{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T21:40:46Z","timestamp":1774906846417,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,15]],"date-time":"2023-01-15T00:00:00Z","timestamp":1673740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41875031"],"award-info":[{"award-number":["41875031"]}]},{"name":"National Natural Science Foundation of China","award":["41522501"],"award-info":[{"award-number":["41522501"]}]},{"name":"National Natural Science Foundation of China","award":["41275028"],"award-info":[{"award-number":["41275028"]}]},{"name":"National Natural Science Foundation of China","award":["42230610"],"award-info":[{"award-number":["42230610"]}]},{"name":"National Natural Science Foundation of China","award":["2019QZKK0103"],"award-info":[{"award-number":["2019QZKK0103"]}]},{"name":"National Natural Science Foundation of China","award":["58516"],"award-info":[{"award-number":["58516"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["41875031"],"award-info":[{"award-number":["41875031"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["41522501"],"award-info":[{"award-number":["41522501"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["41275028"],"award-info":[{"award-number":["41275028"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["42230610"],"award-info":[{"award-number":["42230610"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["2019QZKK0103"],"award-info":[{"award-number":["2019QZKK0103"]}]},{"name":"the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, Ministry of Science and Technology of the People\u2019s Republic of China","award":["58516"],"award-info":[{"award-number":["58516"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["41875031"],"award-info":[{"award-number":["41875031"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["41522501"],"award-info":[{"award-number":["41522501"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["41275028"],"award-info":[{"award-number":["41275028"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["42230610"],"award-info":[{"award-number":["42230610"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["2019QZKK0103"],"award-info":[{"award-number":["2019QZKK0103"]}]},{"name":"CLIMATE-Pan-TPE in the framework of the ESA-MOST Dragon 5 Programme","award":["58516"],"award-info":[{"award-number":["58516"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Drought is a major disaster over the Tibetan Plateau (TP) that exerts great impacts on natural ecosystems and agricultural production. Furthermore, most drought indices are only useful for assessing drought conditions on a coarse temporal scale. Drought indices that describe drought evolution at a fine temporal scale are still scarce. In this study, four machine learning methods, including random forest regression (RFR), k-nearest neighbor regression (KNNR), support vector regression (SVR), and extreme gradient boosting regression (XGBR), were used to construct daily drought indices based on multisource remote sensing and reanalysis data. Through comparison with in situ soil moisture (SM) over the TP, our results indicate that the drought index based on the XGBR model outperforms other models (R2 = 0.76, RMSE = 0.11, MAE = 0.08), followed by RFR (R2 = 0.74, RMSE = 0.11, MAE = 0.08), KNNR (R2 = 0.73, RMSE = 0.11, MAE = 0.08) and SVR (R2 = 0.66, RMSE = 0.12, MAE = 0.1). A new daily drought index, the standardized integrated drought index (SIDI), was developed by the XGBR model for monitoring agricultural drought. A comparison with ERA5-Land SM and widely used indices such as SPI-6 and SPEI-6 indicated that the SIDI depicted the dry and wet change characteristics of the plateau well. Furthermore, the SIDI was applied to analyze a typical drought event and reasonably characterize the spatiotemporal patterns of drought evolution, demonstrating its capability and superiority for drought monitoring over the TP. In addition, soil properties accounted for 59.5% of the model output, followed by meteorological conditions (35.8%) and topographic environment (4.7%).<\/jats:p>","DOI":"10.3390\/rs15020512","type":"journal-article","created":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T04:31:32Z","timestamp":1673843492000},"page":"512","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A New Drought Monitoring Index on the Tibetan Plateau Based on Multisource Data and Machine Learning Methods"],"prefix":"10.3390","volume":"15","author":[{"given":"Meilin","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8003-0856","authenticated-orcid":false,"given":"Lei","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"},{"name":"CAS Center for Excellence in Comparative Planetology, Hefei 230026, China"},{"name":"Jiangsu Collaborative Innovation Center for Climate Change, Nanjing 210023, China"},{"name":"Frontiers Science Center for Planetary Exploration and Emerging Technologies, University of Science and Technology of China, Hefei 230026, China"}]},{"given":"Yaoming","family":"Ma","sequence":"additional","affiliation":[{"name":"Land-Atmosphere Interaction and Its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China"},{"name":"National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China"},{"name":"Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad 45320, Pakistan"}]},{"given":"Xian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"}]},{"given":"Peizhen","family":"Li","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"}]},{"given":"Zixin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"}]},{"given":"Yuting","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.scitotenv.2017.10.327","article-title":"Drought evolution, severity and trends in mainland China over 1961\u20132013","volume":"616\u2013617","author":"Yao","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhang, X., Su, Z., Lv, J., Liu, W., Ma, M., Peng, J., and Leng, G. (2019). A set of satellite-based near real-time meteorological drought monitoring data over China. Remote Sens., 11.","DOI":"10.3390\/rs11040453"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"D12115","DOI":"10.1029\/2010JD015541","article-title":"Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900\u20132008","volume":"116","author":"Dai","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_4","first-page":"11","article-title":"Aridity pattern of Tibetan Plateau and its influential factors in 2001\u20132010","volume":"8","author":"Wang","year":"2012","journal-title":"Progress. Inquisitiones Mutat. Clim."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s10584-009-9787-8","article-title":"Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau","volume":"103","author":"Zhong","year":"2010","journal-title":"Clim. Chang."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7540","DOI":"10.1029\/2019JD030481","article-title":"Climate change trends and impacts on vegetation greening over the Tibetan Plateau","volume":"124","author":"Zhong","year":"2019","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"034013","DOI":"10.1088\/1748-9326\/10\/3\/034013","article-title":"Aridity changes in the Tibetan Plateau in a warming climate","volume":"10","author":"Gao","year":"2015","journal-title":"Environ. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.scitotenv.2016.11.098","article-title":"Does drought in China show a significant decreasing trend from 1961 to 2009?","volume":"579","author":"Wang","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"14323","DOI":"10.1038\/s41598-020-71295-1","article-title":"Drought characteristics and its elevation dependence in the Qinghai-Tibet plateau during the last half-century","volume":"10","author":"Feng","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_10","unstructured":"Liu, G. (2008). Encyclopedia of Meteorological Disasters in China: Tibet Volume."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s00704-013-1025-7","article-title":"The impracticality of a universal drought definition","volume":"117","year":"2014","journal-title":"Theor. Appl. Climatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1080\/02508068508686328","article-title":"Understanding the drought phenomenon: The role of definitions","volume":"10","author":"Dracup","year":"1985","journal-title":"Water Int."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1175\/1520-0477-78.5.847","article-title":"Meteorological drought-policy statement","volume":"78","author":"Society","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.jhydrol.2010.07.012","article-title":"A review of drought concepts","volume":"391","author":"Mishra","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2543","DOI":"10.1175\/BAMS-D-16-0292.1","article-title":"Defining Ecological Drought for the Twenty-First Century","volume":"98","author":"Crausbay","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"103348","DOI":"10.1016\/j.earscirev.2020.103348","article-title":"Challenges for drought assessment in the Mediterranean region under future climate scenarios","volume":"210","author":"Tramblay","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"102953","DOI":"10.1016\/j.earscirev.2019.102953","article-title":"A review of environmental droughts; increased risk under global warming?","volume":"201","author":"Quiring","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Maliva, R., and Thomas, M. (2012). Aridity and drought. Arid Lands Water Evaluation and Management, Springer.","DOI":"10.1007\/978-3-642-29104-3"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1175\/1520-0450(1984)023<1100:TPDSIL>2.0.CO;2","article-title":"The Palmer drought severity index: Limitations and assumptions","volume":"23","author":"Alley","year":"1984","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_20","unstructured":"Mckee, T.B., Doesken, N.J., and Kleist, J. (1993, January 17\u201322). The Relationship of Drought Frequency and Duration to Time Scales. Proceedings of the 8th Conference on Applied Climatology, Anaheim, CA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1175\/2009JCLI2909.1","article-title":"A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index","volume":"23","year":"2010","journal-title":"J. Clim."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1175\/JHM-D-22-0011.1","article-title":"A novel standardized drought and flood potential index based on reconstructed daily GRACE data","volume":"23","author":"Xiong","year":"2022","journal-title":"J. Hydrometeorol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"126868","DOI":"10.1016\/j.jhydrol.2021.126868","article-title":"A comprehensive assessment of water storage dynamics and hydroclimatic extremes in the Chao Phraya River Basin during 2002\u20132020","volume":"603","author":"Kinouchi","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/S1367-9120(02)00069-X","article-title":"The soil moisture distribution, thawing-freezing processes and their effects on the seasonal transition on the Qinghai-Xizang (Tibetan) Plateau","volume":"21","author":"Yang","year":"2003","journal-title":"J. Asian Earth Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/0273-1177(93)90548-P","article-title":"Development of global drought-watch system using NOAA\/AVHRR data","volume":"13","author":"Kogan","year":"1993","journal-title":"Adv. Space Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0273-1177(95)00079-T","article-title":"Application of vegetation index and brightness temperature for drought detection","volume":"15","author":"Kogan","year":"1995","journal-title":"Adv. Space Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"111813","DOI":"10.1016\/j.rse.2020.111813","article-title":"Agricultural drought mitigating indices derived from the changes in drought characteristics","volume":"244","author":"Wu","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1016\/j.jhydrol.2015.05.032","article-title":"Integrated index for drought assessment based on variable fuzzy set theory: A case study in the Yellow River basin, China","volume":"527","author":"Huang","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.apgeog.2019.01.005","article-title":"Mapping the agricultural drought based on the long-term AVHRR NDVI and North American Regional Reanalysis (NARR) in the United States, 1981\u20132013","volume":"104","author":"Lu","year":"2019","journal-title":"Appl. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2875","DOI":"10.1016\/j.rse.2010.07.005","article-title":"Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data","volume":"114","author":"Rhee","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1175\/JHM-D-12-0160.1","article-title":"A nonparametric multivariate multi-index drought monitoring framework","volume":"15","author":"Hao","year":"2014","journal-title":"J. Hydrometeorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"140701","DOI":"10.1016\/j.scitotenv.2020.140701","article-title":"Copula-based Joint Drought Index using SPI and EDDI and its application to climate change","volume":"744","author":"Won","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1016\/j.jhydrol.2015.05.031","article-title":"Drought characterization from a multivariate perspective: A review","volume":"527","author":"Hao","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"104394","DOI":"10.1016\/j.catena.2019.104394","article-title":"A remote sensing and artificial neural network-based integrated agricultural drought index: Index development and applications","volume":"186","author":"Liu","year":"2020","journal-title":"Catena"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.5194\/hess-15-2303-2011","article-title":"The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products","volume":"15","author":"Su","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.rse.2011.05.029","article-title":"Soil moisture mapping over the central part of the Tibetan Plateau using a series of ASAR WS images","volume":"120","author":"Su","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_37","first-page":"55","article-title":"Maqu network for validation of satellite-derived soil moisture products","volume":"17","author":"Dente","year":"2012","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5304","DOI":"10.1002\/jgrd.50468","article-title":"Evaluation of ECMWF\u2019s soil moisture analyses using observations on the Tibetan Plateau","volume":"118","author":"Su","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2937","DOI":"10.5194\/essd-12-2937-2020","article-title":"A long-term (2005\u20132016) dataset of hourly integrated land\u2013atmosphere interaction observations on the Tibetan Plateau","volume":"12","author":"Ma","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Zhang, H., Ding, M., Li, L., and Liu, L. (2019). Continuous wetting on the Tibetan Plateau during 1970\u20132017. Water, 11.","DOI":"10.3390\/w11122605"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"134230","DOI":"10.1016\/j.scitotenv.2019.134230","article-title":"Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia","volume":"699","author":"Rahmati","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_42","first-page":"273","article-title":"The responses of Pa, SPI, SPEI to dry climate in alpine meadows of eastern Qing-Tibet Plateau","volume":"34","author":"Zhao","year":"2017","journal-title":"Pratacultural Sci."},{"key":"ref_43","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_44","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.agrformet.2015.10.011","article-title":"Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions","volume":"216","author":"Park","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Gholami, R., and Nikoo, F. (2017). Support vector machine: Principles, parameters, and applications. Handbook of Neural Computation, Academic Press.","DOI":"10.1016\/B978-0-12-811318-9.00027-2"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Kramer, O. (2011, January 18\u201321). Dimensionality reduction by unsupervised k-nearest neighbor regression. Proceedings of the 2011 10th International Conference on Machine Learning and Applications and Workshops, Honolulu, HI, USA.","DOI":"10.1109\/ICMLA.2011.55"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). Xgboost. 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_48","doi-asserted-by":"crossref","unstructured":"Cheng, M., Zhong, L., Ma, Y., Zou, M., Ge, N., Wang, X., and Hu, Y. (2019). A study on the assessment of multi-source satellite soil moisture products and reanalysis data for the Tibetan Plateau. Remote Sens., 11.","DOI":"10.3390\/rs11101196"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Ge, N., Zhong, L., Ma, Y., Cheng, M., Wang, X., Zou, M., and Huang, Z. (2019). Estimation of land surface heat fluxes based on Landsat 7 ETM+ data and field measurements over the Northern Tibetan Plateau. Remote Sens., 11.","DOI":"10.3390\/rs11242899"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Shapley, L.S. (1953). A value for n-person games. Contributions to the Theory of Games, Princeton University Press.","DOI":"10.1515\/9781400881970-018"},{"key":"ref_51","unstructured":"Lundberg, S., and Lee, S.-I. (2017). A unified approach to interpreting model predictions. arXiv."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"149797","DOI":"10.1016\/j.scitotenv.2021.149797","article-title":"Interpretable and explainable AI (XAI) model for spatial drought prediction","volume":"801","author":"Dikshit","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3230829","article-title":"Integration of multisource data to estimate downward longwave radiation based on deep neural networks","volume":"60","author":"Zhu","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Dikshit, A., Pradhan, B., and Alamri, A.M. (2020). Temporal hydrological drought index forecasting for New South Wales, Australia using machine learning approaches. Atmosphere, 11.","DOI":"10.3390\/atmos11060585"},{"key":"ref_55","first-page":"322","article-title":"Comparative agricultural drought monitoring based on three machine learning methods","volume":"39","author":"Wang","year":"2022","journal-title":"Arid. Zone Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"119757","DOI":"10.1016\/j.conbuildmat.2020.119757","article-title":"Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method","volume":"260","author":"Wakim","year":"2020","journal-title":"Constr. Build. Mater."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/s11430-021-9822-y","article-title":"A daily drought index based on evapotranspiration and its application in regional drought analyses","volume":"65","author":"Zhang","year":"2022","journal-title":"Sci. China Earth Sci."},{"key":"ref_58","first-page":"86","article-title":"Remote sensing monitoring of drought level in North Tibet based on MODIS TVDI and fuzzy mathematics","volume":"37","author":"Liu","year":"2020","journal-title":"Arid. Zone Res."},{"key":"ref_59","first-page":"134","article-title":"Monitoring the droughts in Tibet based on remote sensing using MODIS data","volume":"27","author":"Liu","year":"2013","journal-title":"J. Arid. Land Resour. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1029\/WR016i002p00297","article-title":"On the definition of droughts","volume":"16","author":"Dracup","year":"1980","journal-title":"Water Resour."},{"key":"ref_61","unstructured":"Lundberg, S.M., Erion, G.G., and Lee, S.I. (2018). Consistent individualized feature attribution for tree ensembles. arXiv."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"105804","DOI":"10.1016\/j.catena.2021.105804","article-title":"A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China","volume":"209","author":"Tian","year":"2022","journal-title":"Catena"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"7628","DOI":"10.1002\/jgrd.50571","article-title":"Projection of occurrence of extreme dry-wet years and seasons in Europe with stationary and nonstationary Standardized Precipitation Indices","volume":"118","author":"Russo","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"125052","DOI":"10.1016\/j.jhydrol.2020.125052","article-title":"Investigating the impacts of climate change and human activities on hydrological drought using non-stationary approaches","volume":"588","author":"Jehanzaib","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1007\/s00477-020-01870-5","article-title":"Hydroclimatic aggregate drought index (HADI): A new approach for identification and categorization of drought in cold climate regions","volume":"34","author":"Bazrkar","year":"2020","journal-title":"Stoch. Environ. Res. Risk Assess."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/512\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:06:26Z","timestamp":1760119586000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/512"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,15]]},"references-count":65,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15020512"],"URL":"https:\/\/doi.org\/10.3390\/rs15020512","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,15]]}}}