]  S. Goetz,et al.  Mapping and monitoring carbon stocks with satellite observations: a comparison of methods , 2009, Carbon balance and management.

[34]  Sandra A. Brown,et al.  Monitoring and estimating tropical forest carbon stocks: making REDD a reality , 2007 .

[35]  Gregory P Asner,et al.  Changing Drivers of Deforestation and New Opportunities for Conservation , 2009, Conservation biology : the journal of the Society for Conservation Biology.

[36]  G. Powell,et al.  High-resolution forest carbon stocks and emissions in the Amazon , 2010, Proceedings of the National Academy of Sciences.

[37]  Stephen V. Stehman,et al.  A comparison of sampling designs for estimating deforestation from Landsat imagery: A case study of the Brazilian Legal Amazon , 2009 .

[38]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[39]  F. J. Gallego,et al.  Stratified sampling of satellite images with a systematic grid of points , 2005 .

[40]  R. DeFries,et al.  A Contemporary Assessment of Change in Humid Tropical Forests , 2009, Conservation biology : the journal of the Society for Conservation Biology.

[41]  F. Achard,et al.  Monitoring Forest Areas from Continental to Territorial Levels Using a Sample of Medium Spatial Resolution Satellite Imagery , 2010 .

[42]  J. Townshend,et al.  Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data , 2008, Proceedings of the National Academy of Sciences.

[43]  M. Lefsky A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System , 2010 .

[44]  F. Wagner,et al.  Good Practice Guidance for Land Use, Land-Use Change and Forestry , 2003 .

[45]  S. Goetz,et al.  Importance of biomass in the global carbon cycle , 2009 .

[46]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[47]  R. McRoberts,et al.  Remote sensing support for national forest inventories , 2007 .

[48]  Dirk H. Hoekman,et al.  PALSAR Wide-Area Mapping of Borneo: Methodology and Map Validation , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[49]  F. Achard,et al.  Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s , 2010, Proceedings of the National Academy of Sciences.

[50]  J. Townshend,et al.  Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[51]  G. Foody Assessing the accuracy of land cover change with imperfect ground reference data , 2010 .

[52]  M. Steininger,et al.  Effects of systematic sampling on satellite estimates of deforestation rates , 2009 .

[53]  W. Edeson Food and Agriculture Organization of the UN , 1996 .

[54]  Michael Berger,et al.  The optical high-resolution mission for GIMES operational services , 2007 .

[55]  Steffen Fritz,et al.  A land‐cover map for South and Southeast Asia derived from SPOT‐VEGETATION data , 2007 .

[56]  Yosio Edemir Shimabukuro,et al.  Using dual‐polarized ALOS PALSAR data for detecting new fronts of deforestation in the Brazilian Amazônia , 2009 .

[57]  F. Achard,et al.  A Synthesis of Information on Rapid Land-cover Change for the Period 1981–2000 , 2005 .

[58]  Eli Kintisch,et al.  Improved Monitoring of Rainforests Helps Pierce Haze of Deforestation , 2007, Science.

[59]  David B. Lindenmayer,et al.  Re-evaluation of forest biomass carbon stocks and lessons from the world's most carbon-dense forests , 2009, Proceedings of the National Academy of Sciences.

[60]  F. Achard,et al.  Tropical forest cover change in the 1990s and options for future monitoring , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[61]  S. Fritz,et al.  A land cover map of South America , 2004 .

[62]  A. Belward,et al.  GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .

[63]  F. Achard,et al.  Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates , 2008 .

[64]  Matthew C. Hansen,et al.  The global Landsat imagery database for the FAO FRA remote sensing survey , 2011, Int. J. Digit. Earth.

[65]  A. Mather,et al.  Global Forest Resources , 1990 .

[66]  Frédéric Achard,et al.  Tropical forest mapping from coarse spatial resolution satellite data: Production and accuracy assessment issues , 2001 .

[67]  Sean C. Thomas,et al.  Increasing carbon storage in intact African tropical forests , 2009, Nature.

[68]  Ruth S. DeFries,et al.  Estimation of tree cover using MODIS data at global, continental and regional/local scales , 2005 .

[69]  Philippe Ciais,et al.  Weak Northern and Strong Tropical Land Carbon Uptake from Vertical Profiles of Atmospheric CO2 , 2007, Science.

[70]  Steffen Fritz,et al.  Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover , 2009, Remote. Sens..

[71]  P. Snoeij,et al.  Sentinel-1 - the radar mission for GMES operational land and sea services , 2007 .

[72]  Christelle Vancutsem,et al.  Mapping and characterizing the vegetation types of the Democratic Republic of Congo using SPOT VEGETATION time series , 2009, Int. J. Appl. Earth Obs. Geoinformation.

[73]  Patrick Bogaert,et al.  Forest change detection by statistical object-based method , 2006 .

[74]  F. Kraxner,et al.  An assessment of monitoring requirements and costs of 'Reduced Emissions from Deforestation and Degradation' , 2009, Carbon balance and management.

[75]  Ruth S. DeFries,et al.  Earth observations for estimating greenhouse gas emissions from deforestation in developing countries , 2007 .

[76]  Frédéric Achard,et al.  Improved estimates of net carbon emissions from land cover change in the tropics for the 1990s , 2004 .

[77]  Martin Herold,et al.  A joint initiative for harmonization and validation of land cover datasets , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[78]  Limin Yang,et al.  An analysis of the IGBP global land-cover characterization process , 1999 .

[79]  J. V. Soares,et al.  Distribution of aboveground live biomass in the Amazon basin , 2007 .

[80]  F. Achard,et al.  An incentive mechanism for reducing emissions from conversion of intact and non-intact forests , 2007 .

[81]  Erik Næsset,et al.  Using remotely sensed data to construct and assess forest attribute maps and related spatial products , 2010 .

[82]  C. Tucker,et al.  NASA’s Global Orthorectified Landsat Data Set , 2004 .

[83]  R. Houghton,et al.  Aboveground Forest Biomass and the Global Carbon Balance , 2005 .

[84]  Gregory Duveiller,et al.  Deforestation in Central Africa: Estimates at regional, national and landscape levels by advanced processing of systematically-distributed Landsat extracts , 2008 .

[85]  Martyna Poreba,et al.  Assessing the accuracy of land-based mobile laser scanning data , 2012 .

[86]  R. Czaplewski,et al.  Can a sample of Landsat sensor scenes reliably estimate the global extent of tropical deforestation? , 2003 .

[87]  S. Stehman Sampling Designs for Assessing Map Accuracy , 2008 .

[88]  Christina Corbane,et al.  Land use monitoring by remote sensing in tropical forest areas in support of the Kyoto Protocol: the case of French Guiana , 2009 .

[89]  A. Grainger Difficulties in tracking the long-term global trend in tropical forest area , 2008, Proceedings of the National Academy of Sciences.

[90]  David M. Wilkinson,et al.  The parable of Green Mountain: Ascension Island, ecosystem construction and ecological fitting , 2004 .

[91]  B. Lasserre,et al.  Patterns and trends in tropical forest cover , 2009 .