{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T01:22:21Z","timestamp":1769304141585,"version":"3.49.0"},"reference-count":77,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31971577"],"award-info":[{"award-number":["31971577"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land cover changes are the main factors driving the evolution of regional ecological quality. These changes must be considered in the strategic formulation of regional or national ecological policies. The forest-steppe ecotone in the Greater Khingan Mountains is an important ecological barrier in northern China. To measure the effect of ecological protection in recent years, Landsat images, object-oriented image segmentation, and convolutional neural networks were used to create land cover datasets of the forest-steppe ecotone. The Carnegie\u2013Ames\u2013Stanford approach (CASA) and the dimidiate pixel model were used to derive net primary productivity (NPP) and fractional vegetation cover (FVC) to assess the ecological quality of this area. The results showed that only grassland and urban land increased, whereas saline\u2013alkali land and desert areas initially increased and then decreased from 2010 to 2018, indicating that the desertification process was substantially curbed. Total NPP increased by 26.3% (2000\u20132010) and 10.8% (2010\u20132018). However, NPP decreased slightly in the center of the study area. FVC first decreased and then increased, and the increased areas were concentrated in the forest-steppe ecotone, saline\u2013alkali land, and desert zone in Xin Barag Left Banner. These observations indicate that the ecological quality has gradually improved due to the strict protection of forest and grassland resources and the suppression of desertification. Our results provide potential insights for land use planning and the development of environmental protection measures in the forest-steppe ecotone.<\/jats:p>","DOI":"10.3390\/rs14030725","type":"journal-article","created":{"date-parts":[[2022,2,6]],"date-time":"2022-02-06T20:38:40Z","timestamp":1644179920000},"page":"725","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Assessing Land Cover and Ecological Quality Changes in the Forest-Steppe Ecotone of the Greater Khingan Mountains, Northeast China, from Landsat and MODIS Observations from 2000 to 2018"],"prefix":"10.3390","volume":"14","author":[{"given":"Fang","family":"Shi","sequence":"first","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Mingxing","family":"Liu","sequence":"additional","affiliation":[{"name":"Hunan Prospecting Designing & Research General Institute for Agriculture Forestry & Industry, Changsha 410007, China"}]},{"given":"Jie","family":"Qiu","sequence":"additional","affiliation":[{"name":"Provincial Geomatics Center of Jiangsu, Nanjing 210013, China"}]},{"given":"Yali","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Huiyi","family":"Su","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Xupeng","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Jiahui","family":"Fan","sequence":"additional","affiliation":[{"name":"Nanjing Institute of Environmental Sciences (NIES), Ministry of Environmental Protection (MEP), Nanjing 210042, China"}]},{"given":"Junsong","family":"Chen","sequence":"additional","affiliation":[{"name":"Jiangxi Academy of Forestry, Nanchang 330032, China"}]},{"given":"Yingying","family":"Lv","sequence":"additional","affiliation":[{"name":"Nanjing Institute of Environmental Sciences (NIES), Ministry of Environmental Protection (MEP), Nanjing 210042, China"}]},{"given":"Wanggu","family":"Xu","sequence":"additional","affiliation":[{"name":"Nanjing Institute of Environmental Sciences (NIES), Ministry of Environmental Protection (MEP), Nanjing 210042, China"}]},{"given":"Zhi","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanjing Institute of Environmental Sciences (NIES), Ministry of Environmental Protection (MEP), Nanjing 210042, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5689-5091","authenticated-orcid":false,"given":"Mingshi","family":"Li","sequence":"additional","affiliation":[{"name":"College of Forestry, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1016\/j.scitotenv.2019.03.015","article-title":"Impacts of anthropogenic land use\/cover changes on soil wind erosion in China","volume":"668","author":"Chi","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.5194\/isprs-archives-XLIII-B3-2020-1601-2020","article-title":"Fate of agricultural areas of Kailali District of Nepal: A temporal land use land cover change (LUCC) analysis","volume":"43","author":"Niraj","year":"2020","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci \u2014ISPRS"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, Z., Sun, Z., Tian, Y., Zhong, J., and Yang, W. (2019). Impact of land use\/cover change on yangtze river delta urban agglomeration ecosystem services value: Temporal-spatial patterns and cold\/hot spots ecosystem services value change brought by urbanization. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16010123"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Msofe, N.K., Sheng, L., Li, Z., and Lyimo, J. (2020). Impact of land use\/cover change on ecosystem service values in the Kilombero valley floodplain, southeastern Tanzania. Forests, 11.","DOI":"10.3390\/f11010109"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/13504500902771891","article-title":"Land-use dynamics and landscape pattern change in a coastal gulf region, southeast China","volume":"16","author":"Huang","year":"2009","journal-title":"Int. J. Sustain. Dev. World Ecol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Fan, J., Wang, Y., Zhou, Z., You, N., and Meng, J. (2016). Dynamic ecological risk assessment and management of land use in the middle reaches of the heihe river based on landscape patterns and spatial statistics. Sustainability, 8.","DOI":"10.3390\/su8060536"},{"key":"ref_7","first-page":"1","article-title":"Mapping and evaluation of landscape ecological status using geographic indices extracted from remote sensing imagery of the Pearl River Delta, China, between 1998 and 2008","volume":"75","author":"Zhang","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.ecolmodel.2007.06.007","article-title":"Combining AHP with GIS in synthetic evaluation of eco-environment quality\u2014A case study of hunan province, China","volume":"209","author":"Ying","year":"2007","journal-title":"Ecol. Modell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1080\/13658816.2013.845892","article-title":"Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster-vector routines with remote sensing and GIS","volume":"28","author":"Tayyebi","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.envsoft.2013.09.015","article-title":"A big data urban growth simulation at a national scale: Configuring the GIS and neural network based land transformation model to run in a high performance computing (HPC) environment","volume":"51","author":"Pijanowski","year":"2014","journal-title":"Environ. Model. Softw."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.landusepol.2014.02.002","article-title":"Assessment of decoupling between rural settlement area and rural population in China","volume":"39","author":"Song","year":"2014","journal-title":"Land Use Policy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"247","DOI":"10.3368\/le.81.2.247","article-title":"Grain for green: Cost-effectiveness and sustainability of China\u2019s conservation set-aside program","volume":"81","author":"Uchida","year":"2003","journal-title":"Land Econ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.jenvman.2019.02.046","article-title":"Land use model research in agro-pastoral ecotone in northern China: A case study of horqin left back banner","volume":"237","author":"Zhou","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.landurbplan.2018.04.014","article-title":"Land use change and habitat fragmentation of wildland ecosystems of the North Central United States","volume":"177","author":"Adhikari","year":"2018","journal-title":"Landsc. Urban Plan."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hu, Y., and Nacun, B. (2018). An analysis of land-use change and grassland degradation from a policy perspective in Inner Mongolia, China, 1990\u20132015. Sustainability, 10.","DOI":"10.3390\/su10114048"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3289","DOI":"10.1080\/014311697217099","article-title":"The igbp-dis global 1km land cover data set, discover: First results","volume":"18","author":"Loveland","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","first-page":"3289","article-title":"Global land cover classification at 1 km spatial resolution using a classification tree approach","volume":"18","author":"Hansen","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: A new approach to global land cover mapping from earth observation data","volume":"26","author":"Belward","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_20","unstructured":"Defourny, P., Vancutsem, C., Bicheron, C., Brockmann, C., Nino, F., Schouten, L., and Leroy, M. (2006, January 8\u201311). GlobCover: A 300M global land cover product for 2005 using envisat meris time series. using Envisat MERIS time series. Proceedings of the ISPRS Commission VII Mid-Term Symposium, Remote Sensing from Pixels to Processes, Enschede, The Netherlands."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Jin, S., Homer, C., Yang, L., Danielson, P., Dewitz, J., Li, C., Zhu, Z., Xian, G., and Howard, D. (2019). Overall methodology design for the United States national land cover database 2016 products. Remote Sens., 11.","DOI":"10.3390\/rs11242971"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1080\/01431161.2012.748992","article-title":"Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data","volume":"34","author":"Gong","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2721","DOI":"10.1590\/0001-3765201820170737","article-title":"Monitoring vegetation coverage in tongren from 2000 to 2016 based on landsat7 etm+ and landsat8","volume":"90","author":"Liu","year":"2018","journal-title":"An. Acad. Bras. Cienc."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"108017","DOI":"10.1016\/j.agrformet.2020.108017","article-title":"Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels","volume":"290","author":"Alton","year":"2020","journal-title":"Agric. For. Meteorol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"121490","DOI":"10.1016\/j.jclepro.2020.121490","article-title":"A study of the impacts of urban expansion on vegetation primary productivity levels in the Jing-Jin-Ji region, based on nighttime light data","volume":"263","author":"Chang","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.rse.2005.07.011","article-title":"A comparison of methods for estimating fractional green vegetation cover within a desert-to-upland transition zone in central New Mexico, USA","volume":"98","author":"Xiao","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1029\/93GB02725","article-title":"Terrestrial ecosystem production\u2014A process model based on global satellite and surface data","volume":"7","author":"Potter","year":"1993","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/S0034-4257(02)00043-3","article-title":"Estimation of carbon mass fluxes over Europe using the C-fix model and Euroflux data","volume":"83","author":"Veroustraete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1080\/20964129.2020.1749010","article-title":"Impacts of land conversion and management measures on net primary productivity in semi-arid grassland","volume":"6","author":"Cao","year":"2020","journal-title":"Ecosyst. Health Sustain."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.quaint.2019.06.017","article-title":"Variations and climate constraints of terrestrial net primary productivity over Mongolia","volume":"537","author":"Bao","year":"2020","journal-title":"Quat. Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1016\/j.asr.2012.11.015","article-title":"Using vegetation indices and texture measures to estimate vegetation fractional coverage (VFC) of planted and natural forests in Nanjing city, China","volume":"51","author":"Gu","year":"2013","journal-title":"Adv. Sp. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"102331","DOI":"10.1016\/j.resourpol.2021.102331","article-title":"Characterizing and attributing the vegetation coverage changes in North Shanxi coal base of China from 1987 to 2020","volume":"74","author":"Li","year":"2021","journal-title":"Resour. Policy"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1080\/2150704X.2019.1597298","article-title":"Monitoring vegetation dynamics using the universal normalized vegetation index (UNVI): An optimized vegetation index-VIUPD","volume":"10","author":"Zhang","year":"2019","journal-title":"Remote Sens. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, R., Yan, F., and Wang, Y. (2020). Vegetation growth status and topographic effects in the pisha sandstone area of China. Remote Sens., 12.","DOI":"10.3390\/rs12172759"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1080\/01431161.2019.1657605","article-title":"Fractional vegetation coverage response to climatic factors based on grey relational analysis during the 2000-2017 growing season in Sichuan Province, China","volume":"41","author":"Li","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.scib.2019.12.007","article-title":"Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018","volume":"65","author":"Gong","year":"2020","journal-title":"Sci. Bull."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.ecoinf.2019.01.012","article-title":"Automatic detection of woody vegetation in repeat landscape photographs using a convolutional neural network","volume":"50","author":"Bayr","year":"2019","journal-title":"Ecol. Inform."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med. Image Anal."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun. ACM"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1016\/j.procs.2018.10.342","article-title":"Deep alexnet with reduced number of trainable parameters for satellite image classification","volume":"143","author":"Unnikrishnan","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_43","first-page":"70","article-title":"Classifition of land use scenarios based on find-tuing convolution naturel network","volume":"34","author":"Chen","year":"2019","journal-title":"Remote Sens. Inf."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4336","DOI":"10.1080\/01431161.2020.1717667","article-title":"Analysis of spatiotemporal dynamics of forest net primary productivity of Nepal during 2000\u20132015","volume":"41","author":"Koju","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3740","DOI":"10.1080\/01431161.2019.1707902","article-title":"Modifying the maximal light-use efficiency for enhancing predictions of vegetation net primary productivity on the Mongolian Plateau","volume":"41","author":"Jin","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1007\/s00704-020-03348-4","article-title":"Drought severity classification based on threshold level method and drought effects on NPP","volume":"142","author":"Li","year":"2020","journal-title":"Theor. Appl. Climatol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"7664","DOI":"10.1080\/01431161.2018.1478464","article-title":"An improved phenology-based CASA model for estimating net primary production of forest in central China based on Landsat images","volume":"39","author":"Pei","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s11434-006-0457-1","article-title":"Simulation of maximum light use efficiency for some typical vegetation types in China","volume":"51","author":"Zhu","year":"2006","journal-title":"Chin. Sci. Bull."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/S0143-6228(02)00048-6","article-title":"Evaluation of approaches for forest cover estimation in the Pacific Northwest, USA, using remote sensing","volume":"22","author":"Boyd","year":"2002","journal-title":"Appl. Geogr."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1007\/s11769-018-1010-2","article-title":"Comparative analysis of fractional vegetation cover estimation based on multi-sensor data in a semi-arid sandy area","volume":"29","author":"Liu","year":"2019","journal-title":"Chin. Geogr. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/S0034-4257(01)00289-9","article-title":"Novel algorithms for remote estimation of vegetation fraction","volume":"80","author":"Gitelson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Jia, K., Li, Y., Liang, S., Wei, X., and Yao, Y. (2017). Combining estimation of green vegetation fraction in an arid region from Landsat 7 ETM+ data. Remote Sens., 9.","DOI":"10.3390\/rs9111121"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"105874","DOI":"10.1016\/j.ecolind.2019.105874","article-title":"Assessment of spatial and temporal variation of ecological environment quality in Ebinur lake Wetland National Nature Reserve, Xinjiang, China","volume":"110","author":"Jing","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Rihan, W., Zhao, J., Zhang, H., Guo, X., Ying, H., Deng, G., and Li, H. (2019). Wildfires on the Mongolian Plateau: Identifying drivers and spatial distributions to predict wildfire probability. Remote Sens., 11.","DOI":"10.3390\/rs11202361"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Gao, Q., Schwartz, M.W., Zhu, W., Wan, Y., Qin, X., Ma, X., Liu, S., Williamson, M.A., Peters, C.B., and Li, Y. (2016). Changes in global grassland productivity during 1982 to 2011 attributable to climatic factors. Remote Sens., 8.","DOI":"10.3390\/rs8050384"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1007\/s00382-014-2273-7","article-title":"Drought variability in eastern Mongolian Plateau and its linkages to the large-scale climate forcing","volume":"44","author":"Bao","year":"2015","journal-title":"Clim. Dyn."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"110","DOI":"10.4028\/www.scientific.net\/AMR.365.110","article-title":"The research of livestock carrying capacity of rangeland ecosystem in HulunBuir","volume":"365","author":"Wang","year":"2012","journal-title":"Adv. Mater. Res."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Fang, H., and Fan, Z. (2020). Assessment of soil erosion at multiple spatial scales following land use changes in 1980\u20132017 in the black soil region, (NE) China. Int. J. Environ. Res. Public Health, 17.","DOI":"10.20944\/preprints202009.0082.v1"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"104123","DOI":"10.1016\/j.catena.2019.104123","article-title":"Spatiotemporal changes in the Aeolian desertification of Hulunbuir Grassland and its driving factors in China during 1980\u20132015","volume":"182","author":"Na","year":"2019","journal-title":"Catena"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1007\/s10980-014-0092-1","article-title":"Effects of precipitation on grassland ecosystem restoration under grazing exclusion in Inner Mongolia, China","volume":"29","author":"Hao","year":"2014","journal-title":"Landsc. Ecol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.catena.2017.05.030","article-title":"Monitoring the trends of aeolian desertified lands based on time-series remote sensing data in the Horqin Sandy Land, China","volume":"157","author":"Wang","year":"2017","journal-title":"Catena"},{"key":"ref_62","unstructured":"Wang, Z., Wang, Z., Zhang, B., Lu, C., and Ren, C. (2013, January 26\u201328). Landscape dynamics in Hulunbuir Grassland of China. Proceedings of the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE), Nanjing, China, 316\u2013319."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.ecolind.2017.11.026","article-title":"Association analysis between spatiotemporal variation of net primary productivity and its driving factors in inner mongolia, china during 1994\u20132013","volume":"105","author":"Wang","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.landurbplan.2012.01.003","article-title":"Urban neighborhood green index\u2014A measure of green spaces in urban areas","volume":"105","author":"Gupta","year":"2012","journal-title":"Landsc. Urban Plan."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1638","DOI":"10.1016\/S2095-3119(15)61253-9","article-title":"Evaluating the grassland net primary productivity of southern China from 2000 to 2011 using a new climate productivity model","volume":"15","author":"Sun","year":"2016","journal-title":"J. Integr. Agric."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.jaridenv.2019.01.004","article-title":"Spatiotemporal variations and its influencing factors of grassland net primary productivity in Inner Mongolia, China during the period 2000\u20132014","volume":"165","author":"Zhao","year":"2019","journal-title":"J. Arid Environ."},{"key":"ref_67","first-page":"647","article-title":"Temporal and spatial distribution of vegetation net primary productivity (NPP) in the Years from 1982 to 2010 in Hulunbeier","volume":"8","author":"Chen","year":"2012","journal-title":"J. Ecol. Rural Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s11769-014-0662-9","article-title":"Examining forest net primary productivity dynamics and driving forces in northeastern China during 1982\u20132010","volume":"24","author":"Mao","year":"2014","journal-title":"Chin. Geogr. Sci."},{"key":"ref_69","first-page":"88690Z","article-title":"Study on spatio-temporal vegetation cover changes based on MODIS NDVI data in the Mongolian Plateau, 2000\u20132012","volume":"8869","author":"Cao","year":"2013","journal-title":"Remote Sens. Model. Ecosyst. Sustain. X"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1002\/gj.3030","article-title":"Spatial and temporal change of fractional vegetation cover in North-western China from 2000 to 2010","volume":"53","author":"Wei","year":"2018","journal-title":"Geol. J."},{"key":"ref_71","first-page":"563","article-title":"Analysis on temporal-spatial change of vegetation coverage in hulunbuir steppe (2000\u20132014). Presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"53","author":"Peng","year":"2017","journal-title":"Beijing Daxue Xuebao (Ziran Kexue Ban)"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"4705","DOI":"10.3390\/rs6064705","article-title":"Improving estimates of grassland fractional vegetation cover based on a pixel dichotomy model: A case study in Inner Mongolia, China","volume":"6","author":"Li","year":"2014","journal-title":"Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3004","DOI":"10.1111\/j.1365-2486.2010.02210.x","article-title":"Change in winter snow depth and its impacts on vegetation in China","volume":"16","author":"Peng","year":"2010","journal-title":"Glob. Change Biol."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Liu, H., and Ma, L. (2020). Spatial pattern and effects of urban coordinated development in China\u2019s urbanization. Sustainability, 12.","DOI":"10.3390\/su12062389"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12665-020-09035-x","article-title":"Spatiotemporal change characteristics and driving mechanism of slope cultivated land transition in karst trough valley area of Guizhou Province, China","volume":"79","author":"Wang","year":"2020","journal-title":"Environ. Earth Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1130\/G30334A.1","article-title":"Barchan dunes stabilized under recent climate warming on the northern Great Plains","volume":"37","author":"Wolfe","year":"2009","journal-title":"Geology"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s11442-014-1082-6","article-title":"Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s","volume":"24","author":"Liu","year":"2014","journal-title":"J. Geogr. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/725\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:13:49Z","timestamp":1760134429000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/725"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,3]]},"references-count":77,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030725"],"URL":"https:\/\/doi.org\/10.3390\/rs14030725","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,3]]}}}