{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T17:18:17Z","timestamp":1764350297825,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,15]],"date-time":"2015-09-15T00:00:00Z","timestamp":1442275200000},"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>Soil erosion can be linked to relative fractional cover of photosynthetic-active vegetation (PV), non-photosynthetic-active vegetation (NPV) and bare soil (BS), which can be integrated into erosion models as the cover-management C-factor. This study investigates the capability of EnMAP imagery to map fractional cover in a region near San Jose, Costa Rica, characterized by spatially extensive coffee plantations and grazing in a mountainous terrain. Simulated EnMAP imagery is based on airborne hyperspectral HyMap data. Fractional cover estimates are derived in an automated fashion by extracting image endmembers to be used with a Multiple End-member Spectral Mixture Analysis approach. The C-factor is calculated based on the fractional cover estimates determined independently for EnMAP and HyMap. Results demonstrate that with EnMAP imagery it is possible to extract quality endmember classes with important spectral features related to PV, NPV and soil, and be able to estimate relative cover fractions. This spectral information is critical to separate BS and NPV which greatly can impact the C-factor derivation. From a regional perspective, we can use EnMAP to provide good fractional cover estimates that can be integrated into soil erosion modeling.<\/jats:p>","DOI":"10.3390\/rs70911776","type":"journal-article","created":{"date-parts":[[2015,9,16]],"date-time":"2015-09-16T10:33:36Z","timestamp":1442399616000},"page":"11776-11800","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling"],"prefix":"10.3390","volume":"7","author":[{"given":"Sarah","family":"Malec","sequence":"first","affiliation":[{"name":"Department of Global Change Ecology, University of Bayreuth, Bayreuth 95440, Germany"}]},{"given":"Derek","family":"Rogge","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center, Oberpfaffenhofen D-82234, Germany"}]},{"given":"Uta","family":"Heiden","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center, Oberpfaffenhofen D-82234, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7768-6600","authenticated-orcid":false,"given":"Arturo","family":"Sanchez-Azofeifa","sequence":"additional","affiliation":[{"name":"Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada"}]},{"given":"Martin","family":"Bachmann","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center, Oberpfaffenhofen D-82234, Germany"}]},{"given":"Martin","family":"Wegmann","sequence":"additional","affiliation":[{"name":"Department of Global Change Ecology, University of Bayreuth, Bayreuth 95440, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,15]]},"reference":[{"key":"ref_1","unstructured":"Kaufmann, H., Segl, K., Chabrillat, S., Hofer, S., Stuffler, T., M\u00fcller, A., Richter, R., Schreier, G, Haydn, R, and Bach, H. (August, January 31). EnMaP a hyperspectral sensor for environmental mapping and analysis (invited paper). Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Denver, CO, USA."},{"key":"ref_2","unstructured":"Hannam, I.D., Oldeman, L.R., Pening de Vries, F.W.T., Scherr, S.J., and Sompatpanit, S. Land degradation: An overview. Responses to Land Degradation, Proceedings of the International Conference on Land Degradation and Desertification, New Dehli, India, 2001."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/S0160-4120(02)00192-7","article-title":"Soil erosion and the global carbon budget","volume":"29","author":"Lal","year":"2003","journal-title":"Environ. Int."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s00254-003-0897-8","article-title":"Soil erosion assessment and its verification using the universal soil loss equation and geographic information system: A case study at Boun, Korea","volume":"45","author":"Lee","year":"2004","journal-title":"Environ. Geol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.catena.2005.10.005","article-title":"Satellite remote sensing for water erosion assessment","volume":"65","author":"Vrieling","year":"2006","journal-title":"Catena"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s00267-014-0281-3","article-title":"Seasonality of soil erosion under Mediterranean conditions at the Alqueva dam watershed","volume":"54","author":"Ferreira","year":"2014","journal-title":"Environ. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.agee.2015.01.027","article-title":"Soil erosion in the humid tropics: A systematic quantitative review","volume":"203","author":"Locatelli","year":"2015","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_8","first-page":"418","article-title":"A universal soil-loss equation to guide conservation farm planning","volume":"1","author":"Wischmeier","year":"1968","journal-title":"Trans. Int. Congr. Soil Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1002\/(SICI)1096-9837(199806)23:6<527::AID-ESP868>3.0.CO;2-5","article-title":"The European Soil Erosion Model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments","volume":"23","author":"Morgan","year":"1998","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1191\/0309133305pp443ra","article-title":"Impact of plant root characteristics on resistance of soil to erosion by water: A review","volume":"29","author":"Gyssels","year":"2005","journal-title":"Prog. Phys. Geogr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.isprsjprs.2007.05.013","article-title":"Estimation of vegetation parameter for modeling soil erosion using spectral mixture analysis of Landsat ETM data","volume":"62","author":"Omasa","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","unstructured":"Gray, D.H., and Sotir, R.B. (1996). Biotechnical and Soil Bioengineering Slope Stabilization: A Practical Guide for Erosion Control, John Wiley and Sons."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Renard, K.G., Yoder, D.C., Lightle, D.T., and Dabney, S.M. (2011). Universal Soil Loss Equation and Revised Universal Soil Loss Equation, Blackwell Publishing Ltd.. [1st ed.].","DOI":"10.1002\/9781444328455.ch8"},{"key":"ref_14","unstructured":"Mirsal, I.A. (2008). Soil Pollution: Origin, Monitoring and Remediation, Springer."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6152","DOI":"10.1080\/01431161.2013.793872","article-title":"Monitoring of agricultural soil degradation by remote-sensing methods: A review","volume":"37","author":"Shoshanya","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0341-8162(00)00158-2","article-title":"Modelling of event-based soil erosion in Costa Rica, Nicaragua and Mexico: Evaluation of the Eurosem model","volume":"44","author":"Veihe","year":"2001","journal-title":"Catena"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/EI134.1","article-title":"Ecosystem structure throughout the brazilian amazon from landsat observations and automated spectral unmixing","volume":"9","author":"Asner","year":"2005","journal-title":"Earth Interact."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rse.2015.01.021","article-title":"Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and BS fractions from Landsat and MODIS data","volume":"161","author":"Guerschman","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.rse.2012.11.021","article-title":"Comparison of methods for estimation of absolute vegetation and soil fractional cover using MODIS normalized BRDF-adjusted reflectance","volume":"130","author":"Okin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2006.09.018","article-title":"Relative spectral mixture analysis\u2014A multitemporal index of total vegetation cover","volume":"106","author":"Okin","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1080\/01431160110115960","article-title":"Spectral unmixing of vegetation, soil and dry carbon in arid regions: Comparing multi-spectral and hyperspectral observations","volume":"23","author":"Asner","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0034-4257(00)00126-7","article-title":"A biogeophysical approach for automated SWIR unmixing of soils and vegetation","volume":"74","author":"Asner","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1080\/01431169008955129","article-title":"Visible and near infrared reflectance characteristics of dry plant materials","volume":"11","author":"Elvidge","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","first-page":"523","article-title":"Using imaging spectroscopy to study ecosystem processes and properties","volume":"54","author":"Ustin","year":"2004","journal-title":"Bio. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"S38","DOI":"10.1016\/j.rse.2008.09.019","article-title":"Using imaging spectroscopy for soil properties","volume":"113","author":"Chabrillat","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_26","first-page":"1","article-title":"Spectroscopy: An alternative to wet chemistry for soil monitoring","volume":"132","author":"Nocita","year":"2015","journal-title":"Adv. Agron."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.still.2005.11.013","article-title":"Remote sensing of crop residue cover and soil tillage intensity","volume":"91","author":"Daughtry","year":"2006","journal-title":"Soil Tillage Res."},{"key":"ref_28","first-page":"350","article-title":"Brown and green LAI mapping through spectral indices","volume":"35","author":"Delegido","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.geoderma.2010.12.018","article-title":"The use of remote sensing in soil and terrain mapping\u2014A review","volume":"162","author":"Mulder","year":"2011","journal-title":"Geoderma"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1982","DOI":"10.1007\/s11368-014-0992-3","article-title":"Assessment of sediment connectivity from vegetation cover and topography using remotely sensed data in a dryland catchment in the Spanish Pyrenees","volume":"14","author":"Wilczok","year":"2014","journal-title":"J. Soil. Sediment."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2012\/971252","article-title":"A comparison of feature-based MLR and PLS regression techniques for the prediction of three soil constituents in a degraded South African ecosystem","volume":"2012","author":"Bayer","year":"2012","journal-title":"Appl. Environ. Soil Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/S0034-4257(01)00207-3","article-title":"Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments","volume":"77","author":"Okin","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8107","DOI":"10.3390\/rs70608107","article-title":"Spatial variability mapping of crop residue using Hyperion (EO-1) hyperspectral data","volume":"7","author":"Bannari","year":"2015","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s12524-011-0143-x","article-title":"Hyperspectral satellite data in mapping salt-affected soils using linear spectral unmixing analysis","volume":"40","author":"Ghosh","year":"2012","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5145","DOI":"10.1080\/01431160903302940","article-title":"Application of Hyperion data to land degradation mapping in the Hengshan region of China","volume":"31","author":"Wu","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1109\/TGRS.2003.812908","article-title":"Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping","volume":"41","author":"Kruse","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1109\/TGRS.2003.812904","article-title":"Evaluation of the potential of Hyperion for fire danger assessment by comparison to the airborne visible\/infrared imaging spectrometer","volume":"41","author":"Roberts","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1109\/JSTARS.2013.2249496","article-title":"The earth observing one (EO-1) satellite mission: Over a decade in space","volume":"6","author":"Middleton","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"8830","DOI":"10.3390\/rs70708830","article-title":"The Environmental Mapping and Analysis Program (EnMAP) spaceborne imaging spectroscopy mission for Earth observation","volume":"7","author":"Guanter","year":"2015","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.07.021","article-title":"Synergies between VSWIR and TIR data for the urban environment: An evaluation of the potential for the hyperspectral infrared imager (HyspIRI) decadal survey mission","volume":"117","author":"Roberts","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Matsunaga, T., Iwasaki, A., Tsuchida, S., Tanii, J., Kashimura, O., Nakamura, R., Yamamoto, H., Tachikawa, T., and Rokugawa, S. (2013, January 21\u201326). Current status of Hyperspectral Imager Suite (HISUI). Peoceedings of the IEEE Geoscience and Remote Sensing Symposium, Melbourne, Australia.","DOI":"10.1109\/IGARSS.2013.6723586"},{"key":"ref_42","first-page":"522","article-title":"Eetes- the EnMAP end-to-end simulation tool","volume":"5","author":"Segl","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.rse.2014.06.024","article-title":"Mapping of NiCu\u2013PGE ore hosting ultramafic rocks using airborne and simulated EnMAP hyperspectral imagery, Nunavik, QC, Canada","volume":"152","author":"Rogge","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_44","unstructured":"(1999). Soil Taxonomy: A Basic System of Soil Classification for Making and Interpreting Soil Surveys, Natural Resources Conservation Service. [2nd ed.]. U.S. Department of Agriculture Handbook 436."},{"key":"ref_45","unstructured":"Bachmann, M., Habermeyer, M., Holzwarth, S., Richter, R., and M\u00fcller, A. (2007, January 23\u201325). Including quality measures in an automated processing chain for airborne hyperspectral data. Proceedings of the 5th EARSel Workshop on Imaging Spectroscopy, Bruges, Belgium."},{"key":"ref_46","unstructured":"Richter, R., and Schlapfer, D. (2010). Atmospheric\/Topographical Correction for Airborne Imagery: ATCOR-4 User Guide, DLR IB."},{"key":"ref_47","unstructured":"M\u00fcller, R., Lehner, M., M\u00fcller, R., Reinartz, P., Schroeder, M., and Vollmer, B. (2002, January 10\u201315). A program for direct georeferencing of airborne and spaceborne line scanner images. Proceedings of the International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences, Denver, CO, USA."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1109\/TGRS.2014.2349946","article-title":"Operational BRDF effects correction for wide-field-of-view optical scanners (BREFCOR)","volume":"53","author":"Richter","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1109\/TGRS.2008.2011616","article-title":"Simulation of the optical remote-sensing scenes with application to the EnMAP hyperspectral mission","volume":"47","author":"Guanter","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3046","DOI":"10.1109\/TGRS.2010.2042455","article-title":"Simulation of spatial sensor characteristics in the context of the EnMAP hyper-spectral mission","volume":"48","author":"Segl","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1109\/LGRS.2013.2272953","article-title":"Urban footprint processor\u2014Fully automated processing chain generating settlement masks from global data of the TanDEM-X mission","volume":"10","author":"Esch","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_52","unstructured":"Pieters, C.M., and Englert, P.A. (1993). Remote Geochemical Analysis: Elemental and Mineralogical Composition, Cambridge University Press."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1109\/JSTARS.2011.2168513","article-title":"Spatial sub-sampling using local endmembers for adapting OSP and SSEE for large-scale hyperspectral surveys","volume":"5","author":"Rogge","year":"2012","journal-title":"IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/0034-4257(94)90013-2","article-title":"How unique are spectral signatures?","volume":"49","author":"Price","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_55","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_56","unstructured":"Bachmann, M. (2007). Automated Estimation of Ground Cover Fractions Using MESMA Unmixing. [Ph.D. Thesis, University of Wuerzburg]."},{"key":"ref_57","unstructured":"Bachmann, M., M\u00fcller, A., and Dech, S. (2009, January 16\u201319). Increasing and evaluating the reliability of multiple endmember spectral mixture analysis (MESMA). Proceedings of the 6th EARSeL-SIG-IS, Tel Aviv, Israel."},{"key":"ref_58","first-page":"152","article-title":"Using airborne hyperspectral data to characterize the surface pH and mineralogy of pyrite mine tailings","volume":"32","author":"Zabcic","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinform."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/S0016-7061(98)00050-0","article-title":"Applications of fuzzy logic to the prediction of soil erosion in a large watershed","volume":"86","author":"Mitra","year":"1998","journal-title":"Geoderma"},{"key":"ref_60","unstructured":"Bakimchandra, O. (2011). Integrated Fuzzy-GIS Approach for Assessing Regional Soil Erosion Risks. [Ph.D. Thesis, University of Stuttgart]."},{"key":"ref_61","unstructured":"Wischmeier, W.H., and Smith, D.D. (1978). Predicting Rainfall Erosion Losses\u2014A Guide to Conservation Planning, U.S. Department of Agriculture. Agriculture Handbook No. 537."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.rse.2013.01.008","article-title":"Effect of image spatial and spectral characteristics on mapping semi-arid rangeland vegetation using multiple endmember spectral mixture analysis (MESMA)","volume":"132","author":"Thorp","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.rse.2014.11.009","article-title":"Extending the vegetation-impervious-soil model using simulated EnMAP data and machine learning","volume":"158","author":"Okujeni","year":"2015","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11776\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:36Z","timestamp":1760215716000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11776"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,15]]},"references-count":63,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["rs70911776"],"URL":"https:\/\/doi.org\/10.3390\/rs70911776","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2015,9,15]]}}}