{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T11:40:30Z","timestamp":1790250030985,"version":"4.1.0"},"reference-count":126,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC1507101"],"award-info":[{"award-number":["2018YFC1507101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41605042"],"award-info":[{"award-number":["41605042"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41875094"],"award-info":[{"award-number":["41875094"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Jiangsu Province, China","award":["BK20151525"],"award-info":[{"award-number":["BK20151525"]}]},{"DOI":"10.13039\/501100013088","name":"Qinglan Project of Jiangsu Province of China","doi-asserted-by":"publisher","award":["NON"],"award-info":[{"award-number":["NON"]}],"id":[{"id":"10.13039\/501100013088","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite-based precipitation products, especially those with high temporal and spatial resolution, constitute a potential alternative to sparse rain gauge networks for multidisciplinary research and applications. In this study, the validation of the 30-year Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) daily precipitation dataset was conducted over the Huai River Basin (HRB) of China. Based on daily precipitation data from 182 rain gauges, several continuous and categorical validation statistics combined with bias and error decomposition techniques were employed to quantitatively dissect the PERSIANN-CDR performance on daily, monthly, and annual scales. With and without consideration of non-rainfall data, this product reproduces adequate climatologic precipitation characteristics in the HRB, such as intra-annual cycles and spatial distributions. Bias analyses show that PERSIANN-CDR overestimates daily, monthly, and annual precipitation with a regional mean percent total bias of 11%. This is related closely to the larger positive false bias on the daily scale, while the negative non-false bias comes from a large underestimation of high percentile data despite overestimating lower percentile data. The systematic sub-component (error from high precipitation), which is independent of timescale, mainly leads to the PERSIANN-CDR total Mean-Square-Error (TMSE). Moreover, the daily TMSE is attributed to non-false error. The correlation coefficient (R) and Kling\u2013Gupta Efficiency (KGE) respectively suggest that this product can well capture the temporal variability of precipitation and has a moderate-to-high overall performance skill in reproducing precipitation. The corresponding capabilities increase from the daily to annual scale, but decrease with the specified precipitation thresholds. Overall, the PERSIANN-CDR product has good (poor) performance in detecting daily low (high) rainfall events on the basis of Probability of Detection, and it has a False Alarm Ratio of above 50% for each precipitation threshold. The Equitable Threat Score and Heidke Skill Score both suggest that PERSIANN-CDR has a certain ability to detect precipitation between the second and eighth percentiles. According to the Hanssen\u2013Kuipers Discriminant, this product can generally discriminate rainfall events between two thresholds. The Frequency Bias Index indicates an overestimation (underestimation) of precipitation totals in thresholds below (above) the seventh percentile. Also, continuous and categorical statistics for each month show evident intra-annual fluctuations. In brief, the comprehensive dissection of PERSIANN-CDR performance reported herein facilitates a valuable reference for decision-makers seeking to mitigate the adverse impacts of water deficit in the HRB and algorithm improvements in this product.<\/jats:p>","DOI":"10.3390\/rs11151805","type":"journal-article","created":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T11:39:37Z","timestamp":1564659577000},"page":"1805","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Dissecting Performances of PERSIANN-CDR Precipitation Product over Huai River Basin, China"],"prefix":"10.3390","volume":"11","author":[{"given":"Shanlei","family":"Sun","sequence":"first","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujia","family":"Zhou","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huayu","family":"Shen","sequence":"additional","affiliation":[{"name":"Ningbo Meteorological Bureau, Ningbo 315012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongfan","family":"Chai","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2403-3187","authenticated-orcid":false,"given":"Haishan","family":"Chen","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4345-0138","authenticated-orcid":false,"given":"Yibo","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wanrong","family":"Shi","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Wang","sequence":"additional","affiliation":[{"name":"Climate Center of Jiangsu Province, Meteorological Bureau, Nanjing 210008, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guojie","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters\/Key Laboratory of Meteorological Disaster, Ministry of Education\/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,1]]},"reference":[{"key":"ref_1","unstructured":"GCOS (2010). Implementation plan for the Global Observing System for Climate in Support of the UNFCCC, World Meteorological Organization. WMO Tech. Doc. WMO\/TD-1523."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-14-00283.1","article-title":"So How much of the Earth\u2019s surface is covered by rain gauges?","volume":"98","author":"Kidd","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_3","unstructured":"Janowiak, J.E., Xie, P., Joyce, R.J., Chen, M., and Yarosh, Y. (2004, January 21\u201326). Validation of satellite-derived rainfall estimates and numerical model forecasts of precipitation over the United States. Proceedings of the 29th Annual Climate Diagnostics and Prediction Workshop, Madison, WI, USA."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1175\/1525-7541(2003)004<1119:ANNATR>2.0.CO;2","article-title":"A neural network approach to real-time rainfall estimation for Africa using satellite data","volume":"4","author":"Grimes","year":"2003","journal-title":"J. Hydrometeorol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1002\/met.200","article-title":"Communicating the value of atmospheric services","volume":"17","author":"Thornes","year":"2010","journal-title":"Meteorol. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1175\/2011BAMS3158.1","article-title":"Advanced concepts on remote sensing of precipitation at multiple scales","volume":"92","author":"Sorooshian","year":"2011","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.rse.2015.01.016","article-title":"Correction of real-time satellite precipitation with multi-sensor satellite observations of land surface variables","volume":"160","author":"Wanders","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1175\/1525-7541(2003)004<1088:SREUCP>2.0.CO;2","article-title":"Satellite rainfall estimation using combined passive microwave and infrared algorithms","volume":"4","author":"Kidd","year":"2003","journal-title":"J. Hydrometeorol."},{"key":"ref_9","unstructured":"Field, C.B., Barros, V.R., Dokken, D.J., Mach, K.J., Mastrandrea, M.D., Bilir, T.E., Chatterjee, M., Ebi, K.L., Estrada, Y.O., and Genova, R.C. (2014). IPPC. Summary for policymakers. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part a: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1038\/nclimate2067","article-title":"Global warming and changes in drought","volume":"4","author":"Trenberth","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6554","DOI":"10.1002\/2016GL069386","article-title":"Role of ocean evaporation in California droughts and floods","volume":"43","author":"Wei","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Berghuijs, W.R., Aalbers, E.E., Larsen, J.R., Trancoso, R., and Woods, R.A. (2017). Recent changes in extreme floods across multiple continents. Environ. Res. Lett., 12.","DOI":"10.1088\/1748-9326\/aa8847"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3779","DOI":"10.1007\/s00382-016-3302-5","article-title":"On the coupling between precipitation and potential evapotranspiration: Contributions to decadal drought anomalies in the Southwest China","volume":"48","author":"Sun","year":"2017","journal-title":"Clim. Dyn."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/j.jhydrol.2018.10.071","article-title":"Revisiting the evolution of the 2009\u20132011 meteorological drought over Southwest China","volume":"568","author":"Sun","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hong, Y., Adler, R.F., Hossain, F., Curtis, S., and Huffman, G.J. (2007). A first approach to global runoff simulation using satellite rainfall estimation. Water Resour. Res., 43.","DOI":"10.1029\/2006WR005739"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1175\/JHM574.1","article-title":"Evaluation of PERSIANN-CCS rainfall measurement using the NAME event rain gauge network","volume":"8","author":"Hong","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1175\/2007JHM944.1","article-title":"Evaluation of TRMM multisatellite precipitation analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin","volume":"9","author":"Su","year":"2008","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Pan, M., Li, H., and Wood, E.F. (2010). Assessing the skill of satellite-based precipitation estimates in hydrologic applications. Water Resour. Res., 46.","DOI":"10.1029\/2009WR008290"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5801","DOI":"10.5194\/hess-22-5801-2018","article-title":"The PERSIANN family of global satellite precipitation data: A review and evaluation of products","volume":"22","author":"Nguyen","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2197","DOI":"10.1175\/2769.1","article-title":"GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates","volume":"16","author":"Xie","year":"2003","journal-title":"J. Clim."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1175\/1520-0477(1988)069<0753:AITSHG>2.0.CO;2","article-title":"An introduction to some historical governmental weather records of China","volume":"69","author":"Wang","year":"1988","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1126\/science.1140746","article-title":"How much more rain will global warming bring?","volume":"317","author":"Wentz","year":"2007","journal-title":"Science"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1175\/1525-7541(2001)002<0621:EORIC>2.0.CO;2","article-title":"Estimation of rainfall interstation correlation","volume":"2","author":"Habib","year":"2001","journal-title":"J. Hydrometeorol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1061\/(ASCE)1084-0699(2001)6:2(159)","article-title":"Sampling errors of tipping-bucket rain gauge measurements","volume":"6","author":"Habib","year":"2001","journal-title":"J. Hydrol. Eng."},{"key":"ref_25","unstructured":"Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tigora, M., and Miller, H.L. (2007). Climate Change 2007: The Physical Science Basis, Cambridge University Press."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"11775","DOI":"10.1029\/2001JD900066","article-title":"Scale issues in verification of precipitation forecasts","volume":"106","author":"Tustison","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1175\/1520-0434(2002)017<0927:WRCOTC>2.0.CO;2","article-title":"Weather radar coverage over the contiguous United States","volume":"17","author":"Maddox","year":"2002","journal-title":"Weather Forecast."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-13-00068.1","article-title":"PERSIANNCDR: Daily precipitation climate data record from multi-satellite observations for hydrological and climate studies","volume":"96","author":"Ashouri","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.atmosres.2009.08.017","article-title":"Precipitation: Measurement, Remote Sensing, Climatology and Modeling","volume":"94","author":"Michaelides","year":"2009","journal-title":"Atmos. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"6508","DOI":"10.1080\/01431161.2014.955147","article-title":"Understanding the dependence of the uncertainty in a satellite precipitation data set on the underlying surface and a correction method based on geographically weighted regression","volume":"35","author":"Xu","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.crte.2010.01.004","article-title":"Precipitation retrieval from space: An overview","volume":"342","author":"Prigent","year":"2010","journal-title":"Comptes Rendus Geosci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1007\/s10712-004-5724-6","article-title":"Overview of overland satellite rainfall estimation for hydro-meteorological applications","volume":"25","author":"Anagnostou","year":"2004","journal-title":"Surv. Geophys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1175\/JHM-D-13-0191.1","article-title":"Evaluation of multiple satellite-based precipitation products over complex topography","volume":"15","author":"Derin","year":"2014","journal-title":"J. Hydrometeorol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1175\/JHM-D-15-0094.1","article-title":"Estimating uncertainties in high-resolution satellite precipitation products: Systematic or random error?","volume":"17","author":"Maggioni","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1175\/BAMS-88-1-47","article-title":"Comparison of near-real-time precipitation estimates from satellite observations and numerical models","volume":"88","author":"Ebert","year":"2007","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-global, multi-year, combined-sensor precipitation at fine scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Xie, P.P., and Xiong., A.Y. (2011). A Conceptual model for constructing high-resolution gauge-satellite merged precipitation analyses. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2011JD016118"},{"key":"ref_39","first-page":"69","article-title":"Precipitation estimation from remotely sensed information using artificial neural networks","volume":"19","author":"Hsu","year":"1997","journal-title":"J. Hydrometeorol."},{"key":"ref_40","unstructured":"Huffman, G.J. (2019, June 10). README for Accessing Experimental Real-Time TRMM Multi-Satellite Precipitation Analysis (TMPA-RT) Data Sets, NASA Tech. Doc., Available online: ftp:\/\/meso-a.gsfc.nasa.gov\/pub\/trmmdocs\/rt\/3B4XRT_README.pdf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new enviromental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.5194\/hess-15-1109-2011","article-title":"Status of satellite precipitation retrievals","volume":"15","author":"Kidd","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.atmosres.2013.07.013","article-title":"The 183-WSL fast rain rate retrieval algorithm. Path II: Validation using ground radar measurements","volume":"134","author":"Laviola","year":"2013","journal-title":"Atmos. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"6201","DOI":"10.5194\/hess-21-6201-2017","article-title":"Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling","volume":"21","author":"Beck","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.atmosres.2013.11.011","article-title":"Evaluation and comparison of Satellite precipitation estimations with reference to a local area in the Mediterranean Sea","volume":"138","author":"Hsu","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Chen, F., and Li, X. (2016). Evaluation of IMERG and TRMM 3B43 monthly precipitation products over Mainland China. Remote Sens., 8.","DOI":"10.3390\/rs8060472"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2393","DOI":"10.1080\/02626667.2017.1384548","article-title":"Evaluation of gridded precipitation data in the Hindu Kush-Karakoram-Himalaya mountainous area","volume":"62","author":"Hussain","year":"2017","journal-title":"Hydrol. Sci. J."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Mayor, Y.G., Tereshchenko, I., Fonseca-Hern\u00e1ndez, M., Pantoja, D.A., and Montes, J.M. (2017). Evaluation of Error in IMERG Precipitation Estimates under Different Topographic Conditions and Temporal Scales over Mexico. Remote Sens., 9.","DOI":"10.3390\/rs9050503"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Omranian, E., and Sharif, H.O. (2018). Evaluation of the Global Precipitation Measurement (GPM) satellite rainfall products over the Lower Colorado River Basin, Texas. J. Am. Water Resour., 1\u201317.","DOI":"10.1111\/1752-1688.12610"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.atmosres.2018.10.012","article-title":"Evaluation of 3B42V7 and IMERG daily-precipitation products for a very high-precipitation region in northwestern South America","volume":"217","author":"Botero","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.atmosres.2018.02.020","article-title":"Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria","volume":"206","author":"Sharifi","year":"2018","journal-title":"Atmos. Res."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Zeng, Q., Wang, Y., Chen, L., Wang, Z., Zhu, H., and Li, B. (2018). Inter-comparison and evaluation of remote sensing precipitation products over China from 2005 to 2013. Remote Sens., 10.","DOI":"10.3390\/rs10020168"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Bai, P., and Liu, X. (2018). Evaluation of five satellite-based precipitation products in two gauge-scarce basins on the Tibetan Plateau. Remote Sens., 10.","DOI":"10.3390\/rs10081316"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"207","DOI":"10.5194\/hess-23-207-2019","article-title":"Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS","volume":"23","author":"Beck","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"8987","DOI":"10.1002\/2015JD023437","article-title":"Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data","volume":"120","author":"Sunilkumar","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_56","first-page":"179","article-title":"Evolution of temporal-spatial pattern of grain production and its driving mechanism in Huaihe River","volume":"36","author":"Gao","year":"2016","journal-title":"Bull. Soil Water Conserv."},{"key":"ref_57","first-page":"66","article-title":"Role of irrigation in crop yield in Huai River Basin","volume":"12","author":"Zhan","year":"2015","journal-title":"Zhi Huai"},{"key":"ref_58","first-page":"437","article-title":"The evaluation of the coordinating degree between agricultural production capacity and resource environment in Huaihe Basin","volume":"37","author":"Hu","year":"2016","journal-title":"Res. Agric. Mod."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Liu, J., Xu, Z., Bai, J., Peng, D., and Ren, M. (2018). Assessment and correction of the PERSIANN-CDR product in the Yarlung Zangbo River Basin, China. Remote Sens., 10.","DOI":"10.3390\/rs10122031"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"169","DOI":"10.5194\/hess-21-169-2017","article-title":"Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau","volume":"21","author":"Liu","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1175\/JHM-D-14-0174.1","article-title":"Evaluation of the PERSIANN-CDR daily rainfall estimates in capturing the behavior of extreme precipitation events over China","volume":"16","author":"Miao","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Guo, H., Bao, A., Liu, T., Chen, S., and Ndayisaba, F. (2016). Evaluation of PERSIANN-CDR for Meteorological Drought Monitoring over China. Remote Sens., 8.","DOI":"10.3390\/rs8050379"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Ghajarnia, N., Arasteh, P.D., Liaghat, M., and Araghinejad, S. (2018). Error analysis on PERSIANN precipitation estimations: Case study of Urmia Lake Basin, Iran. J. Hydrol. Eng., 23.","DOI":"10.1061\/(ASCE)HE.1943-5584.0001643"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1007\/s00704-016-2027-z","article-title":"Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan","volume":"131","author":"Hussain","year":"2018","journal-title":"Theor. Appl. Climatol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2061","DOI":"10.1175\/JHM-D-15-0192.1","article-title":"Assessing the efficacy of high-resolution satellite-based PERSIANN-CDR precipitation product in simulating streamflow","volume":"17","author":"Ashouri","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.quaint.2014.12.038","article-title":"Changes in extreme climate events in eastern China during 1960\u20132013: A case study of the Huaihe River Basin","volume":"380","author":"Zhang","year":"2015","journal-title":"Quat. Int."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1002\/joc.906","article-title":"Homogeneity of 20th century European daily temperature and precipitation series","volume":"23","author":"Wijngaard","year":"2003","journal-title":"Int. J. Climatol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.jaridenv.2013.05.013","article-title":"Evaluation of satellite-based precipitation estimation over Iran","volume":"97","author":"Nasrollahi","year":"2013","journal-title":"J. Arid Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jhydrol.2009.08.003","article-title":"Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling","volume":"377","author":"Gupta","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.5194\/hess-21-1295-2017","article-title":"Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile","volume":"21","author":"Nauditt","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.atmosres.2009.06.015","article-title":"Evaluation of TMPA satellite-based research and real-time rainfall estimates during six tropical related heavy rainfall events over Louisiana, USA","volume":"94","author":"Habib","year":"2009","journal-title":"Atmos. Res."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.jhydrol.2009.05.010","article-title":"Validation of NEXRAD multisensor precipitation estimates using an experimental dense rain gauge network in south Louisiana","volume":"373","author":"Habib","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1175\/1520-0493(1981)109<1081:OTRBSO>2.0.CO;2","article-title":"On the relationship between satellite-observed cloud cover and precipitation","volume":"109","author":"Richards","year":"1981","journal-title":"Mon. Weather Rev."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"2875","DOI":"10.1175\/1520-0477(1996)077<2875:RFTGAI>2.0.CO;2","article-title":"Results from the GPCP Algorithm Intercomparison Programme","volume":"77","author":"Ebert","year":"1996","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1175\/1520-0477(1994)075<0401:TGPCPF>2.0.CO;2","article-title":"The Global Precipitation Climatology Project: First Algorithm Intercomparison Project","volume":"75","author":"Arkin","year":"1994","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1175\/2008JHM1052.1","article-title":"An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data","volume":"10","author":"Sapiano","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1175\/1520-0434(2003)018<1037:SAOOOS>2.0.CO;2","article-title":"Status and outlook of operational satellite precipitation algorithms for extreme-precipitation events","volume":"18","author":"Scofield","year":"2003","journal-title":"Weather Forecast."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1175\/2009JAMC2291.1","article-title":"Daytime Precipitation estimation using bispectral cloud classification system","volume":"49","author":"Behrangi","year":"2010","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1872","DOI":"10.1175\/JHM-D-12-0172.1","article-title":"An artificial neural network model to reduce false alarms in satellite precipitation products using MODIS and CloudSat observations","volume":"14","author":"Nasrollahi","year":"2013","journal-title":"J. Hydrometeorol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1175\/1520-0469(2001)058<0742:ACSIAP>2.0.CO;2","article-title":"Combined satellite infrared and passive microwave technique for estimation of small-scale rainfall","volume":"18","author":"Todd","year":"2001","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1175\/JAMC-D-13-069.1","article-title":"Combining satellite infrared and lightning information to estimate warm-season convective and stratiform rainfall","volume":"53","author":"Xu","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1175\/JHM-D-15-0075.1","article-title":"A Deep Neural Network Modeling Framework to Reduce Bias in Satellite Precipitation Products","volume":"17","author":"Tao","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1175\/JHM-D-15-0186.1","article-title":"Improvements to the GOES-R Rainfall Rate Algorithm","volume":"17","author":"Kuligowski","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1175\/JAMC-D-12-0107.1","article-title":"Impact of TRMM data on a low-latency, high-resolution precipitation algorithm for flash-flood forecasting","volume":"52","author":"Kuligowski","year":"2013","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_85","unstructured":"Lin, Y., and Mitchell, K.E. (2005, January 9\u201313). The NCEP stage II\/IV hourly precipitation analyses: Development and applications. Preprints. Proceedings of the 19th Conference on Hydrology, San Diego, CA, USA. Available online: https:\/\/ams.confex.com\/ams\/pdfpapers\/83847.pdf."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/JHM-D-17-0069.1","article-title":"Improving the quality of heavy precipitation estimates from satellite passive microwave rainfall retrievals","volume":"19","author":"Kummerow","year":"2018","journal-title":"J. Hydrometeorol."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1080\/01431160010006935","article-title":"The role of orographic and parallax corrections on real time high resolution satellite rainfall rate distribution","volume":"23","author":"Vicente","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1834","DOI":"10.1175\/JAM2173.1","article-title":"Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system","volume":"43","author":"Hong","year":"2004","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1626","DOI":"10.1175\/JAM2283.1","article-title":"Effect of temporal sampling on inferred rainfall spatial statistics","volume":"44","author":"Gebremichael","year":"2005","journal-title":"J. Appl. Meteorol."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Villarini, G., and Krajewski, W.F. (2007). Evaluation of the research version TMPA three-hourly 0.25\u00b0 \u00d7 0.25\u00b0 rainfall estimates over Oklahoma. Geophys. Res. Lett., 34.","DOI":"10.1029\/2006GL029147"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1016\/j.jhydrol.2017.09.050","article-title":"Effect of temporal aggregation on the estimate of annual maximum rainfall depths for the design of hydraulic infrastructure systems","volume":"554","author":"Morbidelli","year":"2017","journal-title":"J. Hydrol."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.advwatres.2018.10.027","article-title":"Influence of temporal data aggregation on trend estimation for intense rainfall","volume":"122","author":"Morbidelli","year":"2018","journal-title":"Adv. Water Resour."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1175\/1520-0434(1998)013<0377:TWRA>2.0.CO;2","article-title":"The WSR-88D rainfall algorithm","volume":"13","author":"Fulton","year":"1998","journal-title":"Weather Forecast."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1175\/WAF-D-14-00112.1","article-title":"Assessment and implications of NCEP Stage IV quantitative precipitation estimates for product intercomparisons","volume":"31","author":"Nelson","year":"2016","journal-title":"Weather Forecast."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1175\/2007JTECHA910.1","article-title":"Calibration assessment of ISCCP geostationary infrared observations using HIRS","volume":"25","author":"Knapp","year":"2008","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Knapp, K.R. (2008). Scientific data stewardship of International Satellite Cloud Climatology Project B1 global geostationary observations. J. Appl. Remote Sens., 2.","DOI":"10.1117\/1.3043461"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Knapp, K.R. (2012). Inter-satellite bias of the high resolution infrared radiation sounder water vapor channel determined using ISCCP B1 data. J. Appl. Remote Sens., 6.","DOI":"10.1117\/1.JRS.6.063523"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1175\/2011BAMS3039.1","article-title":"Globally gridded satellite observations for climate studies","volume":"92","author":"Knapp","year":"2011","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1175\/1520-0450(2001)040<0689:LASDZA>2.0.CO;2","article-title":"Latitudinally and seasonally dependent zenith-angle corrections for geostationary satellite IR brightness temperatures","volume":"40","author":"Joyce","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1175\/JHM-392.1","article-title":"Comparison of the GPCP and CMAP merged gauge-satellite monthly precipitation products for the period 1979\u20132001","volume":"5","author":"Yin","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1175\/2008JHM1023.1","article-title":"Comparison of Precipitation Datasets over the Tropical South American and African Continents","volume":"10","author":"Juarez","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Ma, L., Zhang, T., Frauenfeld, O.W., Ye, B., Yang, D., and Qin, D. (2009). Evaluation of precipitation from the ERA-40, NCEP-1, and NCEP-2 Reanalyses and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China. J. Geophys. Res. Atmos., 114.","DOI":"10.1029\/2008JD011178"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1002\/qj.2634","article-title":"Assessment of summer monsoon precipitation derived from five reanalysis datasets over East Asia","volume":"142","author":"Huang","year":"2016","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Wang, G., Zhang, P., Liang, L., and Zhang, S. (2017). Evaluation of precipitation from CMORPH, GPCP-2, TRMM 3B43, GPCC, and ITPCAS with ground-based measurements in the Qinling-Daba Mountains, China. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0185147"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Simmons, A.J., Willett, K.M., Jones, P.D., Thorne, P.W., and Dee, D.P. (2010). Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets. J. Geophys. Res. Atmos., 115.","DOI":"10.1029\/2009JD012442"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"1654","DOI":"10.1175\/JCLI-D-12-00239.1","article-title":"The role of mesoscale convective complexes in southern Africa summer rainfall","volume":"26","author":"Blamey","year":"2012","journal-title":"J. Clim."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1029\/1999JD900228","article-title":"Numerical simulation studies of rain gauge data correction due to wind effect","volume":"104","author":"Habib","year":"1999","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Adam, J.C., and Lettenmaier, D.P. (2003). Adjustment of global gridded precipitation for systematic bias. J. Geophys. Res. Atmos., 108.","DOI":"10.1029\/2002JD002499"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1175\/1520-0426(2003)20<752:LREITB>2.0.CO;2","article-title":"Local random errors in tipping-bucket rain gauge measurements","volume":"20","author":"Ciach","year":"2003","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1002\/joc.4045","article-title":"Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region","volume":"35","author":"Ma","year":"2015","journal-title":"Intent. J. Climatol."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.jhydrol.2018.02.057","article-title":"Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products","volume":"559","author":"Tang","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"2487","DOI":"10.1029\/1999WR900142","article-title":"Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation","volume":"35","author":"Steiner","year":"1999","journal-title":"Water Resour. Res."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"531","DOI":"10.5194\/hess-4-531-2000","article-title":"Accuracy of rainfall measurement for scales of hydrological interest","volume":"4","author":"Wood","year":"2000","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_114","doi-asserted-by":"crossref","unstructured":"Villarini, G., Mandapaka, P.V., Krajewski, W.F., and Moore, R.J. (2008). Rainfall and sampling uncertainties: A rain gauge perspective. J. Geophys. Res. Atmos., 113.","DOI":"10.1029\/2007JD009214"},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"3863","DOI":"10.1029\/2017WR022421","article-title":"Quantifying and mitigating wind-Induced undercatch in rainfall measurements","volume":"54","author":"Pollock","year":"2018","journal-title":"Water Resour. Res."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.atmosres.2016.04.016","article-title":"Assessment of measurement errors and dynamic calibration methods for three different tipping bucket rain gauges","volume":"178","author":"Shedekar","year":"2016","journal-title":"Atmos. Res."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1002\/wea.875","article-title":"Rainfall measurement revisited","volume":"67","author":"Rodda","year":"2012","journal-title":"Weather"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"1734","DOI":"10.1175\/JCLI4092.1","article-title":"Spatial and temporal patterns of precipitation intensity as observed by the NAME event rain gauge network from 2002 to 2004","volume":"20","author":"Gochis","year":"2007","journal-title":"J. Clim."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1175\/1525-7541(2001)002<0122:ABCSRP>2.0.CO;2","article-title":"A bias-corrected Siberian regional precipitation climatology","volume":"2","author":"Yang","year":"2001","journal-title":"J. Hydrometeorol."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"3253","DOI":"10.1029\/2001WR000541","article-title":"Comparative rainfall observations from pit and aboveground rain gauges with and without wind shields","volume":"37","author":"Duchon","year":"2001","journal-title":"Water Resour. Res."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1175\/1520-0426(1999)016<0450:EOWIEO>2.0.CO;2","article-title":"Estimation of wind-induced error of rainfall gauge measurements using a numerical simulation","volume":"16","author":"Sevruk","year":"1999","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Sieck, L.C., Burges, S.J., and Steiner, M. (2007). Challenges in obtaining reliable measurements of point rainfall. Water Resour. Res., 43.","DOI":"10.1029\/2005WR004519"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1002\/hyp.5539","article-title":"Field assessments on the accuracy of spherical gauges in rainfall measurements","volume":"19","author":"Chang","year":"2005","journal-title":"Hydrol. Process."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1175\/1520-0477(1991)072<1725:OBOPMA>2.0.CO;2","article-title":"Overcoming biases of precipitation measurement: A history of the USSR experience","volume":"72","author":"Groisman","year":"1991","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1002\/joc.3370060607","article-title":"A homogeneity test applied to precipitation data","volume":"6","author":"Alexandersson","year":"1986","journal-title":"J. Clim."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1007\/s11442-012-0948-8","article-title":"Development of China homogenized monthly precipitation dataset during 1900\u20132009","volume":"22","author":"Li","year":"2012","journal-title":"J. Geogr. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1805\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:12:20Z","timestamp":1760188340000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1805"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,1]]},"references-count":126,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["rs11151805"],"URL":"https:\/\/doi.org\/10.3390\/rs11151805","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,1]]}}}