{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T23:08:39Z","timestamp":1773184119761,"version":"3.50.1"},"reference-count":99,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,6]],"date-time":"2021-10-06T00:00:00Z","timestamp":1633478400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,6]],"date-time":"2021-10-06T00:00:00Z","timestamp":1633478400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Earth Sci Inform"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12145-021-00669-4","type":"journal-article","created":{"date-parts":[[2021,10,6]],"date-time":"2021-10-06T06:33:26Z","timestamp":1633502006000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["A review of downscaling methods of satellite-based precipitation estimates"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7926-1219","authenticated-orcid":false,"given":"Arman","family":"Abdollahipour","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0314-1012","authenticated-orcid":false,"given":"Hassan","family":"Ahmadi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9411-9413","authenticated-orcid":false,"given":"Babak","family":"Aminnejad","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,6]]},"reference":[{"issue":"4","key":"669_CR1","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1016\/j.rse.2006.10.006","volume":"107","author":"N Agam","year":"2007","unstructured":"Agam N, Kustas WP, Anderson MC, Li F, Neale CM (2007) A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sens Environ 107(4):545\u2013558. https:\/\/doi.org\/10.1016\/j.rse.2006.10.006","journal-title":"Remote Sens Environ"},{"issue":"2","key":"669_CR2","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1111\/j.1538-4632.1995.tb00338.x","volume":"27","author":"L Anselin","year":"1995","unstructured":"Anselin L (1995) Local indicators of spatial association\u2014LISA. Geogr Anal 27(2):93\u2013115. https:\/\/doi.org\/10.1111\/j.1538-4632.1995.tb00338.x","journal-title":"Geogr Anal"},{"key":"669_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2021.147140","volume":"784","author":"A Arshad","year":"2021","unstructured":"Arshad A, Zhang W, Zhang Z, Wang S, Zhang B, Cheema MJM, Shalamzari MJ (2021) Reconstructing high-resolution gridded precipitation data using an improved downscaling approach over the high altitude mountain regions of Upper Indus Basin (UIB). Sci Total Environ 784:147140. https:\/\/doi.org\/10.1016\/j.scitotenv.2021.147140","journal-title":"Sci Total Environ"},{"key":"669_CR4","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.jag.2012.04.012","volume":"22","author":"PM Atkinson","year":"2013","unstructured":"Atkinson PM (2013) Downscaling in remote sensing. Int J Appl Earth Obs Geoinf 22:106\u2013114. https:\/\/doi.org\/10.1016\/j.jag.2012.04.012","journal-title":"Int J Appl Earth Obs Geoinf"},{"issue":"2","key":"669_CR5","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.rse.2005.10.025","volume":"100","author":"NA Brunsell","year":"2006","unstructured":"Brunsell NA (2006) Characterization of land-surface precipitation feedback regimes with remote sensing. Remote Sens Environ 100(2):200\u2013211. https:\/\/doi.org\/10.1016\/j.rse.2005.10.025","journal-title":"Remote Sens Environ"},{"issue":"8","key":"669_CR6","doi-asserted-by":"publisher","first-page":"2603","DOI":"10.1080\/01431161.2011.617397","volume":"33","author":"MJM Cheema","year":"2012","unstructured":"Cheema MJM, Bastiaanssen WG (2012) Local calibration of remotely sensed rainfall from the TRMM satellite for different periods and spatial scales in the Indus Basin. Int J Remote Sens 33(8):2603\u20132627. https:\/\/doi.org\/10.1080\/01431161.2011.617397","journal-title":"Int J Remote Sens"},{"issue":"9","key":"669_CR7","doi-asserted-by":"publisher","first-page":"3074","DOI":"10.1080\/01431161.2014.902550","volume":"35","author":"F Chen","year":"2014","unstructured":"Chen F, Liu Y, Liu Q, Li X (2014) Spatial downscaling of TRMM 3B43 precipitation considering spatial heterogeneity. Int J Remote Sens 35(9):3074\u20133093. https:\/\/doi.org\/10.1080\/01431161.2014.902550","journal-title":"Int J Remote Sens"},{"key":"669_CR8","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.rse.2018.05.021","volume":"214","author":"Y Chen","year":"2018","unstructured":"Chen Y, Huang J, Sheng S, Mansaray LR, Liu Z, Wu H, Wang X (2018) A new downscaling-integration framework for high-resolution monthly precipitation estimates: combining rain gauge observations, satellite-derived precipitation data and geographical ancillary data. Remote Sens Environ 214:154\u2013172. https:\/\/doi.org\/10.1016\/j.rse.2018.05.021","journal-title":"Remote Sens Environ"},{"issue":"3","key":"669_CR9","doi-asserted-by":"publisher","first-page":"568","DOI":"10.3390\/w11030568","volume":"11","author":"S Chen","year":"2019","unstructured":"Chen S, Zhang L, She D, Chen J (2019) Spatial Downscaling of Tropical Rainfall Measuring Mission (TRMM) annual and monthly precipitation data over the middle and lower reaches of the Yangtze River Basin, China. Water 11(3):568. https:\/\/doi.org\/10.3390\/w11030568","journal-title":"Water"},{"issue":"7","key":"669_CR10","doi-asserted-by":"publisher","first-page":"1696","DOI":"10.1002\/joc.3543","volume":"33","author":"XW Chuai","year":"2013","unstructured":"Chuai XW, Huang XJ, Wang WJ, Bao G (2013) NDVI, temperature and precipitation changes and their relationships with different vegetation types during 1998\u20132007 in Inner Mongolia, China. Int J Climatol 33(7):1696\u20131706. https:\/\/doi.org\/10.1002\/joc.3543","journal-title":"Int J Climatol"},{"key":"669_CR11","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.atmosres.2017.02.011","volume":"190","author":"M Darand","year":"2017","unstructured":"Darand M, Amanollahi J, Zandkarimi S (2017) Evaluation of the performance of TRMM Multi-satellite Precipitation Analysis (TMPA) estimation over Iran. Atmos Res 190:121\u2013127. https:\/\/doi.org\/10.1016\/j.atmosres.2017.02.011","journal-title":"Atmos Res"},{"key":"669_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.rse.2012.12.002","volume":"131","author":"Z Duan","year":"2013","unstructured":"Duan Z, Bastiaanssen WGM (2013) First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling\u2013calibration procedure. Remote Sens Environ 131:1\u201313. https:\/\/doi.org\/10.1016\/j.rse.2012.12.002","journal-title":"Remote Sens Environ"},{"key":"669_CR13","doi-asserted-by":"publisher","first-page":"1536","DOI":"10.1016\/j.scitotenv.2016.08.213","volume":"573","author":"Z Duan","year":"2016","unstructured":"Duan Z, Liu J, Tuo Y, Chiogna G, Disse M (2016) Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales. Sci Total Environ 573:1536\u20131553. https:\/\/doi.org\/10.1016\/j.scitotenv.2016.08.213","journal-title":"Sci Total Environ"},{"key":"669_CR14","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.advwatres.2013.08.011","volume":"61","author":"J Fang","year":"2013","unstructured":"Fang J, Du J, Xu W, Shi P, Li M, Ming X (2013) Spatial downscaling of TRMM precipitation data based on the orographical effect and meteorological conditions in a mountainous area. Adv Water Resour 61:42\u201350. https:\/\/doi.org\/10.1016\/j.advwatres.2013.08.011","journal-title":"Adv Water Resour"},{"issue":"3","key":"669_CR15","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.rse.2003.08.004","volume":"88","author":"GM Foody","year":"2003","unstructured":"Foody GM (2003) Geographical weighting as a further refinement to regression modelling: an example focused on the NDVI\u2013rainfall relationship. Remote Sens Environ 88(3):283\u2013293. https:\/\/doi.org\/10.1016\/j.rse.2003.08.004","journal-title":"Remote Sens Environ"},{"issue":"1","key":"669_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2015.66","volume":"2","author":"C Funk","year":"2015","unstructured":"Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison L, Hoell A, Michaelsen J (2015) The climate hazards infrared precipitation with stations\u2014a new environmental record for monitoring extremes. Sci Data 2(1):1\u201321. https:\/\/doi.org\/10.1038\/sdata.2015.66","journal-title":"Sci Data"},{"key":"669_CR17","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.ecolind.2012.02.007","volume":"20","author":"Y Gao","year":"2012","unstructured":"Gao Y, Huang J, Li S, Li S (2012) Spatial pattern of non-stationarity and scale-dependent relationships between NDVI and climatic factors\u2014A case study in Qinghai-Tibet Plateau, China. Ecol Ind 20:170\u2013176. https:\/\/doi.org\/10.1016\/j.ecolind.2012.02.007","journal-title":"Ecol Ind"},{"issue":"3\u20134","key":"669_CR18","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1016\/j.atmosres.2007.11.028","volume":"88","author":"M Gebremichael","year":"2008","unstructured":"Gebremichael M, Krajewski WF, Over TM, Takayabu YN, Arkin P, Katayama M (2008) Scaling of tropical rainfall as observed by TRMM precipitation radar. Atmos Res 88(3\u20134):337\u2013354. https:\/\/doi.org\/10.1016\/j.atmosres.2007.11.028","journal-title":"Atmos Res"},{"issue":"1","key":"669_CR19","doi-asserted-by":"publisher","first-page":"61","DOI":"10.5194\/esd-6-61-2015","volume":"6","author":"L Gerlitz","year":"2015","unstructured":"Gerlitz L, Conrad O, B\u00f6hner J (2015) Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia-a neural-network-based approach. Earth Syst Dyn 6(1):61. https:\/\/doi.org\/10.5194\/esd-6-61-2015","journal-title":"Earth Syst Dyn"},{"issue":"1\u20132","key":"669_CR20","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/S0022-1694(00)00144-X","volume":"228","author":"P Goovaerts","year":"2000","unstructured":"Goovaerts P (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J Hydrol 228(1\u20132):113\u2013129. https:\/\/doi.org\/10.1016\/S0022-1694(00)00144-X","journal-title":"J Hydrol"},{"issue":"1","key":"669_CR21","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s11004-007-9129-1","volume":"40","author":"P Goovaerts","year":"2008","unstructured":"Goovaerts P (2008) Kriging and semivariogram deconvolution in the presence of irregular geographical units. Math Geosci 40(1):101\u2013128. https:\/\/doi.org\/10.1007\/s11004-007-9129-1","journal-title":"Math Geosci"},{"issue":"6","key":"669_CR22","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1007\/s11004-010-9284-7","volume":"42","author":"P Harris","year":"2010","unstructured":"Harris P, Fotheringham AS, Crespo R, Charlton M (2010) The use of geographically weighted regression for spatial prediction: an evaluation of models using simulated data sets. Math Geosci 42(6):657\u2013680. https:\/\/doi.org\/10.1007\/s11004-010-9284-7","journal-title":"Math Geosci"},{"issue":"12","key":"669_CR23","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1175\/JAM2173.1","volume":"43","author":"Y Hong","year":"2004","unstructured":"Hong Y, Hsu KL, Sorooshian S, Gao X (2004) Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J Appl Meteorol 43(12):1834\u20131853. https:\/\/doi.org\/10.1175\/JAM2173.1","journal-title":"J Appl Meteorol"},{"issue":"9","key":"669_CR24","doi-asserted-by":"publisher","first-page":"1176","DOI":"10.1175\/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2","volume":"36","author":"KL Hsu","year":"1997","unstructured":"Hsu KL, Gao X, Sorooshian S, Gupta HV (1997) Precipitation estimation from remotely sensed information using artificial neural networks. J Appl Meteorol 36(9):1176\u20131190. https:\/\/doi.org\/10.1175\/1520-0450(1997)036%3c1176:PEFRSI%3e2.0.CO;2","journal-title":"J Appl Meteorol"},{"issue":"5","key":"669_CR25","doi-asserted-by":"publisher","first-page":"1605","DOI":"10.1029\/1999WR900032","volume":"35","author":"KL Hsu","year":"1999","unstructured":"Hsu KL, Gupta HV, Gao X, Sorooshian S (1999) Estimation of physical variables from multichannel remotely sensed imagery using a neural network: application to rainfall estimation. Water Resour Res 35(5):1605\u20131618. https:\/\/doi.org\/10.1029\/1999WR900032","journal-title":"Water Resour Res"},{"issue":"1","key":"669_CR26","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1175\/JHM560.1","volume":"8","author":"GJ Huffman","year":"2007","unstructured":"Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF (2007) The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38\u201355. https:\/\/doi.org\/10.1175\/JHM560.1","journal-title":"J Hydrometeorol"},{"key":"669_CR27","unstructured":"Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Xie P, Yoo SH (2015) NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG).\u00a0Algorithm Theoretical Basis Document (ATBD) Version,\u00a04, p.26."},{"key":"669_CR28","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.rse.2016.03.006","volume":"178","author":"C Hutengs","year":"2016","unstructured":"Hutengs C, Vohland M (2016) Downscaling land surface temperatures at regional scales with random forest regression. Remote Sens Environ 178:127\u2013141. https:\/\/doi.org\/10.1016\/j.rse.2016.03.006","journal-title":"Remote Sens Environ"},{"issue":"2","key":"669_CR29","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.rse.2008.10.004","volume":"113","author":"WW Immerzeel","year":"2009","unstructured":"Immerzeel WW, Rutten MM, Droogers P (2009) Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula. Remote Sens Environ 113(2):362\u2013370. https:\/\/doi.org\/10.1016\/j.rse.2008.10.004","journal-title":"Remote Sens Environ"},{"issue":"12","key":"669_CR30","doi-asserted-by":"publisher","first-page":"3069","DOI":"10.1016\/j.rse.2011.06.009","volume":"115","author":"S Jia","year":"2011","unstructured":"Jia S, Zhu W, L\u0171 A, Yan T (2011) A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China. Remote Sens Environ 115(12):3069\u20133079. https:\/\/doi.org\/10.1016\/j.rse.2011.06.009","journal-title":"Remote Sens Environ"},{"issue":"4","key":"669_CR31","doi-asserted-by":"publisher","first-page":"579","DOI":"10.3390\/rs10040579","volume":"10","author":"Y Jin","year":"2018","unstructured":"Jin Y, Ge Y, Wang J, Heuvelink G, Wang L (2018) Geographically weighted area-to-point regression kriging for spatial downscaling in remote sensing. Remote Sens 10(4):579. https:\/\/doi.org\/10.3390\/rs10040579","journal-title":"Remote Sens"},{"issue":"8","key":"669_CR32","doi-asserted-by":"publisher","first-page":"655","DOI":"10.3390\/rs8080655","volume":"8","author":"W Jing","year":"2016","unstructured":"Jing W, Yang Y, Yue X, Zhao X (2016a) A spatial downscaling algorithm for satellite-based precipitation over the Tibetan plateau based on NDVI, DEM, and land surface temperature. Remote Sens 8(8):655. https:\/\/doi.org\/10.3390\/rs8080655","journal-title":"Remote Sens"},{"issue":"10","key":"669_CR33","doi-asserted-by":"publisher","first-page":"835","DOI":"10.3390\/rs8100835","volume":"8","author":"W Jing","year":"2016","unstructured":"Jing W, Yang Y, Yue X, Zhao X (2016b) A comparison of different regression algorithms for downscaling monthly satellite-based precipitation over North China. Remote Sens 8(10):835. https:\/\/doi.org\/10.3390\/rs8100835","journal-title":"Remote Sens"},{"issue":"3","key":"669_CR34","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","volume":"5","author":"RJ Joyce","year":"2004","unstructured":"Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5(3):487\u2013503. https:\/\/doi.org\/10.1175\/1525-7541(2004)005%3c0487:CAMTPG%3e2.0.CO;2","journal-title":"J Hydrometeorol"},{"issue":"3","key":"669_CR35","doi-asserted-by":"publisher","first-page":"215","DOI":"10.3390\/rs8030215","volume":"8","author":"Y Ke","year":"2016","unstructured":"Ke Y, Im J, Park S, Gong H (2016) Downscaling of MODIS One kilometer evapotranspiration using Landsat-8 data and machine learning approaches. Remote Sens 8(3):215. https:\/\/doi.org\/10.3390\/rs8030215","journal-title":"Remote Sens"},{"key":"669_CR36","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/j.jhydrol.2012.07.024","volume":"464","author":"M Kizza","year":"2012","unstructured":"Kizza M, Westerberg I, Rodhe A, Ntale HK (2012) Estimating areal rainfall over Lake Victoria and its basin using ground-based and satellite data. J Hydrol 464:401\u2013411. https:\/\/doi.org\/10.1016\/j.jhydrol.2012.07.024","journal-title":"J Hydrol"},{"issue":"7","key":"669_CR37","doi-asserted-by":"publisher","first-page":"2259","DOI":"10.1109\/TGRS.2007.895337","volume":"45","author":"T Kubota","year":"2007","unstructured":"Kubota T, Shige S, Hashizume H, Aonashi K, Takahashi N, Seto S, Hirose M, Takayabu YN, Ushio T, Nakagawa K, Iwanami K (2007) Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation. IEEE Trans Geosci Remote Sens 45(7):2259\u20132275. https:\/\/doi.org\/10.1109\/TGRS.2007.895337","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"669_CR38","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-6849-3","volume-title":"Applied predictive modeling","author":"M Kuhn","year":"2013","unstructured":"Kuhn M, Johnson K (2013) Applied predictive modeling, vol 26. Springer, New York"},{"key":"669_CR39","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.chemosphere.2014.12.027","volume":"127","author":"S Kumar","year":"2015","unstructured":"Kumar S (2015) Estimating spatial distribution of soil organic carbon for the Midwestern United States using historical database. Chemosphere 127:49\u201357. https:\/\/doi.org\/10.1016\/j.chemosphere.2014.12.027","journal-title":"Chemosphere"},{"key":"669_CR40","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1016\/j.geoderma.2012.05.022","volume":"189","author":"S Kumar","year":"2012","unstructured":"Kumar S, Lal R, Liu D (2012) A geographically weighted regression kriging approach for mapping soil organic carbon stock. Geoderma 189:627\u2013634. https:\/\/doi.org\/10.1016\/j.geoderma.2012.05.022","journal-title":"Geoderma"},{"issue":"4","key":"669_CR41","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1016\/S0034-4257(03)00036-1","volume":"85","author":"WP Kustas","year":"2003","unstructured":"Kustas WP, Norman JM, Anderson MC, French AN (2003) Estimating subpixel surface temperatures and energy fluxes from the vegetation index\u2013radiometric temperature relationship. Remote Sens Environ 85(4):429\u2013440. https:\/\/doi.org\/10.1016\/S0034-4257(03)00036-1","journal-title":"Remote Sens Environ"},{"key":"669_CR42","doi-asserted-by":"publisher","DOI":"10.7780\/kjrs.2018.34.1.6","author":"GH Kwak","year":"2018","unstructured":"Kwak GH, Park NW, Kyriakidis P (2018) Development of an R-based spatial downscaling tool to predict fine scale information from coarse scale satellite products. J Remote Sens. https:\/\/doi.org\/10.7780\/kjrs.2018.34.1.6","journal-title":"J Remote Sens"},{"issue":"3","key":"669_CR43","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1111\/j.1538-4632.2004.tb01135.x","volume":"36","author":"PC Kyriakidis","year":"2004","unstructured":"Kyriakidis PC (2004) A geostatistical framework for area-to-point spatial interpolation. Geogr Anal 36(3):259\u2013289. https:\/\/doi.org\/10.1111\/j.1538-4632.2004.tb01135.x","journal-title":"Geogr Anal"},{"issue":"11","key":"669_CR44","doi-asserted-by":"publisher","first-page":"1855","DOI":"10.1175\/1520-0450(2001)040<1855:GMOPFR>2.0.CO;2","volume":"40","author":"PC Kyriakidis","year":"2001","unstructured":"Kyriakidis PC, Kim J, Miller NL (2001) Geostatistical mapping of precipitation from rain gauge data using atmospheric and terrain characteristics. J Appl Meteorol 40(11):1855\u20131877. https:\/\/doi.org\/10.1175\/1520-0450(2001)040%3c1855:GMOPFR%3e2.0.CO;2","journal-title":"J Appl Meteorol"},{"key":"669_CR45","unstructured":"Levine N (2004) CrimeStat III: a spatial statistics program for the analysis of crime incident locations (version 3.0). Houston (TX): Ned Levine & Associates\/Washington, DC: National Institute of Justice."},{"issue":"1\u20134","key":"669_CR46","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.jhydrol.2010.01.023","volume":"385","author":"M Li","year":"2010","unstructured":"Li M, Shao Q (2010) An improved statistical approach to merge satellite rainfall estimates and rain gauge data. J Hydrol 385(1\u20134):51\u201364. https:\/\/doi.org\/10.1016\/j.jhydrol.2010.01.023","journal-title":"J Hydrol"},{"issue":"5","key":"669_CR47","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1080\/014311602753474192","volume":"23","author":"BG Li","year":"2002","unstructured":"Li BG, Tao S, Dawson RW (2002) Relations between AVHRR NDVI and ecoclimatic parameters in China. Int J Remote Sens 23(5):989\u2013999. https:\/\/doi.org\/10.1080\/014311602753474192","journal-title":"Int J Remote Sens"},{"issue":"3","key":"669_CR48","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1007\/s11769-019-1033-3","volume":"29","author":"Y Li","year":"2019","unstructured":"Li Y, Zhang Y, He D, Luo X, Ji X (2019) Spatial downscaling of the tropical rainfall measuring mission precipitation using geographically weighted regression Kriging over the Lancang River Basin, China. Chin Geogr Sci 29(3):446\u2013462. https:\/\/doi.org\/10.1007\/s11769-019-1033-3","journal-title":"Chin Geogr Sci"},{"issue":"14","key":"669_CR49","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1029\/94JD00483","volume":"99","author":"X Liang","year":"1994","unstructured":"Liang X, Xie Z, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99(14):415\u2013514. https:\/\/doi.org\/10.1029\/94JD00483","journal-title":"J Geophys Res"},{"issue":"3","key":"669_CR50","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1016\/j.cageo.2007.12.015","volume":"35","author":"Y Liu","year":"2009","unstructured":"Liu Y, Journel AG (2009) A package for geostatistical integration of coarse and fine scale data. Comput Geosci 35(3):527\u2013547. https:\/\/doi.org\/10.1016\/j.cageo.2007.12.015","journal-title":"Comput Geosci"},{"issue":"1\u20134","key":"669_CR51","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.jhydrol.2004.10.026","volume":"308","author":"CD Lloyd","year":"2005","unstructured":"Lloyd CD (2005) Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. J Hydrol 308(1\u20134):128\u2013150. https:\/\/doi.org\/10.1016\/j.jhydrol.2004.10.026","journal-title":"J Hydrol"},{"issue":"3","key":"669_CR52","doi-asserted-by":"publisher","first-page":"398","DOI":"10.3390\/rs12030398","volume":"12","author":"X Lu","year":"2020","unstructured":"Lu X, Tang G, Wang X, Liu Y, Wei M, Zhang Y (2020) The development of a two-step merging and downscaling method for satellite precipitation products. Remote Sens 12(3):398. https:\/\/doi.org\/10.3390\/rs12030398","journal-title":"Remote Sens"},{"issue":"2","key":"669_CR53","first-page":"392","volume":"17","author":"S Ly","year":"2013","unstructured":"Ly S, Charles C, Degr\u00e9 A (2013) Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review. Biotechnol Agron Soc Environ 17(2):392\u2013406","journal-title":"Biotechnol Agron Soc Environ"},{"key":"669_CR54","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.rse.2017.08.023","volume":"200","author":"Z Ma","year":"2017","unstructured":"Ma Z, Shi Z, Zhou Y, Xu J, Yu W, Yang Y (2017a) A spatial data mining algorithm for downscaling TMPA 3B43 V7 data over the Qinghai-Tibet Plateau with the effects of systematic anomalies removed. Remote Sens Environ 200:378\u2013395. https:\/\/doi.org\/10.1016\/j.rse.2017.08.023","journal-title":"Remote Sens Environ"},{"issue":"15","key":"669_CR55","doi-asserted-by":"publisher","first-page":"5107","DOI":"10.1002\/joc.5148","volume":"37","author":"Z Ma","year":"2017","unstructured":"Ma Z, Zhou Y, Hu B, Liang Z, Shi Z (2017b) Downscaling annual precipitation with TMPA and land surface characteristics in China. Int J Climatol 37(15):5107\u20135119. https:\/\/doi.org\/10.1002\/joc.5148","journal-title":"Int J Climatol"},{"issue":"12","key":"669_CR56","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.3390\/rs10121883","volume":"10","author":"Z Ma","year":"2018","unstructured":"Ma Z, He K, Tan X, Xu J, Fang W, He Y, Hong Y (2018a) Comparisons of spatially downscaling TMPA and IMERG over the Tibetan Plateau. Remote Sensing 10(12):1883. https:\/\/doi.org\/10.3390\/rs10121883","journal-title":"Remote Sensing"},{"issue":"10","key":"669_CR57","doi-asserted-by":"publisher","first-page":"1392","DOI":"10.3390\/w10101392","volume":"10","author":"Z Ma","year":"2018","unstructured":"Ma Z, Tan X, Yang Y, Chen X, Kan G, Ji X, Lu H, Long J, Cui Y, Hong Y (2018b) The first comparisons of IMERG and the downscaled results based on IMERG in hydrological utility over the Ganjiang River Basin. Water 10(10):1392. https:\/\/doi.org\/10.3390\/w10101392","journal-title":"Water"},{"issue":"22","key":"669_CR58","doi-asserted-by":"publisher","first-page":"8465","DOI":"10.1080\/01431161.2019.1612118","volume":"40","author":"Z Ma","year":"2019","unstructured":"Ma Z, He K, Tan X, Liu Y, Lu H, Shi Z (2019) A new approach for obtaining precipitation estimates with a finer spatial resolution on a daily scale based on TMPA V7 data over the Tibetan Plateau. Int J Remote Sens 40(22):8465\u20138483. https:\/\/doi.org\/10.1080\/01431161.2019.1612118","journal-title":"Int J Remote Sens"},{"key":"669_CR59","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2019.124378","volume":"581","author":"Z Ma","year":"2020","unstructured":"Ma Z, Xu J, He K, Han X, Ji Q, Wang T, Xiong W, Hong Y (2020) An updated moving window algorithm for hourly-scale satellite precipitation downscaling: a case study in the Southeast Coast of China. J Hydrol 581:124378. https:\/\/doi.org\/10.1016\/j.jhydrol.2019.124378","journal-title":"J Hydrol"},{"issue":"3","key":"669_CR60","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.atmosres.2011.09.003","volume":"102","author":"C Mahesh","year":"2011","unstructured":"Mahesh C, Prakash S, Sathiyamoorthy V, Gairola RM (2011) Artificial neural network based microwave precipitation estimation using scattering index and polarization corrected temperature. Atmos Res 102(3):358\u2013364. https:\/\/doi.org\/10.1016\/j.atmosres.2011.09.003","journal-title":"Atmos Res"},{"issue":"3\u20134","key":"669_CR61","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.jhydrol.2007.02.018","volume":"338","author":"TR McVicar","year":"2007","unstructured":"McVicar TR, Van Niel TG, Li L, Hutchinson MF, Mu X, Liu Z (2007) Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences. J Hydrol 338(3\u20134):196\u2013220. https:\/\/doi.org\/10.1016\/j.jhydrol.2007.02.018","journal-title":"J Hydrol"},{"issue":"10","key":"669_CR62","doi-asserted-by":"publisher","first-page":"3935","DOI":"10.1016\/j.rse.2008.06.012Get","volume":"112","author":"O Merlin","year":"2008","unstructured":"Merlin O, Walker JP, Chehbouni A, Kerr Y (2008) Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency. Remote Sens Environ 112(10):3935\u20133946. https:\/\/doi.org\/10.1016\/j.rse.2008.06.012Get","journal-title":"Remote Sens Environ"},{"issue":"10","key":"669_CR63","doi-asserted-by":"publisher","first-page":"2275","DOI":"10.1016\/j.rse.2009.06.012","volume":"113","author":"O Merlin","year":"2009","unstructured":"Merlin O, Al Bitar A, Walker JP, Kerr Y (2009) A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors. Remote Sens Environ 113(10):2275\u20132284. https:\/\/doi.org\/10.1016\/j.rse.2009.06.012","journal-title":"Remote Sens Environ"},{"issue":"10","key":"669_CR64","doi-asserted-by":"publisher","first-page":"2305","DOI":"10.1016\/j.rse.2010.05.007","volume":"114","author":"O Merlin","year":"2010","unstructured":"Merlin O, Al Bitar A, Walker JP, Kerr Y (2010a) An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data. Remote Sens Environ 114(10):2305\u20132316. https:\/\/doi.org\/10.1016\/j.rse.2010.05.007","journal-title":"Remote Sens Environ"},{"issue":"11","key":"669_CR65","doi-asserted-by":"publisher","first-page":"2500","DOI":"10.1016\/j.rse.2010.05.025","volume":"114","author":"O Merlin","year":"2010","unstructured":"Merlin O, Duchemin B, Hagolle O, Jacob F, Coudert B, Chehbouni G, Dedieu G, Garatuza J, Kerr Y (2010b) Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 images. Remote Sens Environ 114(11):2500\u20132512. https:\/\/doi.org\/10.1016\/j.rse.2010.05.025","journal-title":"Remote Sens Environ"},{"key":"669_CR66","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1016\/j.atmosres.2015.08.008","volume":"169","author":"PT Nastos","year":"2016","unstructured":"Nastos PT, Kapsomenakis J, Philandras KM (2016) Evaluation of the TRMM 3B43 gridded precipitation estimates over Greece. Atmos Res 169:497\u2013514. https:\/\/doi.org\/10.1016\/j.atmosres.2015.08.008","journal-title":"Atmos Res"},{"key":"669_CR67","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/237126","author":"NW Park","year":"2013","unstructured":"Park NW (2013) Spatial downscaling of TRMM precipitation using geostatistics and fine scale environmental variables. Adv Meteorol. https:\/\/doi.org\/10.1155\/2013\/237126","journal-title":"Adv Meteorol"},{"issue":"16","key":"669_CR68","doi-asserted-by":"publisher","first-page":"3858","DOI":"10.1080\/01431161.2016.1204031","volume":"37","author":"NW Park","year":"2016","unstructured":"Park NW, Hong S, Kyriakidis PC, Lee W, Lyu SJ (2016) Geostatistical downscaling of AMSR2 precipitation with COMS infrared observations. Int J Remote Sens 37(16):3858\u20133869. https:\/\/doi.org\/10.1080\/01431161.2016.1204031","journal-title":"Int J Remote Sens"},{"issue":"3","key":"669_CR69","doi-asserted-by":"publisher","first-page":"255","DOI":"10.3390\/rs9030255","volume":"9","author":"NW Park","year":"2017","unstructured":"Park NW, Kyriakidis PC, Hong S (2017) Geostatistical integration of coarse resolution satellite precipitation products and rain gauge data to map precipitation at fine spatial resolutions. Remote Sens 9(3):255. https:\/\/doi.org\/10.3390\/rs9030255","journal-title":"Remote Sens"},{"issue":"9","key":"669_CR70","doi-asserted-by":"publisher","first-page":"3845","DOI":"10.1109\/JSTARS.2014.2325398","volume":"7","author":"M Piles","year":"2014","unstructured":"Piles M, S\u00e1nchez N, Vall-llossera M, Camps A, Mart\u00ednez-Fern\u00e1ndez J, Mart\u00ednez J, Gonz\u00e1lez-Gambau V (2014) A downscaling approach for SMOS land observations: evaluation of high-resolution soil moisture maps over the Iberian Peninsula. IEEE J Select Topics Appl Earth Obs Remote Sens 7(9):3845\u20133857. https:\/\/doi.org\/10.1109\/JSTARS.2014.2325398","journal-title":"IEEE J Select Topics Appl Earth Obs Remote Sens"},{"key":"669_CR71","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1016\/j.jhydrol.2015.02.014","volume":"523","author":"S Pombo","year":"2015","unstructured":"Pombo S, de Oliveira RP (2015) Evaluation of extreme precipitation estimates from TRMM in Angola. J Hydrol 523:663\u2013679. https:\/\/doi.org\/10.1016\/j.jhydrol.2015.02.014","journal-title":"J Hydrol"},{"issue":"3","key":"669_CR72","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/S0020-7373(87)80053-6","volume":"27","author":"JR Quinlan","year":"1987","unstructured":"Quinlan JR (1987) Simplifying decision trees. Int J Man Mach Stud 27(3):221\u2013234. https:\/\/doi.org\/10.1016\/S0020-7373(87)80053-6","journal-title":"Int J Man Mach Stud"},{"issue":"2","key":"669_CR73","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/j.envsoft.2010.07.006","volume":"26","author":"R Quiroz","year":"2011","unstructured":"Quiroz R, Yarlequ\u00e9 C, Posadas A, Mares V, Immerzeel WW (2011) Improving daily rainfall estimation from NDVI using a wavelet transform. Environ Model Softw 26(2):201\u2013209. https:\/\/doi.org\/10.1016\/j.envsoft.2010.07.006","journal-title":"Environ Model Softw"},{"issue":"13","key":"669_CR74","doi-asserted-by":"publisher","first-page":"3943","DOI":"10.1080\/01431161.2017.1312031","volume":"38","author":"A Retalis","year":"2017","unstructured":"Retalis A, Tymvios F, Katsanos D, Michaelides S (2017) Downscaling CHIRPS precipitation data: an artificial neural network modelling approach. Int J Remote Sens 38(13):3943\u20133959. https:\/\/doi.org\/10.1080\/01431161.2017.1312031","journal-title":"Int J Remote Sens"},{"issue":"15","key":"669_CR75","doi-asserted-by":"publisher","first-page":"2907","DOI":"10.1080\/014311698214343","volume":"19","author":"Y Richard","year":"1998","unstructured":"Richard Y, Poccard IJIJORS (1998) A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa. Int J Remote Sens 19(15):2907\u20132920. https:\/\/doi.org\/10.1080\/014311698214343","journal-title":"Int J Remote Sens"},{"issue":"15","key":"669_CR76","doi-asserted-by":"publisher","first-page":"2755","DOI":"10.1080\/01431169508954590","volume":"16","author":"PA Schultz","year":"1995","unstructured":"Schultz PA, Halpert MS (1995) Global analysis of the relationships among a vegetation index, precipitation and land surface temperature. Remote Sens 16(15):2755\u20132777. https:\/\/doi.org\/10.1080\/01431169508954590","journal-title":"Remote Sens"},{"issue":"2","key":"669_CR77","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1029\/2018JD028795","volume":"124","author":"E Sharifi","year":"2019","unstructured":"Sharifi E, Saghafian B, Steinacker R (2019) Downscaling satellite precipitation estimates with multiple linear regression, artificial neural networks, and spline interpolation techniques. J Geophys Res 124(2):789\u2013805. https:\/\/doi.org\/10.1029\/2018JD028795","journal-title":"J Geophys Res"},{"issue":"2","key":"669_CR78","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1659\/MRD-JOURNAL-D-14-00119.1","volume":"35","author":"Y Shi","year":"2015","unstructured":"Shi Y, Song L (2015) Spatial downscaling of monthly TRMM precipitation based on EVI and other geospatial variables over the Tibetan Plateau from 2001 to 2012. Mt Res Dev 35(2):180\u2013194. https:\/\/doi.org\/10.1659\/MRD-JOURNAL-D-14-00119.1","journal-title":"Mt Res Dev"},{"issue":"1\u20134","key":"669_CR79","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.jhydrol.2004.03.039","volume":"298","author":"MB Smith","year":"2004","unstructured":"Smith MB, Koren VI, Zhang Z, Reed SM, Pan JJ, Moreda F (2004) Runoff response to spatial variability in precipitation: an analysis of observed data. J Hydrol 298(1\u20134):267\u2013286. https:\/\/doi.org\/10.1016\/j.jhydrol.2004.03.039","journal-title":"J Hydrol"},{"issue":"4","key":"669_CR80","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.atmosres.2009.03.001","volume":"94","author":"Z Sokol","year":"2009","unstructured":"Sokol Z, Bli\u017e\u0148\u00e1k V (2009) Areal distribution and precipitation\u2013altitude relationship of heavy short-term precipitation in the Czech Republic in the warm part of the year. Atmos Res 94(4):652\u2013662. https:\/\/doi.org\/10.1016\/j.atmosres.2009.03.001","journal-title":"Atmos Res"},{"issue":"9","key":"669_CR81","doi-asserted-by":"publisher","first-page":"2035","DOI":"10.1175\/1520-0477(2000)081<2035:EOPSSE>2.3.CO;2","volume":"81","author":"S Sorooshian","year":"2000","unstructured":"Sorooshian S, Hsu KL, Gao X, Gupta HV, Imam B, Braithwaite D (2000) Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bull Am Meteor Soc 81(9):2035\u20132046. https:\/\/doi.org\/10.1175\/1520-0477(2000)081%3c2035:EOPSSE%3e2.3.CO;2","journal-title":"Bull Am Meteor Soc"},{"issue":"3","key":"669_CR82","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1175\/2009JTECHA1219.1","volume":"27","author":"K Tao","year":"2010","unstructured":"Tao K, Barros AP (2010) Using fractal downscaling of satellite precipitation products for hydrometeorological applications. J Atmos Oceanic Tech 27(3):409\u2013427. https:\/\/doi.org\/10.1175\/2009JTECHA1219.1","journal-title":"J Atmos Oceanic Tech"},{"key":"669_CR83","first-page":"1","volume":"1","author":"J Verlinde","year":"2011","unstructured":"Verlinde J (2011) TRMM rainfall data downscaling in the Pangani Basin in Tanzania. Master Sci Thesis Delft Univ Technol 1:1\u201372","journal-title":"Master Sci Thesis Delft Univ Technol"},{"issue":"2","key":"669_CR84","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1175\/2008JHM1048.1","volume":"10","author":"DA Vila","year":"2009","unstructured":"Vila DA, De Goncalves LGG, Toll DL, Rozante JR (2009) Statistical evaluation of combined daily gauge observations and rainfall satellite estimates over continental South America. J Hydrometeorol 10(2):533\u2013543. https:\/\/doi.org\/10.1175\/2008JHM1048.1","journal-title":"J Hydrometeorol"},{"key":"669_CR85","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.jaridenv.2012.02.014","volume":"82","author":"C Wu","year":"2012","unstructured":"Wu C, Chen JM (2012) The use of precipitation intensity in estimating gross primary production in four northern grasslands. J Arid Environ 82:11\u201318. https:\/\/doi.org\/10.1016\/j.jaridenv.2012.02.014","journal-title":"J Arid Environ"},{"key":"669_CR86","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.rse.2014.03.001","volume":"147","author":"C Wu","year":"2014","unstructured":"Wu C, Gonsamo A, Gough CM, Chen JM, Xu S (2014) Modeling growing season phenology in North American forests using seasonal mean vegetation indices from MODIS. Remote Sens Environ 147:79\u201388. https:\/\/doi.org\/10.1016\/j.rse.2014.03.001","journal-title":"Remote Sens Environ"},{"issue":"11","key":"669_CR87","doi-asserted-by":"publisher","first-page":"2539","DOI":"10.1175\/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2","volume":"78","author":"P Xie","year":"1997","unstructured":"Xie P, Arkin PA (1997) Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteor Soc 78(11):2539\u20132558. https:\/\/doi.org\/10.1175\/1520-0477(1997)078%3c2539:GPAYMA%3e2.0.CO;2","journal-title":"Bull Am Meteor Soc"},{"issue":"13","key":"669_CR88","doi-asserted-by":"publisher","first-page":"2197","DOI":"10.1175\/2769.1","volume":"16","author":"P Xie","year":"2003","unstructured":"Xie P, Janowiak JE, Arkin PA, Adler R, Gruber A, Ferraro R, Huffman GJ, Curtis S (2003) GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates. J Clim 16(13):2197\u20132214. https:\/\/doi.org\/10.1175\/2769.1","journal-title":"J Clim"},{"issue":"6","key":"669_CR89","doi-asserted-by":"publisher","first-page":"1054","DOI":"10.1134\/S0097807820060123","volume":"47","author":"S Xie","year":"2020","unstructured":"Xie S, Liu Y, Yao F (2020) Spatial downscaling of TRMM precipitation using an optimal regression model with NDVI in inner Mongolia, China. Water Resourc 47(6):1054\u20131064. https:\/\/doi.org\/10.1134\/S0097807820060123","journal-title":"Water Resourc"},{"key":"669_CR90","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.rse.2015.02.024","volume":"162","author":"S Xu","year":"2015","unstructured":"Xu S, Wu C, Wang L, Gonsamo A, Shen Y, Niu Z (2015) A new satellite-based monthly precipitation downscaling algorithm with non-stationary relationship between precipitation and land surface characteristics. Remote Sens Environ 162:119\u2013140. https:\/\/doi.org\/10.1016\/j.rse.2015.02.024","journal-title":"Remote Sens Environ"},{"key":"669_CR91","doi-asserted-by":"publisher","unstructured":"Yoo C, Im J, Park S, Cho D. Thermal characteristics of Daegu using land cover data and satellite-derived surface temperature downscaled based on machine learning. Korean Journal of Remote Sensing. 2017;33(6):1101\u20131118. Doi: https:\/\/doi.org\/10.7780\/kjrs.2017.33.6.2.6","DOI":"10.7780\/kjrs.2017.33.6.2.6"},{"key":"669_CR92","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.jag.2012.01.003","volume":"18","author":"W Zhan","year":"2012","unstructured":"Zhan W, Chen Y, Wang J, Zhou J, Quan J, Liu W, Li J (2012) Downscaling land surface temperatures with multi-spectral and multi-resolution images. Int J Appl Earth Obs Geoinf 18:23\u201336. https:\/\/doi.org\/10.1016\/j.jag.2012.01.003","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"669_CR93","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.rse.2012.12.014","volume":"131","author":"W Zhan","year":"2013","unstructured":"Zhan W, Chen Y, Zhou J, Wang J, Liu W, Voogt J, Zhu X, Quan J, Li J (2013) Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats. Remote Sens Environ 131:119\u2013139. https:\/\/doi.org\/10.1016\/j.rse.2012.12.014","journal-title":"Remote Sens Environ"},{"key":"669_CR94","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1506017","author":"C Zhan","year":"2018","unstructured":"Zhan C, Han J, Hu S, Liu L, Dong Y (2018) Spatial downscaling of GPM annual and monthly precipitation using regression-based algorithms in a mountainous area. Adv Meteorol. https:\/\/doi.org\/10.1155\/2018\/1506017","journal-title":"Adv Meteorol"},{"issue":"4","key":"669_CR95","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s11442-009-0403-7","volume":"19","author":"X Zhang","year":"2009","unstructured":"Zhang X, Hu Y, Zhuang D, Qi Y, Ma X (2009) NDVI spatial pattern and its differentiation on the Mongolian Plateau. J Geog Sci 19(4):403\u2013415. https:\/\/doi.org\/10.1007\/s11442-009-0403-7","journal-title":"J Geog Sci"},{"key":"669_CR96","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.rse.2018.06.004","volume":"215","author":"T Zhang","year":"2018","unstructured":"Zhang T, Li B, Yuan Y, Gao X, Sun Q, Xu L, Jiang Y (2018) Spatial downscaling of TRMM precipitation data considering the impacts of macro-geographical factors and local elevation in the Three-River Headwaters Region. Remote Sens Environ 215:109\u2013127. https:\/\/doi.org\/10.1016\/j.rse.2018.06.004","journal-title":"Remote Sens Environ"},{"issue":"6","key":"669_CR97","doi-asserted-by":"publisher","first-page":"1259","DOI":"10.1175\/JHM-D-19-0289.1","volume":"21","author":"H Zhang","year":"2020","unstructured":"Zhang H, Lo\u00e1iciga HA, Ha D, Du Q (2020) Spatial and temporal downscaling of TRMM precipitation with novel algorithms. J Hydrometeorol 21(6):1259\u20131278. https:\/\/doi.org\/10.1175\/JHM-D-19-0289.1","journal-title":"J Hydrometeorol"},{"issue":"2","key":"669_CR98","doi-asserted-by":"publisher","first-page":"234","DOI":"10.3390\/rs13020234","volume":"13","author":"N Zhao","year":"2021","unstructured":"Zhao N (2021) An efficient downscaling scheme for high-resolution precipitation estimates over a high mountainous watershed. Remote Sens 13(2):234. https:\/\/doi.org\/10.3390\/rs13020234","journal-title":"Remote Sens"},{"issue":"10","key":"669_CR99","doi-asserted-by":"publisher","first-page":"1912","DOI":"10.3390\/su9101912","volume":"9","author":"X Zhao","year":"2017","unstructured":"Zhao X, Jing W, Zhang P (2017) Mapping fine spatial resolution precipitation from TRMM precipitation datasets using an ensemble learning method and MODIS optical products in China. Sustainability 9(10):1912. https:\/\/doi.org\/10.3390\/su9101912","journal-title":"Sustainability"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00669-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-021-00669-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00669-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T02:10:41Z","timestamp":1644459041000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-021-00669-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,6]]},"references-count":99,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["669"],"URL":"https:\/\/doi.org\/10.1007\/s12145-021-00669-4","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"value":"1865-0473","type":"print"},{"value":"1865-0481","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,6]]},"assertion":[{"value":"11 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}