{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:27:00Z","timestamp":1760243220385,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2014,3,12]],"date-time":"2014-03-12T00:00:00Z","timestamp":1394582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study was designed to estimate the canopy biophysical characteristics of semi-arid grassland ecosystems by using in situ field spectrometry measurements to identify important spectral information for predictions at broader spatial scales. Spectral vegetation indices (VIs), reflectance spectra, continuum removal spectra, and the amplitude of the red edge peak (drre) based on 61 well-replicated field measurements across a large area in Inner Mongolia were used to develop empirical models for estimating four key canopy biophysical features: percent green coverage (PGC), canopy height (H), green aboveground biomass (GBM), and total aboveground biomass (TBM). The results showed that NDVI, EVI, NDSVI, and LSWI were useful for estimating canopy biophysical features, with NDSVI being the most significant variable. The PGC was accurately estimated with spectral reflectance at 441 nm and 2220 nm (R2 = 0.71), while the maximum depth of band (Dc), absorption area (Darea) in the red domain and drre were selected for estimating TBM and GBM (R2 = 0.51 and 0.44). Among the four canopy features, PGC received the highest confidence from all of the models (R2 = 0.81), while H was the most difficult to estimate (R2 = 0.49). Finally, the degree of disturbances and ecosystem types appeared to be a significant variable for model development.<\/jats:p>","DOI":"10.3390\/rs6032239","type":"journal-article","created":{"date-parts":[[2014,3,12]],"date-time":"2014-03-12T07:14:58Z","timestamp":1394608498000},"page":"2239-2254","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Estimating Canopy Characteristics of Inner Mongolia\u2019s Grasslands from Field Spectrometry"],"prefix":"10.3390","volume":"6","author":[{"given":"Feng","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany,  Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ranjeet","family":"John","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangsheng","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany,  Chinese Academy of Sciences, Beijing 100093, China"},{"name":"Chinese Academy of Meteorological Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changliang","family":"Shao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany,  Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiquan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA"},{"name":"International Center for Ecology, Meteorology and Environment, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,3,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1029\/93GB02725","article-title":"Terrestrial ecosystem production: A process model based on global satellite and surface data","volume":"7","author":"Potter","year":"1993","journal-title":"Glob. Biogeochem. Cy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1175\/1520-0442(1996)009<0676:ARLSPF>2.0.CO;2","article-title":"A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation","volume":"9","author":"Sellers","year":"1996","journal-title":"J. Clim"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1111\/j.1365-2486.2004.00740.x","article-title":"Vegetation structure characteristics and relationships of Kalahari woodlands and savannas","volume":"10","author":"Privette","year":"2004","journal-title":"Glob. Chang. Biol"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/0034-4257(94)00071-T","article-title":"Status of remote sensing algorithms for estimation of land-surface state parameters","volume":"51","author":"Hall","year":"1995","journal-title":"Remote Sens. Environ"},{"key":"ref_5","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_6","doi-asserted-by":"crossref","unstructured":"Goetz, A.F.H. (1995). Imaging spectrometry for remote sensing: Vision to reality in 15 Years. Proc. SPIE, 2480.","DOI":"10.1117\/12.210867"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/S0034-4257(02)00196-7","article-title":"Spectral discrimination of vegetation types in a coastal wetland","volume":"85","author":"Schmidt","year":"2003","journal-title":"Remote Sens. Environ"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/S0034-4257(98)00014-5","article-title":"Biophysical and biochemical sources of variability in canopy reflectance","volume":"64","author":"Asner","year":"1998","journal-title":"Remote Sens. Environ"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/S0034-4257(70)80021-9","article-title":"Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation","volume":"1","author":"Knipling","year":"1970","journal-title":"Remote Sens. Environ"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0034-4257(98)00035-2","article-title":"Determining forest species composition using high spectral resolution remote sensing data","volume":"65","author":"Martin","year":"1998","journal-title":"Remote Sens. Environ"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3999","DOI":"10.1080\/01431160310001654923","article-title":"Narrow band vegetation indices overcome the saturation problem in biomass estimation","volume":"25","author":"Mutanga","year":"2004","journal-title":"Int. J. Remote Sens"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/S0034-4257(98)00013-3","article-title":"Processing of high spectral resolution reflectance data for the retrieval of canopy water content information","volume":"65","author":"Rollin","year":"1998","journal-title":"Remote Sens. Environ"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0034-4257(00)00124-3","article-title":"Impact of tissue, canopy, and landscape factors on the hyperspectral reflectance variability of arid ecosystems","volume":"74","author":"Asner","year":"2000","journal-title":"Remote Sens. Environ"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.rse.2003.11.001","article-title":"Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features","volume":"89","author":"Mutanga","year":"2004","journal-title":"Remote Sens. Environ"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.agrformet.2012.03.010","article-title":"Estimating senesced biomass of desert steppe in Inner Mongolia using field spectrometric data","volume":"161","author":"Ren","year":"2012","journal-title":"Agric. For. Meteorol"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Ren, H., Zhou, G., Zhang, F., and Zhang, X. (2012). Evaluating cellulose absorption index (CAI) for non-photosynthetic biomass estimation in the desert steppe of Inner Mongolia. Chin. Sci. Bull, 57.","DOI":"10.1007\/s11434-012-5016-3"},{"key":"ref_17","unstructured":"Gausman, H.W. (1985). Plant Leaf Optical Properties in Visible and Near Infrared Light, Texas Technical Press. Graduate Studies, Texas Tech University (No. 29)."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1002\/j.1537-2197.1993.tb13796.x","article-title":"Responses of leaf spectral reflectance to plant stress","volume":"80","author":"Carter","year":"1993","journal-title":"Am. J. Bot"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1080\/01431169408954109","article-title":"Ratios of leaf reflectances in narrow wavebands as indicators of plant stress","volume":"15","author":"Carter","year":"1994","journal-title":"Int. J. Remote Sens"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s004680050157","article-title":"Spectral changes with leaf aging in Amazon caatinga","volume":"12","author":"Roberts","year":"1998","journal-title":"Trees"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1109\/36.934079","article-title":"Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California","volume":"39","author":"Garcia","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.rse.2004.06.002","article-title":"Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks","volume":"92","author":"Smith","year":"2004","journal-title":"Remote Sens. Environ"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"De Paul Obade, V., Lal, V.R., and Chen, J. (2013). Remote sensing of soil and water quality in agroecosystems. Water Air Soil Pollut, 224.","DOI":"10.1007\/s11270-013-1658-2"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"John, R., Chen, J., Lu, N., and Wilske, B. (2009). Land cover \/land use change and their ecological consequences. Environ. Res. Lett, 4.","DOI":"10.1088\/1748-9326\/4\/4\/045010"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"John, R., Chen, J., Ou-Yang, Z.-T., Xiao, J., Becker, R., Samanta, A., Ganguly, S., Yuan, W., and Batkhishig, O. (2013). Vegetation response to extreme climate events on the Mongolian Plateau from 2000 to 2010. Environ. Res. Lett, 8.","DOI":"10.1088\/1748-9326\/8\/3\/035033"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Qi, J., Chen, J., Wan, S., and Ai, L. (2012). Understanding the coupled natural and human systems in Dryland East Asia. Environ. Res. Lett, 7.","DOI":"10.1088\/1748-9326\/7\/1\/015202"},{"key":"ref_27","unstructured":"(1988). Explanation of Series Resources Maps of Inner Mongolia Autonomous Region, Science Press."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least square procedure","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem"},{"key":"ref_29","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W. (1973). Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation, Remote Sensing Center, Texas A&M University. Progress Report RSC 1978-1."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices global set of TM images for EOSMODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1029\/2002EO000411","article-title":"Improved rangeland information from satellites for land cover change studies in the Southwest","volume":"83","author":"Qi","year":"2002","journal-title":"EOS Trans. AGU"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3583","DOI":"10.1080\/014311697216810","article-title":"The modified normalized difference vegetation index (mNDVI)\u2014A new index to determine frost damages in agriculture based on Landsat TM data","volume":"18","author":"Jurgens","year":"1997","journal-title":"Int. J. Remote Sens"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1016\/j.rse.2004.12.009","article-title":"Mapping paddy rice agriculture in southern China using multi-temporal MODIS images","volume":"95","author":"Xiao","year":"2005","journal-title":"Remote Sens. Environ"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1080\/01431169408954177","article-title":"The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric","volume":"15","author":"Filella","year":"1994","journal-title":"Int. J. Remote Sens"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1029\/JB089iB07p06329","article-title":"Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications","volume":"89","author":"Clark","year":"1984","journal-title":"J. Geophys. Res"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0034-4257(98)00084-4","article-title":"Spectroscopic determination of leaf biochemistry using optical band-depth analysis of absorption features and stepwise multiple linear regression","volume":"67","author":"Kokaly","year":"1999","journal-title":"Remote Sens. Environ"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/S0034-4257(01)00182-1","article-title":"Estimating the foliar biochemical concentration of leaves with reflectance spectrometry testing the Kokaly and Clark methodologies","volume":"76","author":"Curran","year":"2001","journal-title":"Remote Sens. Environ"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1016\/j.isprsjprs.2011.09.013","article-title":"Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models","volume":"66","author":"Darvishzadeh","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.compag.2010.05.006","article-title":"Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat","volume":"73","author":"Atzberger","year":"2010","journal-title":"Comput. Electron. Agr"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Richter, K., Atzberger, C., Hank, T.B., and Mauser, W. (2012). Derivation of biophysical variables from earth observation data: Validation and statistical measures. J. Appl. Remote Sens, 6.","DOI":"10.1117\/1.JRS.6.063557"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S0034-4257(02)00018-4","article-title":"Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture","volume":"81","author":"Haboudane","year":"2002","journal-title":"Remote Sens. Environ"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1177\/030913339902300303","article-title":"Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems","volume":"23","author":"Treitz","year":"1999","journal-title":"Prog. Phys. Geogr"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1093\/jpe\/rtq035","article-title":"Evapotranspiration and soil water relationships in a range of disturbed and undisturbed ecosystems in the semi-arid Inner Mongolia, China","volume":"4","author":"Lu","year":"2011","journal-title":"J. Plant Ecol"},{"key":"ref_44","unstructured":"Clevers, J., and Buker, C. (1991, January 14\u201318). Feasibility of the red edge index for the detection of nitrogen deficiency. Noordwijk, The Netherlands. ESA SP-319."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.rse.2005.12.011","article-title":"A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method","volume":"101","author":"Cho","year":"2006","journal-title":"Remote Sens. Environ"},{"key":"ref_46","first-page":"388","article-title":"Using spectral information from the NIR water absorption features for the retrieval of canopy water content","volume":"10","author":"Clevers","year":"2008","journal-title":"Int. J. Appl. Earth Obs"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"6199","DOI":"10.1080\/01431160902842342","article-title":"Leaf Area Index derivation from hyperspectral vegetation indices and the red edge position","volume":"30","author":"Darvishzadeh","year":"2009","journal-title":"Int. J. Remote Sens"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.biosystemseng.2011.05.004","article-title":"Estimation of green aboveground biomass of desert steppe in Inner Mongolia based on red-edge reflectance curve area method","volume":"109","author":"Ren","year":"2011","journal-title":"Biosyst. Eng"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2249","DOI":"10.1080\/014311699212236","article-title":"Spectral features associated with nitrogen, phosphorous, and potassium deficiencies in Eucalyptus saligna seedling leaves","volume":"20","author":"Ponzoni","year":"1999","journal-title":"Int. J. Remote Sens"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/S0034-4257(03)00096-8","article-title":"Mapping nonnative plants using hyper spectral imagery","volume":"86","author":"Underwood","year":"2003","journal-title":"Remote Sens. Environ"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2592","DOI":"10.1016\/j.rse.2007.12.003","article-title":"Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland","volume":"112","author":"Darvishzadeh","year":"2008","journal-title":"Remote Sens. Environ"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.ecolmodel.2007.01.022","article-title":"Adaptation of a grazing gradient concept to heterogeneous Mediterranean rangelands using cost surface modelling","volume":"204","author":"Kuemmerle","year":"2007","journal-title":"Ecol. Model"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.isprsjprs.2008.01.001","article-title":"LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements","volume":"63","author":"Darvishzadeh","year":"2008","journal-title":"ISPRS J. Photogramm. Remote Sens"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/3\/2239\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:09:09Z","timestamp":1760216949000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/3\/2239"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,3,12]]},"references-count":53,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2014,3]]}},"alternative-id":["rs6032239"],"URL":"https:\/\/doi.org\/10.3390\/rs6032239","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2014,3,12]]}}}