Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

[1]  F. P. Cabello,et al.  Land Surface Temperature (LST) estimated from Landsat images: applications in burnt areas and tree-grass woodlands (dehesas) , 2016 .

[2]  Artur Gil,et al.  Using a stochastic gradient boosting algorithm to analyse the effectiveness of Landsat 8 data for montado land cover mapping: Application in southern Portugal , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[3]  Alessandro Cescatti,et al.  Biophysical climate impacts of recent changes in global forest cover , 2016, Science.

[4]  N. Guiomar,et al.  A remote sensing-based approach to estimating montado canopy density using the FCD model: a contribution to identifying HNV farmlands in southern Portugal , 2016, Agroforestry Systems.

[5]  N. Guiomar,et al.  Assessment of environment, land management, and spatial variables on recent changes in montado land cover in southern Portugal , 2016, Agroforestry Systems.

[6]  Nektarios Chrysoulakis,et al.  Estimation of the Land Surface Albedo Changes in the Broader Mediterranean Area, Based on 12 Years of Satellite Observations , 2015, Remote. Sens..

[7]  D. Roberts,et al.  Relationships between dominant plant species, fractional cover and Land Surface Temperature in a Mediterranean ecosystem , 2015 .

[8]  Xiangke Liao,et al.  Correction: Corrigendum: Genome-wide adaptive complexes to underground stresses in blind mole rats Spalax , 2015, Nature Communications.

[9]  Jiawen Zhu,et al.  Comprehensive study on the influence of evapotranspiration and albedo on surface temperature related to changes in the leaf area index , 2015, Advances in Atmospheric Sciences.

[10]  S. Seneviratne,et al.  Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation , 2015, Climate Dynamics.

[11]  Shuangcheng Li,et al.  Local cooling and warming effects of forests based on satellite observations , 2015, Nature Communications.

[12]  G. Bala,et al.  Effects of large-scale deforestation on precipitation in the monsoon regions: Remote versus local effects , 2015, Proceedings of the National Academy of Sciences.

[13]  Michael A. Wulder,et al.  Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm , 2015 .

[14]  N. Oppelt,et al.  Tree cover and forest cover dynamics in the Mekong Basin from 2001 to 2011 , 2015 .

[15]  Suhong Liu,et al.  Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products , 2015, Remote. Sens..

[16]  Jingfeng Xiao,et al.  Satellite evidence for significant biophysical consequences of the “Grain for Green” Program on the Loess Plateau in China , 2014 .

[17]  Kaiguang Zhao,et al.  Biophysical forcings of land‐use changes from potential forestry activities in North America , 2014 .

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

[19]  M. Hill Vegetation index suites as indicators of vegetation state in grassland and savanna: An analysis with simulated SENTINEL 2 data for a North American transect , 2013 .

[20]  Jan Pokorný,et al.  Daily dynamics of radiation surface temperature of different land cover types in a temperate cultural landscape: Consequences for the local climate , 2013 .

[21]  José A. Sobrino,et al.  Satellite-derived land surface temperature: Current status and perspectives , 2013 .

[22]  M. Clara,et al.  Decline of Mediterranean oak trees and its association with Phytophthora cinnamomi: a review , 2013, European Journal of Forest Research.

[23]  P. Hesslerová,et al.  Surface temperature and hydrochemistry as indicators of land cover functions , 2012 .

[24]  Javed Mallick,et al.  Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[25]  T. Andrews,et al.  An update on Earth's energy balance in light of the latest global observations , 2012 .

[26]  C. Field,et al.  Theoretical Impact of Changing Albedo on Precipitation at the Southernmost Boundary of the ITCZ in South America , 2012 .

[27]  Jian Yang,et al.  Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands: Comparison of vegetation indices and spectral mixture analysis , 2012 .

[28]  P. Hesslerová,et al.  Evapotranspiration – A Driving Force in Landscape Sustainability , 2012 .

[29]  Michael A. Wulder,et al.  Recent rates of forest harvest and conversion in North America , 2011 .

[30]  Maosheng Zhao,et al.  A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests , 2011 .

[31]  G. Sun,et al.  Evapotranspiration and soil water relationships in a range of disturbed and undisturbed ecosystems in the semi-arid Inner Mongolia, China , 2011 .

[32]  Gordon B. Bonan,et al.  Anthropogenic land cover changes in a GCM with surface albedo changes based on MODIS data , 2010 .

[33]  H. Jones,et al.  Remote Sensing of Vegetation: Principles, Techniques, and Applications , 2010 .

[34]  Thomas Raddatz,et al.  Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change , 2010 .

[35]  Mingquan Wu,et al.  Please Scroll down for Article International Journal of Remote Sensing Nondestructive Estimation of Canopy Chlorophyll Content Using Hyperion and Landsat/tm Images Nondestructive Estimation of Canopy Chlorophyll Content Using Hyperion and Landsat/tm Images , 2022 .

[36]  A. Barbati,et al.  Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems , 2010 .

[37]  Alvaro Montenegro,et al.  The net carbon drawdown of small scale afforestation from satellite observations , 2009 .

[38]  D. Barrett,et al.  Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors. , 2009 .

[39]  Tobias Plieninger,et al.  Modification of Land Cover in a Traditional Agroforestry System in Spain: Processes of Tree Expansion and Regression , 2008 .

[40]  J Elith,et al.  A working guide to boosted regression trees. , 2008, The Journal of animal ecology.

[41]  Yichun Xie,et al.  Remote sensing imagery in vegetation mapping: a review , 2008 .

[42]  E. Lambin,et al.  The emergence of land change science for global environmental change and sustainability , 2007, Proceedings of the National Academy of Sciences.

[43]  J. Qu,et al.  NMDI: A normalized multi‐band drought index for monitoring soil and vegetation moisture with satellite remote sensing , 2007 .

[44]  Renee A. McPherson,et al.  A review of vegetation—atmosphere interactions and their influences on mesoscale phenomena , 2007 .

[45]  Eduardo Zorita,et al.  European climate response to tropical volcanic eruptions over the last half millennium , 2007 .

[46]  Giles M. Foody,et al.  Land cover classification using multi‐temporal MERIS vegetation indices , 2007 .

[47]  Kees Klein Goldewijk,et al.  Biogeophysical effects of land use on climate : Model simulations of radiative forcing and large-scale temperature change , 2007 .

[48]  J. Qi,et al.  Remote Sensing for Grassland Management in the Arid Southwest , 2006 .

[49]  H. Jones,et al.  Integrating hyperspectral imagery at different scales to estimate component surface temperatures , 2006 .

[50]  J. Carreiras,et al.  Estimation of tree canopy cover in evergreen oak woodlands using remote sensing , 2006 .

[51]  A. Viña,et al.  Remote estimation of canopy chlorophyll content in crops , 2005 .

[52]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[53]  J. Rogan,et al.  Remote sensing technology for mapping and monitoring land-cover and land-use change , 2004 .

[54]  Z. Wan,et al.  Quality assessment and validation of the MODIS global land surface temperature , 2004 .

[55]  A. Pitman The evolution of, and revolution in, land surface schemes designed for climate models , 2003 .

[56]  Clemente Gallardo,et al.  Sensitivity of the Iberian Peninsula climate to a land degradation , 2003 .

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

[58]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[59]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[60]  J. Friedman Stochastic gradient boosting , 2002 .

[61]  Mark A. Friedl,et al.  Forward and inverse modeling of land surface energy balance using surface temperature measurements , 2002 .

[62]  J. Friedman Greedy function approximation: A gradient boosting machine. , 2001 .

[63]  S. Liess,et al.  Impacts of deforestation and afforestation in the Mediterranean region as simulated by the MPI atmospheric GCM , 2001 .

[64]  P. Dirmeyer,et al.  Modeling the effects of vegetation on Mediterranean climate during the Roman Classical Period: Part I: Climate history and model sensitivity , 2000 .

[65]  S. Rambal,et al.  The dehesa system of southern Spain and Portugal as a natural ecosystem mimic , 1999, Agroforestry Systems.

[66]  V. Ponce,et al.  Surface Albedo and Water Resources: Hydroclimatological Impact of Human Activities , 1997 .

[67]  A. Huete,et al.  A comparison of vegetation indices over a global set of TM images for EOS-MODIS , 1997 .

[68]  Paul A. Dirmeyer,et al.  Albedo as a modulator of climate response to tropical deforestation , 1994 .

[69]  Serge Rambal,et al.  Testing an area-weighted model for albedo or surface temperature of mixed pixels in Mediterranean woodlands. , 1990 .

[70]  D. H. Card,et al.  Remote sensing of forest canopy and leaf biochemical contents , 1988 .

[71]  P. Jarvis,et al.  CHANGES IN CHLOROPHYLL AND CAROTENOID CONTENT, SPECIFIC LEAF AREA AND DRY WEIGHT FRACTION IN SITKA SPRUCE, IN RESPONSE TO SHADING AND SEASON , 1977 .

[72]  Jack Kornfield,et al.  A Comparative Study of the Effects of Albedo Change on Drought in Semi-Arid Regions. , 1977 .

[73]  J. Charney,et al.  Drought in the Sahara: A Biogeophysical Feedback Mechanism , 1975, Science.

[74]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[75]  Nathalie de Noblet-Ducoudré,et al.  Climatic Impact of Global-Scale Deforestation: Radiative versus Nonradiative Processes , 2010 .

[76]  H. Rodríguez,et al.  Seasonal Trends of Chlorophylls a and b and Carotenoids(x + c) in Native Trees and Shrubs of Northeastern Mexico , 2008 .

[77]  J. Camarero,et al.  Drought and Forest Decline in the Iberian Peninsula: A Simple Explanation for a Complex Phenomenom? , 2008 .

[78]  L. Olea,et al.  The Spanish dehesa. A traditional Mediterranean silvopastoral system linking production and nature conservation , 2006 .

[79]  Gordon B. Bonan,et al.  Ecological Climatology: Concepts and Applications , 2002 .