{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T20:34:20Z","timestamp":1780518860789,"version":"3.54.1"},"reference-count":67,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,11]],"date-time":"2020-02-11T00:00:00Z","timestamp":1581379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA2003020201"],"award-info":[{"award-number":["XDA2003020201"]}]},{"name":"National Key Research and Development Program of China-Mongolia cooperation research and demonstration in grassland desertification control technology","award":["2017YFE0109200"],"award-info":[{"award-number":["2017YFE0109200"]}]},{"name":"China-initiated \u201cBelt and Road Special Project\u201d","award":["131965KYSB20170038"],"award-info":[{"award-number":["131965KYSB20170038"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As a result of the unique geographical characteristics, pastoral lifestyle, and economic conditions in Mongolia, its fragile natural ecosystems are highly sensitive to climate change and human activities. The normalized difference vegetation index (NDVI) was employed in this study as an indicator of the growth status of vegetation. The Sen\u2019s slope, Mann\u2013Kendall test, and geographical detector modelling methods were used to assess the spatial and temporal changes of the NDVI in response to variations in natural conditions and human activities in Mongolia from 1982 to 2015. The corresponding individual and interactive driving forces, and the optimal range for the maximum NDVI value of vegetation distribution were also quantified. The area in which vegetation was degraded was roughly equal to the area of increase, but different vegetation types behaved differently. The desert steppe and the Gobi Desert both in arid regions have degraded significantly, whereas the meadow steppe and alpine steppe showed a significant upward trend. Precipitation can satisfactorily account for vegetation distribution. Changes of livestock quantity was the dominant factor influencing the changes of most vegetation types. The interactions of topographic factors and climate factors have significant effects on vegetation growth. In the region of annual precipitation between 331 mm and 596 mm, forest vegetation type and pine sandy soil type were found to be most suitable for the growth of vegetation in Mongolia. The findings of this study can help us to understand the appropriate range or type of environmental factors affecting vegetation growth in Mongolia, based on which we can apply appropriate interventions to effectively mitigate the impact of environmental changes on vegetation.<\/jats:p>","DOI":"10.3390\/rs12040603","type":"journal-article","created":{"date-parts":[[2020,2,11]],"date-time":"2020-02-11T11:45:30Z","timestamp":1581421530000},"page":"603","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":193,"title":["Spatial and Temporal Characteristics of Vegetation NDVI Changes and the Driving Forces in Mongolia during 1982\u20132015"],"prefix":"10.3390","volume":"12","author":[{"given":"Xiaoyu","family":"Meng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengyu","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqiang","family":"Lei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1038\/nclimate1329","article-title":"Continent-wide response of mountain vegetation to climate change","volume":"2","author":"Gottfried","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s11442-017-1369-5","article-title":"Correlation analysis between vegetation coverage and climate drought conditions in North China during 2001\u20132013","volume":"27","author":"Gong","year":"2017","journal-title":"J. Geogr. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1038\/nature01286","article-title":"A globally coherent fingerprint of climate change impacts across natural systems","volume":"421","author":"Parmesan","year":"2003","journal-title":"Nature"},{"key":"ref_4","first-page":"395","article-title":"Seasonal variations of day-and nighttime warming and their effects on vegetation dynamics in China\u2019s temperate zone","volume":"73","author":"Zhao","year":"2018","journal-title":"Acta Ecol. Sin."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Du, Z., Zhang, X., Xu, X., Zhang, H., Wu, Z., and Pang, J. (2017). Quantifying influences of physiographic factors on temperate dryland vegetation, Northwest China. Sci. Rep., 7.","DOI":"10.1038\/srep40092"},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.agrformet.2017.11.013","article-title":"Changes in global vegetation activity and its driving factors during 1982\u20132013","volume":"249","author":"Zhao","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1007\/s00382-018-04611-1","article-title":"Assessment of CFSR, ERA-Interim, JRA-55, MERRA-2, NCEP-2 reanalysis data for drought analysis over China","volume":"53","author":"Chen","year":"2019","journal-title":"Clim. Dyn."},{"key":"ref_9","first-page":"2413","article-title":"Spatiotemporal variations of growing-season NDVI and response to climate change in permafrost zone of Northeast China","volume":"28","author":"Guo","year":"2017","journal-title":"Chin. J. Appl. Ecol."},{"key":"ref_10","first-page":"91","article-title":"Vegetation dynamics in response to climate change based on satellite derived NDVI in Nepal","volume":"20","author":"Baniya","year":"2018","journal-title":"EGU Gen. Assem. Conf. Abstr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.ecolind.2011.08.011","article-title":"Trend analysis of vegetation dynamics in Qinghai\u2013Tibet Plateau using Hurst Exponent","volume":"14","author":"Peng","year":"2012","journal-title":"Ecol. Indic."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1164","DOI":"10.1016\/j.jaridenv.2011.05.002","article-title":"Desertification in the Sahel: Towards better accounting for ecosystem dynamics in the interpretation of remote sensing images","volume":"75","author":"Hein","year":"2011","journal-title":"J. Arid Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1111\/j.1467-8306.2004.09402008.x","article-title":"The Validity and Usefulness of Laws in Geographic Information Science and Geography","volume":"2","author":"Goodchild","year":"2004","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Fischer, M., and Wang, J. (2011). Spatial Data Analysis: Models, Methods and Techniques, Springer.","DOI":"10.1007\/978-3-642-21720-3"},{"key":"ref_15","unstructured":"Fortin, M.J. (2012). Spatio-Temporal Heterogeneity: Concepts and Analyses by Pierre R.L. Dutilleul. Q. Rev. Biol., 87."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/13658810802443457","article-title":"Geographical Detectors-ased Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China","volume":"24","author":"Wang","year":"2010","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_17","first-page":"34","article-title":"Mongolia Assessment Report on Climate Change 2009","volume":"2","author":"Dagvadorj","year":"2009","journal-title":"Minist. Nat. Environ. Tour. Ulaanbaatar"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3354\/cr01347","article-title":"Climate variability and change on the Mongolian Plateau: Historical variation and future predictions","volume":"67","author":"Jiang","year":"2016","journal-title":"Clim. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1111\/gcb.12365","article-title":"Satellite observed widespread decline in Mongolian grasslands largely due to overgrazing","volume":"20","author":"Hilker","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1007\/s10980-015-0261-x","article-title":"Differentiating anthropogenic modification and precipitation-driven change on vegetation productivity on the Mongolian Plateau","volume":"31","author":"John","year":"2016","journal-title":"Landsc. Ecol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4293","DOI":"10.1002\/joc.4286","article-title":"NDVI-indicated long-term vegetation dynamics in Mongolia and their response to climate change at biome scale","volume":"35","author":"Bao","year":"2015","journal-title":"Int. J. Climatol."},{"key":"ref_22","first-page":"73","article-title":"Degradation of the Vegetation Cover in Central Mongolia: A Case Study","volume":"6","author":"Tsydypov","year":"2015","journal-title":"J. Resour. Ecol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"599","DOI":"10.3103\/S1068373918090066","article-title":"Analysis of Desertification in Mongolia","volume":"43","author":"Filei","year":"2018","journal-title":"Russ. Meteorol. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/j.scitotenv.2017.10.253","article-title":"Distinguishing the vegetation dynamics induced by anthropogenic factors using vegetation optical depth and AVHRR NDVI: A cross-border study on the Mongolian Plateau","volume":"616","author":"Zhou","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.5194\/bg-15-1319-2018","article-title":"Climate effects on vegetation vitality at the treeline of boreal forests of Mongolia","volume":"15","author":"Klinge","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.rse.2015.03.031","article-title":"Evaluating temporal consistency of long-term global NDVI datasets for trend analysis","volume":"163","author":"Tian","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.ecolind.2015.05.036","article-title":"Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator","volume":"58","author":"Jiapaer","year":"2015","journal-title":"Ecol. Indic."},{"key":"ref_28","first-page":"28","article-title":"Vegetation NDVI Change and Its Relationship with Climate Change and Human Activities in Yulin, Shaanxi Province of China","volume":"4","author":"Wang","year":"2016","journal-title":"J. Geosci. Environ. Prot."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.rse.2017.01.014","article-title":"Driving forces of recent vegetation changes in the Sahel: Lessons learned from regional and local level analyses","volume":"191","author":"Leroux","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Jinkai, L., Dengfeng, L., Qiang, H., Jiuliang, F., Mu, L., and Guobao, L. (2018). Analysis of the spatial-temporal change and impact factors of the vagetation index in Yulin, Shaanxi Province, in the last 17 years. Acta Ecol. Sin., 38.","DOI":"10.5846\/stxb201704210718"},{"key":"ref_31","unstructured":"Bespalov, N.D., and Gourevitch, A. (1964). Soils of Outer Mongolia (Mongolian People\u2019s Republic), Israel Program for Scientific Translations."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6929","DOI":"10.3390\/rs6086929","article-title":"A Non-Stationary 1981\u20132012 AVHRR NDVI3g Time Series","volume":"6","author":"Pinzon","year":"2014","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3457","DOI":"10.1111\/gcb.12625","article-title":"Strong contribution of autumn phenology to changes in satellite-derived growing season length estimates across Europe (1982\u20132011)","volume":"20","author":"Garonna","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1080\/01431168608948945","article-title":"Characteristics of maximum-value composite images from temporal AVHRR data","volume":"7","author":"HOLBEN","year":"1986","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The Global Land Data Assimilation System","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_36","first-page":"4","article-title":"Analysis of Response of Soil Moisture to Climate Change in Semi-arid Loess Plateau in China Based on GLDAS Data","volume":"27","author":"Cheng","year":"2013","journal-title":"J. Arid Meteorol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2771","DOI":"10.1002\/2017MS001019","article-title":"Evaluation and Enhancement of Permafrost Modeling with the NASA Catchment Land Surface Model","volume":"9","author":"Tao","year":"2017","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5707","DOI":"10.1080\/01431161.2015.1104743","article-title":"Use of GRACE time-variable data and GLDAS-LSM for estimating groundwater storage variability at small basin scales: A case study of the Nzoia River Basin","volume":"36","author":"Ouma","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","unstructured":"Jarvis, A., Reuter, H., Nelson, A., and Guevara, E. (2008). Ole-Filled Seamless SRTM Data V4, International Centre for Tropical Agriculture (CIAT)."},{"key":"ref_40","unstructured":"Dorijgotov, D. (2009). National Atlas of Mongolia, Institute of Geography, Ulaanbaatar City."},{"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":"245","DOI":"10.2307\/1907187","article-title":"Non-Parametric Test against Trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"},{"key":"ref_43","unstructured":"Kendall, M. (1975). Rank Correlation Methods, Griffin."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1007\/s00382-016-3110-y","article-title":"Satio-statistical analysis of temperature fluctuation using Mann-Kendall and Sen\u2019s slope approach","volume":"48","author":"Rahman","year":"2017","journal-title":"Clim. Dyn."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Alhaji, U., Yusuf, A., Edet, C., Oche, C., and Agbo, E. (2018). Trend Analysis of Temperature in Gombe State Using Mann Kendall Trend Test. J. Sci. Res. Rep., 20.","DOI":"10.9734\/JSRR\/2018\/42029"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Ali, R., Kuriqi, A., Abubaker, S., and Kisi, O. (2019). Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen\u2019s Innovative Trend Method. Water, 11.","DOI":"10.3390\/w11091855"},{"key":"ref_47","first-page":"7","article-title":"Mann-Kendall, and Sen\u2019s Slope Estimators for Precipitation Trend Analysis in North-Eastern States of India","volume":"177","author":"Kamal","year":"2019","journal-title":"Int. J. Comp. Appl."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.ecolind.2016.02.052","article-title":"A measure of spatial stratified heterogeneity","volume":"67","author":"Wang","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_49","first-page":"186","article-title":"The Data Model Concept in Statistical Mapping","volume":"7","author":"Jenks","year":"1967","journal-title":"Int. Yearb. Cartogr."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1038\/nclimate3004","article-title":"Greening of the Earth and its drivers","volume":"6","author":"Zhu","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1934","DOI":"10.1126\/science.286.5446.1934","article-title":"Global Warming and Northern Hemisphere Sea Ice Extent","volume":"286","author":"Vinnikov","year":"1999","journal-title":"Science"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/S0169-5347(99)01764-4","article-title":"Biological consequences of global warming: Is the signal already apparent?","volume":"15","author":"Hughes","year":"2000","journal-title":"Trends Ecol. Evol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1007\/s10980-014-0095-y","article-title":"Satellite-indicatedlong-term vegetation changes and their drivers on the Mongolian Plateau","volume":"30","author":"Zhao","year":"2014","journal-title":"Landsc. Ecol."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Gantsetseg, B., Ishizuka, M., Kurosaki, Y., and Mikami, M. (2017). Topographical and hydrological effects on meso-scale vegetation in desert steppe, Mongolia. J. Arid Land.","DOI":"10.1007\/s40333-016-0090-z"},{"key":"ref_55","first-page":"89","article-title":"Soil-Forming Factors: Soil as a Component of Ecosystems","volume":"3","author":"Buol","year":"2011","journal-title":"Wiley-Blackwell"},{"key":"ref_56","first-page":"238","article-title":"Land suitability evaluation for agricultural cropland in Mongolia using the spatial MCDM method and AHP based GIS","volume":"5","author":"Otgonbayar","year":"2017","journal-title":"J. Geosci. Environ. Prot."},{"key":"ref_57","first-page":"5331","article-title":"Spatiotemporal changes in vegetation coverage in China during 1982-2012","volume":"35","author":"Liu","year":"2015","journal-title":"Acta Ecol. Sin."},{"key":"ref_58","unstructured":"Cao, F., Ge, Y., and Wang, J.F. (2015). Optimal discretization for geographical detectors-based risk assessment. GISci. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Deng, Q., Lin, Q., and Cai, C. (2017). Quantitative analysis of the impacts of terrestrial environmental factors on precipitation variation over the Beibu Gulf Economic Zone in Coastal Southwest China. Sci. Rep., 7.","DOI":"10.1038\/srep44412"},{"key":"ref_60","first-page":"210","article-title":"Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia","volume":"15","author":"Lee","year":"2019","journal-title":"For. Sci. Technol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"3833","DOI":"10.1016\/j.rse.2008.06.006","article-title":"Development of a two-band enhanced vegetation index without a blue band","volume":"112","author":"Jiang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1080\/2150704X.2019.1634299","article-title":"Globally standardized MODIS spectral mixture models","volume":"10","author":"Sousa","year":"2019","journal-title":"Remote Sens. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3204","DOI":"10.1080\/01431161.2018.1541110","article-title":"Mapping pasture biomass in Mongolia using Partial Least Squares, Random Forest regression and Landsat 8 imagery","volume":"40","author":"Otgonbayar","year":"2019","journal-title":"Int. J. Remote. Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2970","DOI":"10.1038\/s41467-019-11035-w","article-title":"Divergent changes in the elevational gradient of vegetation activities over the last 30 years","volume":"10","author":"Gao","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Albarakat, R., and Lakshmi, V. (2019). Comparison of Normalized Difference Vegetation Index Derived from Landsat, MODIS, and AVHRR for the Mesopotamian Marshes between 2002 and 2018. Remote Sens., 11.","DOI":"10.3390\/rs11101245"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Otgonbayar, M., Atzberger, C., Mattiuzzi, M., and Erdenedalai, A. (2019). Estimation of Climatologies of Average Monthly Air Temperature over Mongolia Using MODIS Land Surface Temperature (LST) Time Series and Machine Learning Techniques. Remote Sens., 11.","DOI":"10.3390\/rs11212588"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/4\/603\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:56:57Z","timestamp":1760173017000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/4\/603"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,11]]},"references-count":67,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["rs12040603"],"URL":"https:\/\/doi.org\/10.3390\/rs12040603","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,11]]}}}