{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T14:21:27Z","timestamp":1782742887422,"version":"3.54.5"},"reference-count":60,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T00:00:00Z","timestamp":1730505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Department of Tibet Key Project","award":["XZ202201ZY0003G"],"award-info":[{"award-number":["XZ202201ZY0003G"]}]},{"name":"Science and Technology Department of Tibet Key Project","award":["18ZA0047"],"award-info":[{"award-number":["18ZA0047"]}]},{"name":"Sichuan Education Department Natural Science Key Project","award":["XZ202201ZY0003G"],"award-info":[{"award-number":["XZ202201ZY0003G"]}]},{"name":"Sichuan Education Department Natural Science Key Project","award":["18ZA0047"],"award-info":[{"award-number":["18ZA0047"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The ecosystem of the Qinghai\u2013Tibet Plateau is highly fragile due to its unique geographical conditions, with vegetation playing a crucial role in maintaining ecological balance. Thus, accurately monitoring the distribution of vegetation in the plateau region is of paramount importance. This study employs UAV multispectral imagery in combination with four machine-learning models\u2014Support Vector Machine (SVM), Decision Tree (DT), Extreme Gradient Boosting (XGBoost), and Random Forest (RF)\u2014to investigate the impact of different features and their combinations on the fine classification of shrubs and grasses on the Qinghai\u2013Tibet Plateau, including Salix psammophila, Populus simonii Carri\u00e8re, Kobresia tibetica, and Kobresia pygmaea. The results indicate that near-infrared spectral information can improve classification accuracy, with improvements of 5.21%, 1.65%, 6.64%, and 5.03% for Salix psammophila, Populus simonii Carri\u00e8re, Kobresia tibetica, and Kobresia pygmaea, respectively. Feature selection effectively reduces redundant information and enhances model classification accuracy, with all four machine-learning models achieving the best performance on the optimized feature set. Furthermore, the RF model performs best on the optimized feature set, achieving an overall accuracy (OA) of 95.32% and a kappa coefficient of 0.94. This study provides important scientific support for the fine classification and ecological monitoring of plateau vegetation.<\/jats:p>","DOI":"10.3390\/rs16214106","type":"journal-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T09:52:54Z","timestamp":1730713974000},"page":"4106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Study on the Classification of Shrubs and Grasses on the Tibetan Plateau Based on Unmanned Aerial Vehicle Multispectral Imagery"],"prefix":"10.3390","volume":"16","author":[{"given":"Xiaoqiang","family":"Chen","sequence":"first","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1283-438X","authenticated-orcid":false,"given":"Hui","family":"Deng","sequence":"additional","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3268-8749","authenticated-orcid":false,"given":"Houxi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,2]]},"reference":[{"key":"ref_1","first-page":"2504","article-title":"Responses of vegetation and soil characterisitics to degraded grassland under different degrees on the Qinghai-Tibet Plateau","volume":"44","author":"Du","year":"2024","journal-title":"Acta Ecol. Sin."},{"key":"ref_2","first-page":"6","article-title":"Quantitative characteristics of timberline vegetation on Mt. Shergyla, Tibet","volume":"33","author":"Yang","year":"2011","journal-title":"J. Beijing For. Univ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.5194\/hess-26-1089-2022","article-title":"The importance of vegetation in understanding terrestrial water storage variations","volume":"26","author":"Trautmann","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sang, J., Song, C., Jia, N., Jia, Y., Liu, C., Qiao, X., Zhang, L., Yuan, W., Wu, D., and Li, L. (2023). Vegetation survey and mapping on the Qinghai-Tibet Plateau. Biodivers. Sci., 31.","DOI":"10.17520\/biods.2022430"},{"key":"ref_5","first-page":"2955","article-title":"The differences of vegetation characteristics and environmental conditions among main vegetation types on the Qinghai-Tibet Plateau","volume":"44","author":"Zhang","year":"2024","journal-title":"Acta Ecol. Sin."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.ecoleng.2018.11.018","article-title":"Challenging the land degradation in China\u2019s Loess Plateau: Benefits, limitations, sustainability, and adaptive strategies of soil and water conservation","volume":"127","author":"Jiang","year":"2019","journal-title":"Ecol. Eng."},{"key":"ref_7","first-page":"2852","article-title":"Fine classification of urban vegetation based on UAV images","volume":"42","author":"Lin","year":"2022","journal-title":"China Environ. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"101213","DOI":"10.1016\/j.ecoinf.2021.101213","article-title":"Identification of plant species in an alpine steppe of Northern Tibet using close-range hyperspectral imagery","volume":"61","author":"Liu","year":"2021","journal-title":"Ecol. Inform."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1093\/jpe\/rtv077","article-title":"Observer error in vegetation surveys: A review","volume":"9","author":"Morrison","year":"2016","journal-title":"J. Plant Ecol."},{"key":"ref_10","first-page":"18","article-title":"The Vegetation Classification Research of North Tibetan Plateau Based on MODIS","volume":"30","author":"Laba","year":"2010","journal-title":"Plateau Mt. Meteorol. Res."},{"key":"ref_11","first-page":"816","article-title":"A new vegetation map for Qinghai-Tibet Plateau by integrated classification from multi-source data products","volume":"57","author":"Zhang","year":"2021","journal-title":"J. Beijing Norm. Univ."},{"key":"ref_12","first-page":"48","article-title":"Urban Tree Species Classification by UAV Visible Light Imagery and OBIA-RF Model","volume":"52","author":"Chen","year":"2024","journal-title":"J. Northeast. For. Univ."},{"key":"ref_13","first-page":"1862","article-title":"Classification of geological features in agricultural parks based on multispectral remote sensing by unmanned aerial vehicle","volume":"39","author":"Song","year":"2023","journal-title":"Jiangsu J. Agric. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1007\/s40789-019-00264-5","article-title":"A review of UAV monitoring in mining areas: Current status and future perspectives","volume":"6","author":"He","year":"2019","journal-title":"Int. J. Coal Sci. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2017.07.007","article-title":"Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak","volume":"131","author":"Dash","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","first-page":"185","article-title":"Classification of Slope Plant Species Based on Image of UAV","volume":"35","author":"Zhai","year":"2020","journal-title":"J. Northwest For. Univ."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhang, Z., and Zhu, L. (2023). A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications. Drones, 7.","DOI":"10.3390\/drones7060398"},{"key":"ref_18","first-page":"225","article-title":"Extraction of urban impervious surface based on the visible images of UAV and OBIA-RF algorithm","volume":"38","author":"Ye","year":"2022","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_19","first-page":"588","article-title":"Crop Classification Method from UAV Images based on Object-Oriented Multi-feature Learning","volume":"38","author":"Jin","year":"2023","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"107822","DOI":"10.1016\/j.compag.2023.107822","article-title":"A comparison between Pixel-based deep learning and Object-based image analysis (OBIA) for individual detection of cabbage plants based on UAV Visible-light images","volume":"209","author":"Ye","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Huang, Y., Lu, C., Jia, M., Wang, Z., Su, Y., and Su, Y. (2023). Plant species classification of coastal wetlands based on UAV images and object-oriented deep learning. Biodivers. Sci., 31.","DOI":"10.17520\/biods.2022411"},{"key":"ref_22","first-page":"1","article-title":"Vegetation classification of UAV remote sensing images in desert steppe based on object-oriented technology","volume":"33","author":"She","year":"2024","journal-title":"Acta Prataculturae Sin."},{"key":"ref_23","first-page":"1295","article-title":"Object-Based Karst Wetland Vegetation Classification Method Using Unmanned Aerial Vehicle images and Random ForestAlgorithm","volume":"21","author":"Geng","year":"2019","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_24","first-page":"37","article-title":"Identification of typical species in desert steppe based on unmannedaerialvehicle multispectral images","volume":"34","author":"Na","year":"2022","journal-title":"China Agric. Inform."},{"key":"ref_25","first-page":"6","article-title":"Information extraction of urban green space based on UAV remote sensing image","volume":"42","author":"Yang","year":"2017","journal-title":"Sci. Surv. Mapp."},{"key":"ref_26","first-page":"6","article-title":"A Study on TWINSPAN Classification of Meadow Plants in Lazi County, Tibet","volume":"26","author":"Li","year":"2004","journal-title":"Acta Agric. Univ. Jiangxiensis"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.neucom.2019.10.118","article-title":"A comprehensive survey on support vector machine classification: Applications, challenges and trends","volume":"408","author":"Cervantes","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4765","DOI":"10.1007\/s10462-022-10275-5","article-title":"Recent advances in decision trees: An updated survey","volume":"56","author":"Costa","year":"2023","journal-title":"Artif. Intell. Rev."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_31","first-page":"74","article-title":"Classifications of Tree Species Based on UAV\u2013s Visible Light Images and Object-Oriented Method","volume":"37","author":"Wen","year":"2022","journal-title":"J. Northwest For. Univ."},{"key":"ref_32","first-page":"163","article-title":"Study on Machine Learning Methods for Vegetation Classification in Typical Humid Mountainous Areas of South China based on the UAV Multispectral Remote Sensing","volume":"38","author":"Zhang","year":"2023","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1618","DOI":"10.1007\/s11629-022-7333-6","article-title":"Early landslide mapping with slope units division and multi-scale objectbased image analysis\u2014A case study in the Xiansh.ui River basin of Sichuan, China","volume":"19","author":"Gao","year":"2022","journal-title":"J. Mt. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"112645","DOI":"10.1016\/j.ecolind.2024.112645","article-title":"Moderate Red-Edge vegetation index for High-Resolution multispectral remote sensing images in urban areas","volume":"167","author":"Li","year":"2024","journal-title":"Ecol. Indic."},{"key":"ref_36","first-page":"232","article-title":"Extraction Method of Summer Corn Vegetation Coverage Based on Visible Light Image of Unmanned Aerial Vehicle","volume":"50","author":"Zhao","year":"2019","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_37","first-page":"152","article-title":"Extraction of vegetation information from visible unmanned aerial vehicle images","volume":"31","author":"Wang","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_38","first-page":"504","article-title":"Research on vegetation index of small watershed in the Loess Plateau based on visible light image analysis","volume":"43","author":"He","year":"2022","journal-title":"Res. Agric. Mod."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Feng, C., Zhang, W., Deng, H., Dong, L., Zhang, H., and Zhao, Z. (2023). A Combination of OBIA and Random Forest Based on Visible UAV Remote Sensing for Accurately Extracted Information about Weeds in Areas with Different Weed Densities in Farmland. Remote Sens., 15.","DOI":"10.3390\/rs15194696"},{"key":"ref_40","unstructured":"Baret, F., Guyot, G., and Major, D.J. (1989, January 10\u201314). TSAVI: A vegetation index which minimizes soil brightness effects on LAI and APAR estimation. Proceedings of the 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada."},{"key":"ref_41","first-page":"13","article-title":"Review of 54 Vegetation Indices","volume":"51","author":"Ao","year":"2023","journal-title":"J. Anhui Agric. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1399","DOI":"10.1109\/36.843034","article-title":"Evaluation of sensor calibration uncertainties on vegetation indices for MODIS","volume":"38","author":"Miura","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/0034-4257(92)90132-4","article-title":"Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies","volume":"39","author":"Daughtry","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1353691","DOI":"10.1155\/2017\/1353691","article-title":"Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications","volume":"2017","author":"Xue","year":"2017","journal-title":"J. Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"102728","DOI":"10.1016\/j.ecoinf.2024.102728","article-title":"Disentangling disturbances with nested hierarchy classification of Mediterranean garrigue\/maquis shrub community compositions through remote sensing and GIS","volume":"82","author":"Manspeizer","year":"2024","journal-title":"Ecol. Inform."},{"key":"ref_46","first-page":"11","article-title":"Vegetation information classification method considering UAV image point cloud characteristics","volume":"41","author":"Li","year":"2022","journal-title":"Ecol. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"14959","DOI":"10.1007\/s11042-020-08851-4","article-title":"Offline Signature Verification System: A Novel Technique of Fusion of GLCM and Geometric Features using SVM","volume":"83","author":"Batool","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"8975","DOI":"10.1109\/ACCESS.2018.2890743","article-title":"Texture Feature Extraction Methods: A Survey","volume":"7","year":"2019","journal-title":"IEEE Access"},{"key":"ref_49","first-page":"1","article-title":"Identification of rodent hole patches in desert grasslands using UAV imagery and OBIA-CFS algorithms","volume":"41","author":"Qi","year":"2024","journal-title":"Pratacultural Sci."},{"key":"ref_50","first-page":"95","article-title":"Remote sensing information extraction for mangrove forests based on multi-feature parameters: A case study of Guangdong Province","volume":"36","author":"Wang","year":"2024","journal-title":"Remote Sens. Nat. Resour."},{"key":"ref_51","first-page":"69","article-title":"Desert Vegetation Classification Based on Object-oriented UAV Remote Sensing Images","volume":"23","author":"Zhang","year":"2021","journal-title":"J. Agric. Sci. Technol."},{"key":"ref_52","first-page":"1401","article-title":"Remote sensing parameters optimization for accurate land cover classification","volume":"53","author":"Chen","year":"2024","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"9","DOI":"10.12677\/GST.2020.81002","article-title":"Object-Oriented Land Cover Classification Using High Spatial Resolution Remote Sensing","volume":"8","author":"Zhou","year":"2020","journal-title":"Geomat. Sci. Technol."},{"key":"ref_54","first-page":"1688","article-title":"Identification of rice in Shangxing Town, Liyang City based on Sentinel image and multi-feature optimization","volume":"39","author":"Zhong","year":"2023","journal-title":"Jiangsu J. Agric. Sci."},{"key":"ref_55","first-page":"1670","article-title":"Monitoring Wheat Lodging Based on UAV Multi-Spectral Image Feature Fusion","volume":"56","author":"Wei","year":"2023","journal-title":"Sci. Agric. Sin."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"108651","DOI":"10.1016\/j.knosys.2022.108651","article-title":"ConfusionVis: Comparative evaluation and selection of multi-class classifiers based on confusion matrices","volume":"247","author":"Theissler","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"106734","DOI":"10.1016\/j.compag.2022.106734","article-title":"Weakly-supervised learning to automatically count cotton flowers from aerial imagery","volume":"194","author":"Petti","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_58","first-page":"1598","article-title":"Bi-Directional Reflection Characteristic of Vegetation Leaf Measured by Hyperspectral LiDAR and Its Impact on Chlorophyll Content Estimation","volume":"43","author":"Bai","year":"2023","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_59","first-page":"118","article-title":"Review on Application of Near Infrared Spectroscopy in Plant Leaves","volume":"36","author":"Wu","year":"2020","journal-title":"For. Environ. Sci."},{"key":"ref_60","first-page":"275","article-title":"Remote sensing monitoring of non-agriculturalization in typical areas of the Northern Xinjiang of China based on feature optimization","volume":"40","author":"Cao","year":"2024","journal-title":"Trans. Chin. Soc. Agric. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/21\/4106\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:27:31Z","timestamp":1760113651000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/21\/4106"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,2]]},"references-count":60,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["rs16214106"],"URL":"https:\/\/doi.org\/10.3390\/rs16214106","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,2]]}}}