Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

[1]  G. Kuczera,et al.  Hydroclimatic response of evapotranspiration partitioning to prolonged droughts in semiarid grassland , 2018, Journal of Hydrology.

[2]  Tsegaye Tadesse,et al.  Use of remote sensing indicators to assess effects of drought and human-induced land degradation on ecosystem health in Northeastern Brazil , 2018, Remote Sensing of Environment.

[3]  Michael Dixon,et al.  Google Earth Engine: Planetary-scale geospatial analysis for everyone , 2017 .

[4]  V. Mishra,et al.  High-resolution near real-time drought monitoring in South Asia , 2017, Scientific Data.

[5]  J. Gao,et al.  A knowledge-based approach to mapping degraded meadows on the Qinghai–Tibet Plateau, China , 2017 .

[6]  Víctor J García,et al.  Land Cover Classification in an Ecuadorian Mountain Geosystem Using a Random Forest Classifier, Spectral Vegetation Indices, and Ancillary Geographic Data , 2017 .

[7]  Stuart R. Phinn,et al.  A method for mapping Australian woody vegetation cover by linking continental-scale field data and long-term Landsat time series , 2017 .

[8]  J. Pekel,et al.  High-resolution mapping of global surface water and its long-term changes , 2016, Nature.

[9]  Gennadii Donchyts,et al.  Earth's surface water change over the past 30 years , 2016 .

[10]  Richard J. Hobbs,et al.  Degraded or just different? Perceptions and value judgements in restoration decisions , 2016 .

[11]  Thomas Gumbricht,et al.  Mapping of soil properties and land degradation risk in Africa using MODIS reflectance , 2016 .

[12]  Alexey Voinov,et al.  A review of methods, data, and models to assess changes in the value of ecosystem services from land degradation and restoration , 2016 .

[13]  J. Poore.  Call for conservation: Abandoned pasture. , 2016, Science.

[14]  James E. M. Watson,et al.  Shortfalls and Solutions for Meeting National and Global Conservation Area Targets , 2015 .

[15]  R. Denham,et al.  Operational Application of the Landsat Timeseries to Address Large Area Landcover Understanding , 2015 .

[16]  Stuart R. Phinn,et al.  Mapping woody vegetation clearing in Queensland, Australia from Landsat imagery using the Google Earth Engine , 2015 .

[17]  D. Goetze,et al.  Identification of driving factors of land degradation and deforestation in the Wildlife Reserve of Bontioli (Burkina Faso, West Africa) , 2015 .

[18]  Sergio M. Vicente-Serrano,et al.  Contribution of precipitation and reference evapotranspiration to drought indices under different climates , 2015 .

[19]  Sergio M. Vicente-Serrano,et al.  Drought Variability and Land Degradation in Semiarid Regions: Assessment Using Remote Sensing Data and Drought Indices (1982-2011) , 2015, Remote. Sens..

[20]  Nicholas J. Tate,et al.  A critical synthesis of remotely sensed optical image change detection techniques , 2015 .

[21]  H. Liniger,et al.  Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia , 2015 .

[22]  Holly K. Gibbs,et al.  Mapping the world's degraded lands , 2015 .

[23]  H. Possingham,et al.  Optimal Conservation Outcomes Require Both Restoration and Protection , 2015, PLoS biology.

[24]  J. Watson,et al.  The performance and potential of protected areas , 2014, Nature.

[25]  S. Vicente‐Serrano,et al.  Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring , 2014 .

[26]  Scott L. Powell,et al.  Bringing an ecological view of change to Landsat‐based remote sensing , 2014 .

[27]  Liana N. Joseph,et al.  Targeting Global Protected Area Expansion for Imperiled Biodiversity , 2014, PLoS biology.

[28]  Giles M. Foody,et al.  Good practices for estimating area and assessing accuracy of land change , 2014 .

[29]  M. H. Hamza,et al.  Setting up a Spatial Data Infrastructure (SDI) for the ROSELT/OSS Network , 2014 .

[30]  Neil Flood,et al.  Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median) , 2013, Remote. Sens..

[31]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[32]  Emmanuelle Quillérou,et al.  The rewards of investing in sustainable land management , 2013 .

[33]  Neil Flood,et al.  Cloud and cloud shadow screening across Queensland, Australia: An automated method for Landsat TM/ETM+ time series , 2013 .

[34]  M. S. Moran,et al.  Ecosystem resilience despite large-scale altered hydroclimatic conditions , 2013, Nature.

[35]  J. Angerer,et al.  Rangeland Degradation, Poverty, and Conflict: How Can Rangeland Scientists Contribute to Effective Responses and Solutions? , 2012 .

[36]  F. van den Bergh,et al.  Limits to detectability of land degradation by trend analysis of vegetation index data , 2012 .

[37]  Scarth Peter.  Tracking Grazing Pressure and Climate Interaction - The Role of Landsat Fractional Cover in Time Series Analysis , 2012 .

[38]  Thomas R. Loveland,et al.  A review of large area monitoring of land cover change using Landsat data , 2012 .

[39]  Michael Schmidt,et al.  Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method , 2012 .

[40]  Zhe Zhu,et al.  Object-based cloud and cloud shadow detection in Landsat imagery , 2012 .

[41]  Michael E. Schaepman,et al.  Desertification in the Sahel: Towards better accounting for ecosystem dynamics in the interpretation of remote sensing images , 2011 .

[42]  Eve McDonald-Madden,et al.  Optimal timing for managed relocation of species faced with climate change , 2011 .

[43]  Alan Grainger,et al.  Application of indicator systems for monitoring and assessment of desertification from national to global scales , 2011 .

[44]  Jürgen Vogt,et al.  Monitoring and assessment of land degradation and desertification: Towards new conceptual and integrated approaches , 2011 .

[45]  R. Bartley,et al.  Impacts of improved grazing land management on sediment yields, Part 1: Hillslope processes , 2010 .

[46]  D. Post,et al.  Impacts of improved grazing land management on sediment yields. Part 2: Catchment response. , 2010 .

[47]  S. Vicente‐Serrano,et al.  A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index , 2009 .

[48]  D. Jones,et al.  High-quality spatial climate data-sets for Australia , 2009 .

[49]  Peter Scarth,et al.  Land condition monitoring information for reef catchments : a new era , 2009 .

[50]  P. O'Reagain,et al.  Managing for rainfall variability: effect of grazing strategy on cattle production in a dry tropical savanna , 2009 .

[51]  Christian Töttrup,et al.  Regional desertification: A global synthesis , 2008 .

[52]  Susan L. Ustin,et al.  Identification of invasive vegetation using hyperspectral remote sensing in the California Delta ecosystem , 2008 .

[53]  M. Schaepman,et al.  Proxy global assessment of land degradation , 2008 .

[54]  I. Watson,et al.  Monitoring changes in pastoral rangelands – the Western Australian Rangeland Monitoring System (WARMS) , 2007 .

[55]  Lalit Kumar,et al.  Comparative assessment of the measures of thematic classification accuracy , 2007 .

[56]  K. Wessels,et al.  Relevance of rangeland degradation in semiarid northeastern South Africa to the nonequilibrium theory. , 2007, Ecological applications : a publication of the Ecological Society of America.

[57]  J. Ludwig,et al.  Leakiness: A new index for monitoring the health of arid and semiarid landscapes using remotely sensed vegetation cover and elevation data , 2007 .

[58]  P. Erskine,et al.  Restoration of Degraded Tropical Forest Landscapes , 2005, Science.

[59]  Michael L. Roderick,et al.  The use of time-integrated NOAA NDVI data and rainfall to assess landscape degradation in the arid shrubland of Western Australia , 2003 .

[60]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[61]  John A. Ludwig,et al.  CLEARING SAVANNAS FOR USE AS RANGELANDS IN QUEENSLAND: ALTERED LANDSCAPES AND WATER-EROSION PROCESSES , 2002 .

[62]  Giles M. Foody,et al.  Status of land cover classification accuracy assessment , 2002 .

[63]  H. Dregne.  Land Degradation in the Drylands , 2002 .

[64]  Klaus Hubacek,et al.  A scenario analysis of China's land use and land cover change: incorporating biophysical information into input–output modeling , 2001 .

[65]  Vijay P. Singh,et al.  Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome , 1993 .

[66]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[67]  M. I. Ahmad,et al.  Log-logistic flood frequency analysis , 1988 .

[68]  C. Priestley,et al.  On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters , 1972 .

[69]  W. Swinbank.  Long‐wave radiation from clear skies , 1963 .

[70]  Daniel Zízala,et al.  Assessment of Soil Degradation by Erosion Based on Analysis of Soil Properties Using Aerial Hyperspectral Images and Ancillary Data, Czech Republic , 2017, Remote. Sens..

[71]  Scarth Peter.  State of the paddock: monitoring condition and trend in ground cover across Queensland. , 2013 .

[72]  Ximing Cai,et al.  Land availability for biofuel production. , 2011, Environmental science & technology.

[73]  David B Lobell,et al.  Remote sensing of soil degradation: introduction. , 2010, Journal of environmental quality.

[74]  P. Caccetta,et al.  Salinity monitoring in Western Australia using remotely sensed and other spatial data. , 2010, Journal of environmental quality.

[75]  R. George,et al.  A methodology to estimate the future extent of dryland salinity in the southwest of Western Australia. , 2010, Journal of environmental quality.

[76]  Miguel Delibes,et al.  Use of Descriptors of Ecosystem Functioning for Monitoring a National Park Network: A Remote Sensing Approach , 2009, Environmental management.

[77]  Dengsheng Lu,et al.  Mapping and monitoring land degradation risks in the Western Brazilian Amazon using multitemporal Landsat TM/ETM+ images , 2007 .

[78]  N. Batjes.  Soil data resources for land suitability assessment and environmental protection in central and eastern Europe: the 1:2,500,000 scale SOVEUR project , 2001 .

[79]  G. Foody,et al.  A fuzzy classification of sub-urban land cover from remotely sensed imagery , 1998 .

[80]  L. R. Oldeman,et al.  World map of the status of human-induced soil degradation: an explanatory note. , 1990 .