TY - JOUR
T1 - Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces
AU - Nouri, Hamideh
AU - Nagler, Pamela
AU - Chavoshi Borujeni, Sattar
AU - Barreto Munez, Armando
AU - Alaghmand, Sina
AU - Noori, Behnaz
AU - Galindo, Alejandro
AU - Didan, Kamel
N1 - Funding Information:
This article is part of the special issue in honour of Prof. Edward P. Glenn. This paper is dedicated to Edward P. Glenn to express our sincere and deep gratitude for being such an inspiration. Edward P. Glenn was the referee of my PhD thesis, and later during my postdoc, I had the chance to work with him remotely and during my visit to the U. S. Geological Survey (USGS) and University of Arizona. It was truly a great privilege and honour to work with him and learn from him. He is sincerely missed. We thank the University of South Australia to support the in situ measurements in the Adelaide Parklands; without their help, this project would not have been possible. We are also extremely grateful to Mr. Hamed Noori, the graphic designer, for his great assistance with the graphic abstract. We wish to thank Dr. Jon Michael Hathaway for his constructive review. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Publisher Copyright:
© 2020 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.
PY - 2020/7/15
Y1 - 2020/7/15
N2 - 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.
AB - 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.
KW - EVI2
KW - Landsat
KW - MODIS
KW - WorldView
KW - evapotranspiration
KW - water consumption
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U2 - 10.1002/hyp.13790
DO - 10.1002/hyp.13790
M3 - Article
AN - SCOPUS:85085625095
SN - 0885-6087
VL - 34
SP - 3183
EP - 3199
JO - Hydrological Processes
JF - Hydrological Processes
IS - 15
ER -