{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T17:25:01Z","timestamp":1782235501064,"version":"3.54.5"},"reference-count":71,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T00:00:00Z","timestamp":1624579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0604801"],"award-info":[{"award-number":["2017YFA0604801"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Kobresia pygmaea (KP) community is a key succession stage of alpine meadow degradation on the Qinghai\u2013Tibet Plateau (QTP). However, most of the grassland classification and mapping studies have been performed at the grassland type level. The spatial distribution and impact factors of KP on the QTP are still unclear. In this study, field measurements of the grassland vegetation community in the eastern part of the QTP (Counties of Zeku, Henan and Maqu) from 2015 to 2019 were acquired using unmanned aerial vehicle (UAV) technology. The machine learning algorithms for grassland vegetation community classification were constructed by combining Gaofen satellite images and topographic indices. Then, the spatial distribution of KP community was mapped. The results showed that: (1) For all field observed sites, the alpine meadow vegetation communities demonstrated a considerable spatial heterogeneity. The traditional classification methods can hardly distinguish those communities due to the high similarity of their spectral characteristics. (2) The random forest method based on the combination of satellite vegetation indices, texture feature and topographic indices exhibited the best performance in three counties, with overall accuracy and Kappa coefficient ranged from 74.06% to 83.92% and 0.65 to 0.80, respectively. (3) As a whole, the area of KP community reached 1434.07 km2, and accounted for 7.20% of the study area. We concluded that the combination of satellite remote sensing, UAV surveying and machine learning can be used for KP classification and mapping at community level.<\/jats:p>","DOI":"10.3390\/rs13132483","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T11:07:40Z","timestamp":1624619260000},"page":"2483","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Mapping of Kobresia pygmaea Community Based on Umanned Aerial Vehicle Technology and Gaofen Remote Sensing Data in Alpine Meadow Grassland: A Case Study in Eastern of Qinghai\u2013Tibetan Plateau"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5732-0094","authenticated-orcid":false,"given":"Baoping","family":"Meng","sequence":"first","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2879-2057","authenticated-orcid":false,"given":"Zhigui","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyan","family":"Yu","sequence":"additional","affiliation":[{"name":"Qinghai Service and Guarantee Center of Qilian Mountain National Park, Xining 810001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Qin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianguo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9464-3442","authenticated-orcid":false,"given":"Jianjun","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, 12 Jiangan Road, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4285-2458","authenticated-orcid":false,"given":"Zhiwei","family":"Wang","sequence":"additional","affiliation":[{"name":"Guizhou Institute of Prataculture, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyan","family":"Lv","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4932-8237","authenticated-orcid":false,"given":"Shuhua","family":"Yi","sequence":"additional","affiliation":[{"name":"Institute of Fragile Eco-Environment, Nantong University, Nantong 226007, China"},{"name":"School of Geographic Science, Nantong University, Nantong 226007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"ref_1","unstructured":"The Editorial Committee of Vegetation Map of China, Chinese Academy of Sciences (2007). Vegetation of China and Its Geographic Pattern: Illustration of the Vegetation Map of the People\u2019s Republic of China (1:1,000,000), Geological Publishing House. (In Chinese)."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1111\/j.1654-109X.2011.01147.x","article-title":"Alpine steppe plant communities of the Tibetan highlands","volume":"14","author":"Miehe","year":"2011","journal-title":"Appl. Veg. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1071\/RJ14094","article-title":"A critical review of socioeconomic and natural factors in ecological degradation on the Qinghai-Tibetan Plateau, China","volume":"37","author":"Wang","year":"2015","journal-title":"Rangeland J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.agee.2017.10.011","article-title":"Degradation of Tibetan grasslands: Consequences for carbon and nutrient cycles","volume":"252","author":"Liu","year":"2018","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_5","first-page":"553","article-title":"System Stability and its Self-maintaining Mechanism by Grazing in Alpine Kobresia Meadow","volume":"30","author":"Cao","year":"2009","journal-title":"Chin. J. Agrometeorol."},{"key":"ref_6","unstructured":"Lin, L. (2017). Response and Adaptation of Plant-Soil System of Alpine Meadows in Different Successional Stages to Grazing Intensity. [Ph.D. Thesis, Gansu Agricultural University]."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1002\/ldr.1108","article-title":"Rangeland degradation on the Qinghai-Tibet Plateau: Implications for rehabilitation","volume":"24","author":"Li","year":"2013","journal-title":"Land Degrad. Dev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"15378","DOI":"10.1038\/ncomms15378","article-title":"Climate warming reduces the temporal stability of plant community biomass production","volume":"8","author":"Ma","year":"2017","journal-title":"Nat. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5949","DOI":"10.1002\/ece3.4099","article-title":"Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau","volume":"8","author":"Li","year":"2018","journal-title":"Ecol. Evol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.scitotenv.2018.08.164","article-title":"The Kobresia pygmaea ecosystem of the Tibetan highlands\u2014origin, functioning and degradation of the world\u2019s largest pastoral alpine ecosystem Kobresia pastures of Tibet","volume":"648","author":"Miehe","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/BF02389706","article-title":"The vegetation survey of Western Australia","volume":"30","author":"Beard","year":"1975","journal-title":"Vegetatio"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.1023\/A:1021350813586","article-title":"Regional vegetation mapping in Australia: A case study in the practical use of statistical modelling","volume":"11","author":"Cawsey","year":"2002","journal-title":"Biodivers. Conserv."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/s00267-004-0338-9","article-title":"Emergence of indigenous vegetation classifications through integration of traditional ecological knowledge and remote sensing analyses","volume":"38","author":"Naidoo","year":"2006","journal-title":"Environ. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/BF02806465","article-title":"A grid-based, satellite-image supported, multi-attributed vegetation mapping method (MTA)","volume":"42","author":"Bartha","year":"2007","journal-title":"Folia Geobot."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1016\/j.scib.2020.04.004","article-title":"An Updated Vegetation Map of China (1:1000000)","volume":"65","author":"Su","year":"2020","journal-title":"Sci. Bull."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1016\/j.patcog.2003.09.010","article-title":"Color texture classification by integrative co-occurrence matrices","volume":"37","author":"Palm","year":"2004","journal-title":"Pattern Recognit."},{"key":"ref_17","unstructured":"Pietik\u00e4inen, M., M\u00e4enp\u00e4\u00e4, T., and Viertola, J. (1999, January 14\u201315). Color texture classification with color histograms and local binary patterns. Presented at the Workshop on Texture Analysis in Machine Vision, Oulu, Finland."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2639","DOI":"10.1080\/01431161.2016.1249309","article-title":"An investigation of image processing techniques for substrate classification based on dominant grain size using rgb images from uav","volume":"38","author":"Arif","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2089","DOI":"10.3390\/rs70202089","article-title":"Comparative Analysis of GF-1 WFV, ZY-3 MUX, and HJ-1 CCD Sensor Data for Grassland Monitoring Applications","volume":"7","author":"Wang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chen, Q., Yu, R., Hao, Y., Wu, L., Zhang, W., Zhang, Q., and Bu, X. (2018). A new method for mapping aquatic vegetation especially underwater vegetation in lake ulansuhai using GF-1 satellite data. Remote Sens., 10.","DOI":"10.3390\/rs10081279"},{"key":"ref_21","first-page":"155","article-title":"Crop classification based on GF-1\/WFV NDVI time series","volume":"31","author":"Yang","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6273","DOI":"10.5194\/bg-13-6273-2016","article-title":"The burying and grazing effects of plateau pika on alpine grassland are small: A pilot study in a semiarid basin on the Qinghai-Tibet Plateau","volume":"13","author":"Yi","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.rse.2018.09.019","article-title":"Modeling alpine grassland cover based on MODIS data and support vector machine regression in the headwater region of the Huanghe River, China","volume":"218","author":"Ge","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Meng, B.P., Gao, J., Liang, T., Cui, X., Ge, J., Yin, J., Feng, Q., and Xie, H. (2018). Modeling of alpine grassland cover based on unmanned aerial vehicle technology and multi-factor methods: A case study in the east of Tibetan Plateau, China. Remote Sens., 10.","DOI":"10.3390\/rs10020320"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1016\/j.ecolind.2018.08.042","article-title":"Unmanned aerial vehicle methods makes species composition monitoring easier in grasslands","volume":"95","author":"Sun","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1080\/01431161.2016.1253898","article-title":"FragMAP: A tool for long-term and cooperative monitoring and analysis of small-scale habitat fragmentation using an unmanned aerial vehicle","volume":"38","author":"Yi","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","first-page":"1306","article-title":"Habitat environment affects the distribution of plateau pikas:A study based on an unmanned aerial vehicle","volume":"34","author":"Guo","year":"2017","journal-title":"Pratacultural Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.rse.2016.08.014","article-title":"Multi-factor modeling of above-ground biomass in alpine grassland: A case study in the Three-River Headwaters Region, China","volume":"186","author":"Liang","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2986","DOI":"10.1109\/JSTARS.2020.2999348","article-title":"Modeling Alpine Grassland Above Ground Biomass Based on Remote Sensing Data and Machine Learning Algorithm: A Case Study in East of the Tibetan Plateau, China","volume":"13","author":"Meng","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"787","DOI":"10.4028\/www.scientific.net\/AMR.955-959.787","article-title":"Crop Decision Tree Classification Extraction Based on MODIS NDVI in Beijing","volume":"955\u2013959","author":"Dong","year":"2014","journal-title":"Adv. Mater. Res."},{"key":"ref_31","first-page":"1","article-title":"Study on Ensemble Crop Information Extraction of Remote Sensing Images Based on SVM and BPNN","volume":"45","author":"Li","year":"2016","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hou, M.J., Ge, J., Gao, J.L., Meng, B.P., Li, Y.C., Yin, J.P., Liu, J., Feng, Q.S., and Liang, T.G. (2020). Ecological risk assessment and impact factor analysis of alpine wetland ecosystem based on LUCC and boosted regression tree on the Zoige Plateau, China. Remote Sens., 12.","DOI":"10.3390\/rs12030368"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s11442-006-0106-2","article-title":"The effects of land-use types and conversions on desertification in Mu Us Sandy Land of China","volume":"16","author":"Hao","year":"2006","journal-title":"J. Geogr. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1659\/MRD-JOURNAL-D-15-00064.1","article-title":"Estimating Vegetation Cover from High-Resolution Satellite Data to Assess Grassland Degradation in the Georgian Caucasus","volume":"36","author":"Wiesmair","year":"2016","journal-title":"Mt. Res. Dev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1111\/grs.12016","article-title":"Characteristics of global potential natural vegetation distribution from 1911 to 2000 based on comprehensive sequential classification system approach","volume":"59","author":"Feng","year":"2013","journal-title":"Grassl. Sci."},{"key":"ref_36","first-page":"1","article-title":"Maximum Likelihood Estimate","volume":"38","author":"Xu","year":"2013","journal-title":"Encycl. Syst. Biol."},{"key":"ref_37","unstructured":"He, Q. (2008). Neural network and its application in IR, Graduate School of Library and Information Science, Urbana-Champaign."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Vapnik, V.N. (1995). The Nature of Statistical Learning Theory, Springer.","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging predictors","volume":"24","author":"Breiman","year":"1996","journal-title":"Mach. Learn."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"11249","DOI":"10.3390\/rs70911249","article-title":"The EnMAP-Box\u2014A Toolbox and Application Programming Interface for EnMAP Data Processing","volume":"7","author":"Rabe","year":"2015","journal-title":"Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1579\/0044-7447(2008)37[272:SADOTK]2.0.CO;2","article-title":"Status and dynamics of the Kobresia pygmaea ecosystem on the Tibetan Plateau","volume":"37","author":"Miehe","year":"2008","journal-title":"Ambio"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1007\/s10021-015-9874-9","article-title":"Nitrogen uptake in an alpine Kobresia pasture on the Tibetan Plateau: Localization by 15N labeling and implications for a vulnerable ecosystem","volume":"18","author":"Schleuss","year":"2015","journal-title":"Ecosystems"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1007\/s00374-018-1280-y","article-title":"Nitrogen pools and cycles in Tibetan Kobresia pastures depending on grazing","volume":"54","author":"Sun","year":"2018","journal-title":"Biol. Fertil. Soils"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"6633","DOI":"10.5194\/bg-11-6633-2014","article-title":"Pasture degradation modifies the water and carbon cycles of the Tibetan highlands","volume":"11","author":"Babel","year":"2014","journal-title":"Biogeosciences"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2322","DOI":"10.1111\/j.1365-2486.2009.02069.x","article-title":"Partitioning pattern of carbon flux in a Kobresia grassland on the Qinghai-Tibetan Plateau revealed by field 13C pulse-labeling","volume":"16","author":"Wu","year":"2010","journal-title":"Glob. Chang. Biol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1111\/j.1365-2486.2011.02557.x","article-title":"Effect of grazing on carbon stocks and assimilate partitioning in a Tibetan montane pasture revealed by 13CO2 pulse labeling","volume":"18","author":"Hafner","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1016\/j.scitotenv.2014.10.082","article-title":"Carbon pools and fluxes in a Tibetan alpine Kobresia pygmaea pasture partitioned by coupled eddy-covariance measurements and 13CO2 pulse labeling","volume":"505","author":"Ingrisch","year":"2015","journal-title":"Sci. Total Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.epsl.2016.09.031","article-title":"Late Quaternary climate, precipitation 18O, and Indian monsoon variations over the Tibetan Plateau","volume":"457","author":"Li","year":"2016","journal-title":"Earth Planet. Sci. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"20985","DOI":"10.1038\/srep20985","article-title":"Leaf unfolding of Tibetan alpine meadows captures the arrival of monsoon rainfall","volume":"6","author":"Li","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_52","first-page":"282","article-title":"Environmental changes in the pastures of Xizang","volume":"135","author":"Miehe","year":"2000","journal-title":"Marbg. Geogr. Schr."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"24367","DOI":"10.1038\/srep24367","article-title":"Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures","volume":"6","author":"Lehnert","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1111\/avsc.12312","article-title":"Combined effects of livestock grazing and abiotic environment on vegetation and soils of grasslands across Tibet","volume":"20","author":"Wang","year":"2017","journal-title":"Appl. Veg. Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1002\/ldr.3312","article-title":"Overgrazing leads to soil cracking that later triggers the severe degradation of alpine meadows on the Tibetan Plateau","volume":"30","author":"Niu","year":"2019","journal-title":"Land Degrad. Dev."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1111\/j.1744-697X.2005.00028.x","article-title":"Alpine grassland degradation and its control in the source region of the Yangtze and Yellow Rivers, China","volume":"51","author":"Zhou","year":"2005","journal-title":"Grassl. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1038\/s41559-019-0972-5","article-title":"A checklist for maximizing reproducibility of ecologicla niche model","volume":"3","author":"Feng","year":"2019","journal-title":"Nat. Ecol. Evol."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Pedrotti, F. (2013). Plant and Vegetation Mapping, Springer.","DOI":"10.1007\/978-3-642-30235-0"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1109\/JSTARS.2010.2049001","article-title":"Classification of Grassland Types by MODIS Time-Series Images in Tibet, China","volume":"3","author":"Wen","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s11629-016-3929-z","article-title":"Quantifying land degradation in the Zoige Basin, NE Tibetan Plateau using satellite remote sensing data","volume":"14","author":"Yu","year":"2017","journal-title":"J. Mt. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"145644","DOI":"10.1016\/j.scitotenv.2021.145644","article-title":"Grassland type-dependent spatiotemporal characteristics of productivity in Inner Mongolia and its response to climate factors","volume":"775","author":"Guo","year":"2021","journal-title":"Sci. Total. Environ."},{"key":"ref_62","first-page":"e01517","article-title":"Using UAVs to assess the relationship between alpine meadow bare patches and disturbance by pikas in the source region of Yellow River on the Qinghai-Tibetan Plateau","volume":"26","author":"Zhang","year":"2021","journal-title":"Glob. Ecol. Conserv."},{"key":"ref_63","unstructured":"Ma, W.W. (2015). Study on Methods for Grassland Classification and Quality Estimation by Remote Sensing: A Case Study in the Region around Qinghai Lake, Chinese Academy of Science."},{"key":"ref_64","first-page":"5","article-title":"Improved Classification of Forest Vegetation in Northern Wisconsin Through a Rule-Based Combination of Soils, Terrain, and Landsat Thematic Mapper Data","volume":"1","author":"Bolstad","year":"1992","journal-title":"For. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1080\/01431168708948683","article-title":"Fast maximum-likelihood class-ification of remotely sensed imagery","volume":"8","author":"Settle","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1109\/TGRS.2005.848706","article-title":"An adaptive fuzzy evidential nearest neighbor formulation for classifying remote sensing images","volume":"43","author":"Zhu","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"a8","DOI":"10.1255\/jsi.2020.a8","article-title":"Comprehensive review on land use\/land cover change classification in remote sensing","volume":"9","author":"Navin","year":"2020","journal-title":"J. Spectr. Imaging."},{"key":"ref_68","first-page":"24","article-title":"Mapping zoige alpine wetland using random forest classification and landsat 5 TM data","volume":"4","author":"Jiang","year":"2016","journal-title":"Stud. Surv. Mapp. Sci. (SSMS)"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.5194\/isprs-archives-XLII-3-1415-2018","article-title":"Method of grassland information extraction based on multi-level segmentation and cart model","volume":"XLII-3","author":"Qiao","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2829","DOI":"10.1007\/s11227-020-03377-w","article-title":"Multi-spectral remote sensing land-cover classification based on deep learning methods","volume":"77","author":"He","year":"2020","journal-title":"J. Supercomput."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Yuan, H., Yang, G., Li, C., Wang, Y., Liu, J., Yu, H., Feng, H., Xu, B., Zhao, X., and Yang, X. (2017). Retrieving Soybean Leaf Area Index from Unmanned Aerial Vehicle Hyperspectral Remote Sensing: Analysis of RF, ANN, and SVM Regression Models. Remote Sens., 9.","DOI":"10.3390\/rs9040309"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/13\/2483\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:23:58Z","timestamp":1760163838000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/13\/2483"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,25]]},"references-count":71,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13132483"],"URL":"https:\/\/doi.org\/10.3390\/rs13132483","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,25]]}}}