{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T16:15:54Z","timestamp":1740154554243,"version":"3.37.3"},"reference-count":57,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,23]],"date-time":"2022-03-23T00:00:00Z","timestamp":1647993600000},"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":"Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60%\u20134.68% when the temperature increased by 1.5 \u00b0C, while it only changed by 0.06%\u20130.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau.<\/jats:p>","DOI":"10.3390\/rs14071556","type":"journal-article","created":{"date-parts":[[2022,3,24]],"date-time":"2022-03-24T02:08:06Z","timestamp":1648087686000},"page":"1556","source":"Crossref","is-referenced-by-count":9,"title":["Assessing the Sensitivity of Vegetation Cover to Climate Change in the Yarlung Zangbo River Basin Using Machine Learning Algorithms"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1614-2831","authenticated-orcid":false,"given":"Lizhuang","family":"Cui","sequence":"first","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]},{"given":"Bo","family":"Pang","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0278-502X","authenticated-orcid":false,"given":"Gang","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"},{"name":"School of Geographical Science, University of Bristol, Bristol BS8 1SS, UK"}]},{"given":"Chunguang","family":"Ban","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]},{"given":"Meifang","family":"Ren","sequence":"additional","affiliation":[{"name":"China Academy of Urban Planning & Design, Beijing 100044, China"},{"name":"Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2118-5174","authenticated-orcid":false,"given":"Dingzhi","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]},{"given":"Depeng","family":"Zuo","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0579-608X","authenticated-orcid":false,"given":"Zhongfan","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.gloenvcha.2006.02.002","article-title":"NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China","volume":"16","author":"Piao","year":"2006","journal-title":"Glob. Environ. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3667","DOI":"10.1007\/s11269-017-1692-8","article-title":"A case study on a combination NDVI forecasting model based on the entropy weight method","volume":"31","author":"Huang","year":"2017","journal-title":"Water Resour. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"105667","DOI":"10.1016\/j.catena.2021.105667","article-title":"Forest soil nutrient stocks along altitudinal range of Uttarakhand Himalayas: An aid to Nature Based Climate Solutions","volume":"207","author":"Kumar","year":"2021","journal-title":"Catena"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4093","DOI":"10.1073\/pnas.1720712115","article-title":"Critical impact of vegetation physiology on the continental hydrologic cycle in response to increasing CO2","volume":"115","author":"Lemordant","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3520","DOI":"10.1111\/gcb.12945","article-title":"Time-lag effects of global vegetation responses to climate change","volume":"21","author":"Wu","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1038\/nature16986","article-title":"Sensitivity of global terrestrial ecosystems to climate variability","volume":"531","author":"Seddon","year":"2016","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wei, X., Wang, N., Luo, P., Yang, J., Zhang, J., and Lin, K. (2021). Spatiotemporal assessment of land marketization and its driving forces for sustainable Urban\u2013Rural development in Shaanxi Province in China. Sustainability, 13.","DOI":"10.3390\/su13147755"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1007\/s13280-021-01654-3","article-title":"Exploring sustainable solutions for the water environment in Chinese and Southeast Asian cities","volume":"51","author":"Luo","year":"2021","journal-title":"Ambio"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1814","DOI":"10.1002\/hyp.11626","article-title":"Prediction of vegetation anomalies over an inland river basin in north-western China","volume":"32","author":"Fu","year":"2018","journal-title":"Hydrol. Process."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.cliser.2018.04.001","article-title":"Simulating vegetation response to climate change in the Blue Mountains with MC2 dynamic global vegetation model","volume":"10","author":"Kim","year":"2018","journal-title":"Clim. Serv."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"107443","DOI":"10.1016\/j.ecolind.2021.107443","article-title":"The sensitivity of vegetation cover to climate change in multiple climatic zones using machine learning algorithms","volume":"124","author":"Bao","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.jhydrol.2003.09.029","article-title":"Terrestrial vegetation and water balance\u2014Hydrological evaluation of a dynamic global vegetation model","volume":"286","author":"Gerten","year":"2004","journal-title":"J. Hydrol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1175\/2008JCLI2541.1","article-title":"Coupling of integrated biosphere simulator to Regional Climate Model Version 3","volume":"22","author":"Winter","year":"2009","journal-title":"J. Clim."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3228","DOI":"10.1111\/j.1365-2486.2011.02419.x","article-title":"Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006","volume":"17","author":"Piao","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1111\/j.1365-2486.2006.01305.x","article-title":"Modelling the role of agriculture for the 20th century global terrestrial carbon balance","volume":"13","author":"Bondeau","year":"2007","journal-title":"Glob. Chang. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3985","DOI":"10.1016\/j.foreco.2008.03.056","article-title":"Combining remote sensing data with process modeling to monitor boreal conifer forest carbon balances","volume":"255","author":"Smith","year":"2008","journal-title":"For. Ecol. Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1126\/science.1115233","article-title":"Ecosystem service supply and vulnerability to global change in Europe","volume":"310","author":"Schroter","year":"2005","journal-title":"Science"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"GB3020","DOI":"10.1029\/2004GB002395","article-title":"Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics","volume":"19","author":"Zaehle","year":"2005","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"126532","DOI":"10.1016\/j.jhydrol.2021.126532","article-title":"Time-lag effects of climatic change and drought on vegetation dynamics in an alpine river basin of the Tibet Plateau, China","volume":"600","author":"Zuo","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.scitotenv.2019.01.022","article-title":"Impacts of climate change and human activities on grassland vegetation variation in the Chinese Loess Plateau","volume":"660","author":"Zheng","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yuan, H.H., Yang, G.J., Li, C.C., Wang, Y.J., Liu, J.G., Yu, H.Y., Feng, H.K., Xu, B., Zhao, X.Q., and Yang, X.D. (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"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.jhydrol.2019.04.043","article-title":"Spatial heterogeneity of changes in vegetation growth and their driving forces based on satellite observations of the Yarlung Zangbo River Basin in the Tibetan Plateau","volume":"574","author":"Sun","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1007\/s10661-016-5196-4","article-title":"Pattern of NDVI-based vegetation greening along an altitudinal gradient in the eastern Himalayas and its response to global warming","volume":"188","author":"Li","year":"2016","journal-title":"Environ. Monit. Assess."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Krakauer, N., Lakhankar, T., and Anad\u00f3n, J. (2017). Mapping and attributing normalized difference vegetation index trends for Nepal. Remote Sens., 9.","DOI":"10.20944\/preprints201709.0032.v1"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chi, K., Pang, B., Cui, L., Peng, D., Zhu, Z., Zhao, G., and Shi, S. (2020). Modelling the vegetation response to climate changes in the Yarlung Zangbo River Basin using random forest. Water, 12.","DOI":"10.3390\/w12051433"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s11442-007-0409-y","article-title":"Climate change over the Yarlung Zangbo River Basin during 1961\u20132005","volume":"17","author":"You","year":"2007","journal-title":"J. Geogr. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1007\/s12524-017-0692-8","article-title":"An improved dimidiated pixel model for vegetation fraction in the Yarlung Zangbo River Basin of Qinghai-Tibet Plateau","volume":"46","author":"Guo","year":"2017","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s10584-011-0099-4","article-title":"Response of hydrological cycle to recent climate changes in the Tibetan Plateau","volume":"109","author":"Yang","year":"2011","journal-title":"Clim. Chang."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s00477-013-0769-z","article-title":"The impact of climate change on runoff in the Yarlung Tsangpo River basin in the Tibetan Plateau","volume":"28","author":"Li","year":"2013","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_31","first-page":"418","article-title":"Vegetation change and its relationship with precipitation on the southern Tibetan Plateau","volume":"359","author":"Xu","year":"2013","journal-title":"IAHS Publ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1007\/s00704-018-2552-z","article-title":"Downscaling of daily extreme temperatures in the Yarlung Zangbo River Basin using machine learning techniques","volume":"136","author":"Ren","year":"2018","journal-title":"Theor. Appl. Climatol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"106145","DOI":"10.1016\/j.agwat.2020.106145","article-title":"Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm","volume":"237","author":"Mohammadi","year":"2020","journal-title":"Agric. Water Manag."},{"key":"ref_34","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_35","doi-asserted-by":"crossref","first-page":"7265178","DOI":"10.1155\/2017\/7265178","article-title":"Statistical Downscaling of Temperature with the Random Forest Model","volume":"2017","author":"Pang","year":"2017","journal-title":"Adv. Meteorol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","article-title":"River flow forecasting through conceptual models Part I\u2014A discussion of principles","volume":"3","author":"Nash","year":"1970","journal-title":"J. Hydrol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.atmosenv.2012.07.012","article-title":"Compilation and interpretation of photochemical model performance statistics published between 2006 and 2012","volume":"61","author":"Simon","year":"2012","journal-title":"Atmos. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3187","DOI":"10.1175\/JCLI-D-12-00321.1","article-title":"Evaluation of the global climate, models in the CMIP5 over the Tibetan Plateau","volume":"26","author":"Su","year":"2013","journal-title":"Int. J. Climatol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.scitotenv.2016.02.131","article-title":"Climate change and its impacts on vegetation distribution and net primary productivity of the alpine ecosystem in the Qinghai-Tibetan Plateau","volume":"554","author":"Gao","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_40","first-page":"77","article-title":"CMIP6 evaluation and projection of climate change over the Tibetan Plateau","volume":"58","author":"Zhang","year":"2022","journal-title":"J. Beijing Norm. Univ. Nat. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the regression coefficient based on Kendall\u2019s Tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.rse.2015.04.030","article-title":"Nonlinear response of vegetation green-up to local temperature variations in temperate and boreal forests in the Northern Hemisphere","volume":"165","author":"Park","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_43","first-page":"105","article-title":"Analysis of vegetation condition and its relationship with meteorological variables in the Yarlung Zangbo River Basin of China","volume":"379","author":"Han","year":"2018","journal-title":"Proc. Int. Assoc. Hydrol. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"16672","DOI":"10.3390\/rs71215844","article-title":"Elevation-dependent vegetation greening of the Yarlung Zangbo River Basin in the Southern Tibetan Plateau, 1999\u20132013","volume":"7","author":"Li","year":"2015","journal-title":"Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1080\/17538947.2013.848946","article-title":"Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau","volume":"8","author":"Wang","year":"2015","journal-title":"Int. J. Digit. Earth"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1657\/1938-4246-46.3.632","article-title":"Change of snow cover and its impact on alpine vegetation in the source regions of large rivers on the Qinghai-Tibetan Plateau, China","volume":"46","author":"Wan","year":"2014","journal-title":"Arct. Antarct. Alp. Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"124","DOI":"10.2166\/nh.2021.086","article-title":"Impact of variability in the hydrological cycle components on vegetation growth in an alpine basin of the southeastern Tibet Plateau, China","volume":"53","author":"Ban","year":"2022","journal-title":"Hydrol. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2057","DOI":"10.1080\/02626667.2019.1662908","article-title":"Responses of hydrological processes to climate change in the Yarlung Zangbo River basin","volume":"64","author":"Liu","year":"2019","journal-title":"Hydrol. Sci. J."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/S2095-3119(18)61936-7","article-title":"An integrated method of selecting environmental covariates for predictive soil depth mapping","volume":"18","author":"Lu","year":"2019","journal-title":"J. Integr. Agric."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2449","DOI":"10.1093\/bioinformatics\/bty087","article-title":"A new approach for interpreting Random Forest models and its application to the biology of ageing","volume":"34","author":"Fabris","year":"2018","journal-title":"Bioinformatics"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Li, H., Liu, L., Liu, X., Li, X., and Xu, Z. (2019). Greening Implication Inferred from Vegetation Dynamics interacted with climate change and human activities over the Southeast Qinghai\u2013Tibet Plateau. Remote Sens., 11.","DOI":"10.3390\/rs11202421"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Liu, L., Niu, Q., Heng, J., Li, H., and Xu, Z. (2019). Transition characteristics of the Dry-Wet regime and vegetation dynamic responses over the Yarlung Zangbo River Basin, Southeast Qinghai-Tibet Plateau. Remote Sens., 11.","DOI":"10.3390\/rs11101254"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Filippa, G., Cremonese, E., Galvagno, M., Isabellon, M., Bayle, A., Choler, P., Carlson, B.Z., Gabellani, S., di Cella, U.M., and Migliavacca, M. (2019). Climatic drivers of greening trends in the Alps. Remote Sens., 11.","DOI":"10.3390\/rs11212527"},{"key":"ref_54","first-page":"2229","article-title":"Research progress on the response processes of vegetation activity to climate change","volume":"38","author":"Jiao","year":"2018","journal-title":"Acta Ecol. Sin."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Afuye, G.A., Kalumba, A.M., and Orimoloye, I.R. (2021). Characterisation of vegetation response to climate change: A review. Sustainability, 13.","DOI":"10.3390\/su13137265"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"e2328","DOI":"10.1002\/eco.2328","article-title":"A bibliometric analysis of the research on Sponge City: Current situation and future development direction","volume":"14","author":"Zha","year":"2021","journal-title":"Ecohydrology"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3072","DOI":"10.2166\/wst.2021.335","article-title":"Heavy metals in water and surface sediments of the Fenghe River Basin, China: Assessment and source analysis","volume":"84","author":"Luo","year":"2021","journal-title":"Water Sci. Technol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1556\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T22:31:39Z","timestamp":1726871499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,23]]},"references-count":57,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071556"],"URL":"https:\/\/doi.org\/10.3390\/rs14071556","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,3,23]]}}}