{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T05:22:26Z","timestamp":1772601746636,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,23]],"date-time":"2018-04-23T00:00:00Z","timestamp":1524441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The presence and distribution of green vegetation cover in the biosphere are of paramount importance in investigating cause-effect phenomena at the land\/atmosphere interface, estimating primary production rates as part of global carbon and water cycle assessments and evaluating soil protection and land use change over time. The fraction of green vegetation cover (FCover) as estimated from satellite observations has already been demonstrated to be an extraordinarily useful product for understanding vegetation cover changes, for supporting ecosystem service assessments over areas with variable extents and for processes spanning a variable period of time (abrupt events or long-term processes). This study describes a methodology implemented to estimate global FCover (from 2001 to 2015) by applying a linear spectral mixture analysis with global endmembers to an entire temporal series of MODIS satellite observations and gap-filling missing FCover observations in temporal series using the DINEOF algorithm. The resulting global MODV1 FCover product was validated with two global validation datasets and showed an overall good thematic absolute accuracy (RMSE = 0.146) consistent with the validation performance of other FCover global products. Basic statistics performed on the product show changes in average and trend values and allow for the quantification of gross vegetation loss and gain over different temporal scales. To demonstrate the capacity of this global product to monitor specific dynamics, a multitemporal analysis was performed on selected sites and vegetation responses (i.e., cover changes), and specific dynamics resulting from cause-effect phenomena are briefly discussed. The product is intended to be used for monitoring vegetation dynamics, but it also has the potential to be integrated in other modeling frameworks (e.g., the carbon cycle, primary production, and soil erosion) in conjunction with other spatial datasets such as those on climate and soil type.<\/jats:p>","DOI":"10.3390\/rs10040653","type":"journal-article","created":{"date-parts":[[2018,4,24]],"date-time":"2018-04-24T04:44:48Z","timestamp":1524545088000},"page":"653","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Global MODIS Fraction of Green Vegetation Cover for Monitoring Abrupt and Gradual Vegetation Changes"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1419-3734","authenticated-orcid":false,"given":"Federico","family":"Filipponi","sequence":"first","affiliation":[{"name":"Institute for Environmental Protection and Research (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy"}]},{"given":"Emiliana","family":"Valentini","sequence":"additional","affiliation":[{"name":"Institute for Environmental Protection and Research (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy"}]},{"given":"Alessandra","family":"Nguyen Xuan","sequence":"additional","affiliation":[{"name":"Institute for Environmental Protection and Research (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4917-2105","authenticated-orcid":false,"given":"Carlos A.","family":"Guerra","sequence":"additional","affiliation":[{"name":"Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108 Halle (Saale), Germany"},{"name":"German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5E, 04103 Leipzig, Germany"}]},{"given":"Florian","family":"Wolf","sequence":"additional","affiliation":[{"name":"Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108 Halle (Saale), Germany"},{"name":"German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5E, 04103 Leipzig, Germany"}]},{"given":"Martin","family":"Andrzejak","sequence":"additional","affiliation":[{"name":"Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, 06108 Halle (Saale), Germany"},{"name":"German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5E, 04103 Leipzig, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0865-4124","authenticated-orcid":false,"given":"Andrea","family":"Taramelli","sequence":"additional","affiliation":[{"name":"Institute for Environmental Protection and Research (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy"},{"name":"IUSS-Istituto Universitario di Studi Superiori di Pavia, Palazzo del Broletto\u2014Piazza della Vittoria n.15, 27100 Pavia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1126\/science.1229931","article-title":"Essential Biodiversity Variables","volume":"339","author":"Pereira","year":"2013","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"878","DOI":"10.1007\/s10021-014-9766-4","article-title":"Mapping Soil Erosion Prevention Using an Ecosystem Service Modeling Framework for Integrated Land Management and Policy","volume":"17","author":"Guerra","year":"2014","journal-title":"Ecosystems"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.cosust.2015.03.007","article-title":"Linking biodiversity, ecosystem services, and human well-being: Three challenges for designing research for sustainability","volume":"14","author":"Bennett","year":"2015","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0169-2046(02)00149-4","article-title":"Turning brownfields into green space in the City of Toronto","volume":"62","year":"2003","journal-title":"Landsc. Urban Plan."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1080\/01426397.2016.1173658","article-title":"Urban green infrastructure and urban forests: A case study of the Metropolitan Area of Milan","volume":"42","author":"Sanesi","year":"2017","journal-title":"Landsc. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.gloenvcha.2005.08.004","article-title":"Recent trends in vegetation dynamics in the African Sahel and their relationship to climate","volume":"15","author":"Herrmann","year":"2005","journal-title":"Glob. Environ. Chang."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.rse.2006.07.014","article-title":"Neural network estimation of LAI, fAPAR, fCover and LAI\u00d7 C ab, from top of canopy MERIS reflectance data: Principles and validation","volume":"105","author":"Bacour","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.ecocom.2011.07.003","article-title":"Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China","volume":"8","author":"Fu","year":"2011","journal-title":"Ecol. Complex."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.ecolind.2015.06.043","article-title":"An assessment of soil erosion prevention by vegetation in Mediterranean Europe: Current trends of ecosystem service provision","volume":"60","author":"Guerra","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/S0169-5347(03)00070-3","article-title":"Remote sensing for biodiversity science and conservation","volume":"18","author":"Turner","year":"2003","journal-title":"Trends Ecol. Evol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.3390\/rs4061781","article-title":"Exploring the use of MODIS NDVI-based phenology indicators for classifying forest general habitat categories","volume":"4","author":"Clerici","year":"2012","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/0143116031000115328","article-title":"Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA","volume":"25","author":"Wan","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.1007\/s11629-016-3971-x","article-title":"Using leaf area index (LAI) to assess vegetation response to drought in Yunnan province of China","volume":"14","author":"Kim","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combination for monitoring vegetation","volume":"8","author":"Tacker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relation between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/0034-4257(94)90016-7","article-title":"On the relationship between FAPAR and NDVI","volume":"49","author":"Myneni","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.cosust.2018.02.005","article-title":"Monitoring biodiversity change through effective global coordination","volume":"29","author":"Navarro","year":"2017","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_18","unstructured":"Lacaze, R., Atzberger, C., Bartholom\u00e9, E., Combal, B., Calvet, J.C., Lef\u00e8vre, V., and Olsson, B. (2009). BioPar User Requirements, GEOLAND."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/S0034-4257(01)00300-5","article-title":"Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements","volume":"80","author":"Chen","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.rse.2007.03.001","article-title":"LAI and fAPAR CYCLOPES global products derived from VEGETATION. Part 2: Validation and comparison with MODIS collection 4 products","volume":"110","author":"Weiss","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.rse.2015.06.001","article-title":"Exploiting the multi-angularity of the MODIS temporal signal to identify spatially homogeneous vegetation cover: A demonstration for agricultural monitoring applications","volume":"166","author":"Duveiller","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2007.02.018","article-title":"LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm","volume":"110","author":"Baret","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.rse.2012.12.027","article-title":"GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 1: Principles of development and production","volume":"137","author":"Baret","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.rse.2013.02.030","article-title":"GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and Intercomparison with reference products","volume":"137","author":"Camacho","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_25","first-page":"93","article-title":"Early validation of PROBA-V GEOV1 LAI, FAPAR and FCOVER products for the continuity of the Copernicus Global Land Service","volume":"40","author":"Camacho","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_26","unstructured":"Myneni, R.B., Knyazikhin, Y., Park, T., and MOD15A2H MODIS\/Terra Leaf Area Index\/FPAR 8-Day L4 Global 500 m SIN Grid V006 (2017, December 14). NASA EOSDIS Land Processes DAAC. Available online: https:\/\/lpdaac. usgs. gov\/dataset_discovery\/modis\/modis_products_table\/mod15a2h_v006."},{"key":"ref_27","unstructured":"Didan, K., and MOD13A3 MODIS\/Terra Vegetation Indices Monthly L3 Global 1 km SIN Grid V006 (2017, December 14). NASA EOSDIS Land Processes DAAC. Available online: https:\/\/lpdaac.usgs.gov\/dataset_discovery\/modis\/modis_products_table\/mod13a3_v006."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/36.124212","article-title":"Remote sensing of cloud, aerosol, and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS)","volume":"30","author":"King","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1109\/JSTARS.2010.2075916","article-title":"An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data","volume":"4","author":"Tan","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3631","DOI":"10.1021\/ac034173t","article-title":"A perfect smoother","volume":"75","author":"Eilers","year":"2003","journal-title":"Anal. Chem."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.rse.2012.04.001","article-title":"Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology","volume":"123","author":"Atkinson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"333","DOI":"10.3390\/rs1020333","article-title":"Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data","volume":"2","author":"Neteler","year":"2010","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1175\/1520-0426(2003)020<1839:ECADFF>2.0.CO;2","article-title":"EOF Calculations and Data Filling from Incomplete Oceanographic Datasets","volume":"20","author":"Beckers","year":"2003","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_35","unstructured":"Gerber, F., Furrer, R., Schaepman-Strub, G., de Jong, R., and Schaepman, M.E. (arXiv, 2016). Predicting missing values in spatio-temporal satellite data, arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4353","DOI":"10.5194\/amt-7-4353-2014","article-title":"Scientific impact of MODIS C5 calibration degradation and C6+ improvements","volume":"7","author":"Lyapustin","year":"2014","journal-title":"Atmos. Meas. Technol."},{"key":"ref_37","unstructured":"Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Core Team."},{"key":"ref_38","unstructured":"Hijmans, R.J. (2017, December 14). Raster: Geographic Data Analysis and Modeling. Available online: https:\/\/CRAN.R-project.org\/package=raster."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Qiu, Y., and Mei, J. (2017, December 14). RSpectra: Solvers for Large Scale Eigenvalue and SVD Problems. Available online: https:\/\/CRAN.R-project.org\/package=RSpectra.","DOI":"10.32614\/CRAN.package.RSpectra"},{"key":"ref_40","unstructured":"Taylor, M. (2017, December 14). Sinkr: Collection of Functions with Emphasis in Multivariate Data Analysis. Available online: https:\/\/github.com\/marchtaylor\/sinkr."},{"key":"ref_41","unstructured":"(2017, December 14). SNAP Core Team SNAP: ESA Sentinel Application Platform v4.0. Available online: http:\/\/step.esa.int."},{"key":"ref_42","unstructured":"GDAL (2017, December 14). Geospatial Data Abstraction Library, Open Source Geospatial Foundation. Available online: http:\/\/gdal.osgeo.org."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Manfron, G., Crema, A., Boschetti, M., and Confalonieri, R. (2012, January 24\u201326). Testing automatic procedures to map rice area and detect phenological crop information exploiting time series analysis of remote sensed MODIS data. Proceedings of the SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, Edinburgh, UK.","DOI":"10.1117\/12.974662"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2004.06.007","article-title":"The Landsat ETM+ spectral mixing space","volume":"93","author":"Small","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_45","first-page":"8089","article-title":"Spectral mixture modeling: A new analysis of rock and soil types at the viking lander 1 site","volume":"91","author":"Adams","year":"1986","journal-title":"J. Geophys. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"15956","DOI":"10.1038\/srep15956","article-title":"Vegetation greening and climate change promote multidecadal rises of global land evapotranspiration","volume":"5","author":"Zhang","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.rse.2011.12.001","article-title":"Impact of sensor degradation on the MODIS NDVI time series","volume":"119","author":"Wang","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1016\/j.rse.2013.05.024","article-title":"Multi-scale standardized spectral mixture models","volume":"136","author":"Small","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2017.01.033","article-title":"Global cross-calibration of Landsat spectral mixture models","volume":"192","author":"Sousa","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Taramelli, A., Valentini, E., Innocenti, C., and Cappucci, S. (2013, January 21\u201326). FHYL: Field spectral libraries, airborne hyperspectral images and topographic and bathymetric LiDAR data for complex coastal mapping. Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, Melbourne, Australia.","DOI":"10.1109\/IGARSS.2013.6723270"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.ocecoaman.2014.07.015","article-title":"An effective procedure for EUNIS and Natura 2000 habitat type mapping in estuarine ecosystems integrating ecological knowledge and remote sensing analysis","volume":"108","author":"Valentini","year":"2015","journal-title":"Ocean Coast. Manag."},{"key":"ref_52","first-page":"54","article-title":"Spectral characterization of coastal sediments using Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR Data (FHyL)","volume":"36","author":"Manzo","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"62","DOI":"10.2112\/SI77-007.1","article-title":"A hybrid power law approach for spatial and temporal pattern analysis of salt marsh evolution","volume":"77","author":"Taramelli","year":"2017","journal-title":"J. Coast. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"9194","DOI":"10.1175\/JCLI-D-13-00089.1","article-title":"On the Sensitivity of Field Reconstruction and Prediction Using Empirical Orthogonal Functions Derived from Gappy Data","volume":"26","author":"Taylor","year":"2013","journal-title":"J. Clim."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.ocemod.2004.08.001","article-title":"Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: Application to the Adriatic Sea surface temperature","volume":"9","author":"Barth","year":"2005","journal-title":"Ocean Model."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1794","DOI":"10.1109\/TGRS.2006.876030","article-title":"Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products. Proposition of the CEOS-BELMANIP","volume":"44","author":"Baret","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_57","first-page":"EGU2015-2209-1","article-title":"Collection of Ground Biophysical Measurements in support of Copernicus Global Land Product Validation: The ImagineS database","volume":"17","author":"Camacho","year":"2015","journal-title":"Geophys. Res. Abstr."},{"key":"ref_58","unstructured":"Schaepman-Strub, G., Rom\u00e1n, M., and Nickeson, J. (2014). Global Leaf Area Index Product Validation Good Practices, Best Practice for Satellite-Derived Land Product Validation."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1804","DOI":"10.1109\/TGRS.2006.872529","article-title":"Validation of global moderate-resolution LAI products: A framework proposed within the CEOS land product validation subgroup","volume":"44","author":"Morisette","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.rse.2009.08.014","article-title":"Detecting Trend and Seasonal Changes in Satellite Image Time Series","volume":"114","author":"Verbesselt","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.tree.2005.07.009","article-title":"Tropical forests in a changing environment","volume":"20","author":"Wright","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_62","first-page":"159","article-title":"The tasselled cap\u2014A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat","volume":"1","author":"Kauth","year":"1976","journal-title":"Lab. Appl. Remote Sens. Symp."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Jia, K., Li, Y., Liang, S., Wei, X., and Yao, Y. (2017). Combining Estimation of Green Vegetation Fraction in an Arid Region from Landsat 7 ETM+ Data. Remote Sens., 9.","DOI":"10.3390\/rs9111121"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0034-4257(98)00037-6","article-title":"Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models","volume":"65","author":"Roberts","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Degerickx, J., Okujeni, A., Iordache, M.D., Hermy, M., van der Linden, S., and Somers, B. (2017). A Novel Spectral Library Pruning Technique for Spectral Unmixing of Urban Land Cover. Remote Sens., 9.","DOI":"10.3390\/rs9060565"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1109\/TGRS.2010.2086463","article-title":"Integrating MODIS and CYCLOPES leaf area index products using empirical orthogonal functions","volume":"49","author":"Wang","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2789","DOI":"10.1016\/j.rse.2008.01.006","article-title":"Performances of neural networks for deriving LAI estimates from existing CYCLOPES and MODIS products","volume":"112","author":"Verger","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1844","DOI":"10.1109\/TGRS.2007.895841","article-title":"Stripe noise reduction in MODIS data by combining histogram matching with facet filter","volume":"45","author":"Rakwatin","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"13233","DOI":"10.3390\/rs71013233","article-title":"Spatial and temporal patterns of global NDVI trends: Correlations with climate and human factors","volume":"7","author":"Liu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_70","unstructured":"Schmuck, G., San-Miguel-Ayanz, J., Barbosa, P., Camia, A., Kucera, J., Libert\u00e0, G., Buccella, P., Schulte, E., Flies, R., and Colletti, L. (2004). Forest Fires in Europe\u20142003 Fire Campaign, European Communities."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"673","DOI":"10.5194\/nhess-10-673-2010","article-title":"Post-fire vegetation recovery in Portugal based on spot\/vegetation data","volume":"10","author":"Gouveia","year":"2010","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/j.tree.2008.06.012","article-title":"How will oil palm expansion affect biodiversity?","volume":"23","author":"Fitzherbert","year":"2008","journal-title":"Trends Ecol. Evol."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1038\/nclimate1702","article-title":"Carbon emissions from forest conversion by Kalimantan oil palm plantations","volume":"3","author":"Carlson","year":"2013","journal-title":"Nat. Clim. Chang."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Rosa, I.M.D., Purves, D., Souza, C., and Ewers, R.M. (2013). Predictive Modelling of Contagious Deforestation in the Brazilian Amazon. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0077231"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10113-014-0614-z","article-title":"Modelling land cover change in the Brazilian Amazon: Temporal changes in drivers and calibration issues","volume":"15","author":"Rosa","year":"2014","journal-title":"Reg. Environ. Chang."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"175","DOI":"10.3406\/morfo.2001.1100","article-title":"Morphological changes and erosion processes following the 1982 eruption of El Chich\u00f3n volcano, Chiapas, Mexico\/Modifications g\u00e9omorphologiques et processus d\u2019\u00e9rosion cons\u00e9cutifs \u00e0 l\u2019\u00e9ruption du volcan El Chich\u00f3n, Chiapas, Mexico, en 1982","volume":"7","author":"Inbar","year":"2001","journal-title":"G\u00e9omorphologie"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/653\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:01:45Z","timestamp":1760194905000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/653"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,23]]},"references-count":76,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["rs10040653"],"URL":"https:\/\/doi.org\/10.3390\/rs10040653","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,23]]}}}