Abolafia-Rosenzweig R, Livneh B, Small E E; Kumar S V (2019) Soil moisture data assimilation to estimate irrigation water use. J Adv Model Earth Sy 11: 3670-3690. doi: 10.1029/2019MS001797
Anselin L (1995) Local indicators of spatial association-LISA. Geogr Anal 27: 93-115. doi: 10.1111/j.1538-4632.1995.tb00338.x
Bousbih S, Zribi M, El Hajj M, Baghdadi N, Lili-Chabaane Z, Gao Q, Fanise P (2018) Soil moisture and irrigation mapping in A semi-arid region, based on the synergetic use of Sentinel-1 and Sentinel-2 data. Remote Sens 10: 1953. doi: 10.3390/rs10121953
Brocca L, Ciabatta L, Massari C, Moramarco T, Hahn S, Hasenauer S, Levizzani V (2014) Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. J Geophys Res Atmospheres 119: 5128-5141. doi: 10.1002/2014JD021489
Chance E W, Cobourn K M, Thomas V A (2018) Trend detection for the extent of irrigated agriculture in Idaho's Snake river plain, 1984-2016. Remote Sens 10: 145. doi: 10.3390/rs10010145
Dalposso G H, Uribe-Opazo M A, Mercante E, Lamparelli R A (2013) Spatial autocorrelation of NDVI and GVI indices derived from Landsat/TM images for soybean crops in the western of the state of Paraná in 2004/2005 crop season. Engenharia Agrícola 33: 525-537. doi: 10.1590/S0100-69162013000300009
Douglas E M, Beltrán-Przekurat A, Niyogi D, Pielke Sr R A, Vörösmarty C J (2009) The impact of agricultural intensification and irrigation on land–atmosphere interactions and Indian monsoon precipitation—A mesoscale modeling perspective. Glob Planet Change 67: 117-128. doi: 10.1016/j.gloplacha.2008.12.007
Eid A N M, Olatubara C O, Ewemoje T A, Farouk H, El-Hennawy M T (2020) Coastal wetland vegetation features and digital Change Detection Mapping based on remotely sensed imagery: El-Burullus Lake, Egypt. International Soil and Water Conservation Research 8: 66-79. doi: 10.1016/j.iswcr.2020.01.004
FAO (2018) The Future of Food and Agriculture: Alternative pathways to 2050. Food and Agriculture Organization of the United Nations Publications: Rome, Italy 224.
Feyisa G L, Meilby H, Fensholt R, Proud S R (2014) Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote Sens Environ 140: 23-35. doi: 10.1016/j.rse.2014.08.029
Gao Q, Zribi M, Escorihuela M J, Baghdadi N, Segui P Q (2018) Irrigation mapping using Sentinel-1 time series at field scale. Remote Sens 10: 1495. doi: 10.3390/rs10091495
Getis A, Ord J K (1992) The Analysis of Spatial Association by Use of Distance Statistics. Geogr. Anal 24: 189-206. doi: 10.1111/j.1538-4632.1992.tb00261.x
Helman D, Mussery A (2020) Using Landsat satellites to assess the impact of check dams built across erosive gullies on vegetation rehabilitation. Sci Total Environ 730: 138873. doi: 10.1016/j.scitotenv.2020.138873
Ji L, Zhang L, Wylie B (2009) Analysis of dynamic thresholds for the normalized difference water index. Photogrammetric Eng Rem S 75: 1307-1317. doi: 10.14358/PERS.75.11.1307
Jiang H, Feng M, Zhu Y, Lu N, Huang J, Xiao T (2014) An automated method for extracting rivers and lakes from Landsat imagery. Remote Sens 6: 5067-5089. doi: 10.3390/rs6065067
Jin N, Tao B, Ren W, Feng M, Sun R, He L, Yu Q (2016) Mapping irrigated and rainfed wheat areas using multi-temporal satellite data. Remote Sens 8: 207. doi: 10.3390/rs8030207
Kamthonkiat D, Honda K, Turral H, Tripathi N K, Wuwongse V (2005) Discrimination of irrigated and rainfed rice in a tropical agricultural system using SPOT vegetation NDVI and rainfall data. Int J Remote Sens 26: 2527-2547. doi: 10.1080/01431160500104335
Kelly J T, Gontz A M (2018) Using GPS-surveyed intertidal zones to determine the validity of shorelines automatically mapped by Landsat water indices. Int J Appl Earth Obs Geoinf 65: 92-104. do: 10.1016/j.jag.2017.10.007
Kotchenova S Y, Vermote E F, Matarrese R, Klemm Jr F J (2006) Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: Path radiance. Appl Optics 45: 6762-6774. doi: 10.1364/AO.45.006762
Kowe P, Mutanga O, Odindi J, Dube T (2020) A quantitative framework for analysing long term spatial clustering and vegetation fragmentation in an urban landscape using multi-temporal landsat data. Int J Appl Earth Obs 88: 102057. doi: 10.1016/j.jag.2020.102057
Lawston P M, Santanello Jr J A, Hanson B, Arsensault K (2020) Impacts of Irrigation on Summertime Temperatures in the Pacific Northwest. Earth Interactions 24: 1-26. doi: 10.1175/EI-D-19-0015.1
McFeeters S K (1996) The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int J Remote Sens 17: 1425-1432. doi: 10.1080/01431169608948714
Ord J K, Getis A (2001) Testing for local spatial autocorrelation in the presence of global autocorrelation. J Regional Sci 41: 411-432. doi: 10.1111/0022-4146.00224
Ord J K, Getis A (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geogr Anal 27: 286-306. doi: 10.1111/j.1538-4632.1995.tb00912.x
Peña-Arancibia J L, McVicar T R, Paydar Z, Li L, Guerschman J P, Donohue R J, Chiew F H (2014) Dynamic identification of summer cropping irrigated areas in a large basin experiencing extreme climatic variability. Remote Sens Environ 154: 139-152. doi: 10.1016/j.rse.2014.08.016
Pickens A H, Hansen M C, Hancher M, Stehman S V, Tyukavina A, Potapov P, Sherani Z (2020) Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series. Remote Sens Environ 243: 111792. doi: 10.1016/j.rse.2020.111792
Pielke Sr R A, Pitman A, Niyogi D, Mahmood R, McAlpine C, Hossain F, Reichstein M (2011) Land use/land cover changes and climate: modeling analysis and observational evidence. Wiley Interdisciplinary Reviews: Climate Change 2: 828-850. doi: 10.1002/wcc.144
Rogers A S, Kearney M S (2004) Reducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices. Int J Remote Sens 25: 2317-2335. doi: 10.1080/01431160310001618103
Ryan E M, Ogle K, Peltier D, Walker A P, De Kauwe M G, Medlyn B E, Harper A B (2017) Gross primary production responses to warming, elevated CO2, and irrigation: Quantifying the drivers of ecosystem physiology in a semiarid grassland. Global Ghange Biol 23: 3092-3106. doi: 10.1111/gcb.13602
Schroeder T A, Cohen W B, Song C, Canty M J, Yang Z (2006) Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon. Remote Sens Environ 103: 16-26. doi: 10.1016/j.rse.2006.03.008
Sharma A K, Hubert-Moy L, Buvaneshwari S, Sekhar M, Ruiz L, Bandyopadhyay S Corgne S (2018) Irrigation history estimation using multitemporal landsat satellite images: Application to an intensive groundwater irrigated agricultural watershed in India. Remote Sens 10: 893. doi: 10.3390/rs10060893
Teillet P M, Staenz K, William D J (1997) Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions. Remote Sens Environ 61: 139-149. doi: 10.1016/S0034-4257(96)00248-9
Tuinenburg O A, de Vries J P R (2017) Irrigation patterns resemble ERA-Interim Reanalysis soil moisture additions. Geophys Res Lett 44: 10-341. doi: 10.1002/2017GL074884
Worden J, de Beurs K M (2020) Surface water detection in the Caucasus. Int J Appl Earth O B S 91: 102159. doi: 10.1016/j.jag.2020.102159
Xiang K, Ma M, Liu W, Dong J, Zhu X, Yuan W (2019) Mapping Irrigated Areas of Northeast China in Comparison to Natural Vegetation. Remote Sens 11: 825. doi: 10.3390/rs11070825
Xiao X, Boles S, Liu J, Zhuang D, Frolking S, Li C, Moore III B (2005) Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sens Environ 95: 480-492. doi: 10.1016/j.rse.2004.12.009
Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27: 3025-3033. doi: 10.1080/01431160600589179
Yao F, Wang J, Wang C, Crétaux J F (2019) Constructing long-term high-frequency time series of global lake and reservoir areas using Landsat imagery. Remote Sens Environ 232: 111210. doi: 10.1016/j.rse.2019.111210
Young N E, Anderson R S, Chignell S M, Vorster A G, Lawrence R, Evangelista P H (2017) A survival guide to Landsat preprocessing. Ecology 98: 920-932. doi: 10.1002/ecy.1730
Zohaib M, Kim H, Choi M (2019) Detecting global irrigated areas by using satellite and reanalysis products. Sci Total Environ 677: 679-691. doi: 10.1016/j.scitotenv.2019.04.365