Nouri, Hamideh

[["dc.bibliographiccitation.firstpage","3183"],["dc.bibliographiccitation.issue","15"],["dc.bibliographiccitation.journal","Hydrological Processes"],["dc.bibliographiccitation.lastpage","3199"],["dc.bibliographiccitation.volume","34"],["dc.contributor.author","Nouri, Hamideh"],["dc.contributor.author","Nagler, Pamela"],["dc.contributor.author","Chavoshi Borujeni, Sattar"],["dc.contributor.author","Barreto Munez, Armando"],["dc.contributor.author","Alaghmand, Sina"],["dc.contributor.author","Noori, Behnaz"],["dc.contributor.author","Galindo, Alejandro"],["dc.contributor.author","Didan, Kamel"],["dc.date.accessioned","2021-04-14T08:26:17Z"],["dc.date.available","2021-04-14T08:26:17Z"],["dc.date.issued","2020"],["dc.description.abstract","Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their microclimates and irrigation practices builds up the complexity of ET estimation. In oversized UGS, areas too large to be measured with in situ ET methods, remote sensing (RS) approaches of ET measurement have the potential to estimate the actual ET. Often in situ approaches are not feasible or too expensive. We studied the effects of spatial resolution using different satellite images, with high-, medium- and coarse-spatial resolutions, on the greenness and ET of UGS using Vegetation Indices (VIs) and VI-based ET, over a 780-ha urban park in Adelaide, Australia. We validated ET with the ground-based ET method of Soil Water Balance. Three sets of imagery from WorldView2, Landsat and MODIS, and three VIs including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Enhanced Vegetation Index 2 (EVI2), were used to assess long-term changes of VIs and ET calculated from the different imagery acquired for this study (2011–2018). We found high correspondence between ET-MODIS and ET-Landsat (R2 > 0.99 for all VIs). Landsat-VIs captured the seasonal changes of greenness better than MODIS-VIs. We used artificial neural network (ANN) to relate the RS-ET and ground data, and ET-MODIS (EVI2) showed the highest correlation (R2 = 0.95 and MSE =0.01 for validation). We found a strong relationship between RS-ET and in situ measurements, even though it was not explicable by simple regressions; black box models helped us to explore their correlation. The methodology used in this research makes a strong case for the value of remote sensing in estimating and managing ET of green spaces in water-limited cities."],["dc.identifier.doi","10.1002/hyp.13790"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81889"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.publisher","John Wiley \\u0026 Sons, Inc."],["dc.relation.eissn","1099-1085"],["dc.relation.issn","0885-6087"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.rights","This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited."],["dc.title","Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5167"],["dc.bibliographiccitation.issue","24"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.volume","13"],["dc.contributor.affiliation","Abbasi, Neda; 1Department of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075 Göttingen, Germany; hamideh.nouri@uni-goettingen.de (H.N.); stefan.siebert@uni-goettingen.de (S.S.)"],["dc.contributor.affiliation","Nouri, Hamideh; 1Department of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075 Göttingen, Germany; hamideh.nouri@uni-goettingen.de (H.N.); stefan.siebert@uni-goettingen.de (S.S.)"],["dc.contributor.affiliation","Didan, Kamel; 3Biosystems Engineering, The University of Arizona, 1177 E. 4th St., Tucson, AZ 85719, USA; didan@arizona.edu (K.D.); abarreto@arizona.edu (A.B.-M.)"],["dc.contributor.affiliation","Barreto-Muñoz, Armando; 3Biosystems Engineering, The University of Arizona, 1177 E. 4th St., Tucson, AZ 85719, USA; didan@arizona.edu (K.D.); abarreto@arizona.edu (A.B.-M.)"],["dc.contributor.affiliation","Chavoshi Borujeni, Sattar; 4Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan 19395-1113, Iran; Sattar.Chavoshiborujeni@student.uts.edu.au"],["dc.contributor.affiliation","Salemi, Hamidreza; 6Agricultural Engineering Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan 19395-1113, Iran; hrsalemiwk@gmail.com"],["dc.contributor.affiliation","Opp, Christian; 2Department of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032 Marburg, Germany; opp@geo.uni-marburg.de"],["dc.contributor.affiliation","Siebert, Stefan; 1Department of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075 Göttingen, Germany; hamideh.nouri@uni-goettingen.de (H.N.); stefan.siebert@uni-goettingen.de (S.S.)"],["dc.contributor.affiliation","Nagler, Pamela; 7U.S. Geological Survey, Southwest Biological Science Center, 520 N. Park Avenue, Tucson, AZ 85719, USA; pnagler@usgs.gov"],["dc.contributor.author","Abbasi, Neda"],["dc.contributor.author","Nouri, Hamideh"],["dc.contributor.author","Didan, Kamel"],["dc.contributor.author","Barreto-Muñoz, Armando"],["dc.contributor.author","Chavoshi Borujeni, Sattar"],["dc.contributor.author","Salemi, Hamidreza"],["dc.contributor.author","Opp, Christian"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Nagler, Pamela"],["dc.contributor.editor","Doughty, Russell"],["dc.contributor.editor","Bajgain, Rajen"],["dc.contributor.editor","Wang, Jie"],["dc.date.accessioned","2022-01-26T16:33:57Z"],["dc.date.available","2022-01-26T16:33:57Z"],["dc.date.issued","2021-12-20"],["dc.date.updated","2022-02-09T13:20:04Z"],["dc.description.abstract","Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns\\’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVIMccL and EVI2MccL) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption."],["dc.identifier.doi","10.3390/rs13245167"],["dc.identifier.eissn","2072-4292"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/98675"],["dc.language.iso","en"],["dc.publisher","MDPI"],["dc.relation.doi","10.3390/rs13245167"],["dc.relation.issn","2072-4292"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.rights","Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)."],["dc.subject.gro","actual evapotranspiration"],["dc.subject.gro","google earth engine"],["dc.subject.gro","harvested area"],["dc.subject.gro","enhanced vegetation index"],["dc.subject.gro","cross-sensor transformation"],["dc.title","Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]