Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat

Jinyang Du; John S. Kimball; John Galantowicz; Seung Bum Kim; Steven K. Chan; Rolf Reichle; Lucas A. Jones; Jennifer D. Watts

doi:10.1016/j.rse.2018.04.054

Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat

Jinyang Du
, John S. Kimball
, John Galantowicz
, Seung Bum Kim
, Steven K. Chan
, Rolf Reichle
, Lucas A. Jones
, Jennifer D. Watts

Numerical Terradynamic Simulation Group

Research output: Contribution to journal › Article › peer-review

59 Scopus citations

Abstract

A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fw_LBand) retrievals were derived using SMAP H-polarization brightness temperature (T_b) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency T_b observations from AMSR2. The resulting fw_LBand global record has high temporal sampling (1–3 days) and 36-km spatial resolution. The fw_LBand annual averages corresponded favorably (R = 0.85, p-value < 0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fw_LBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fw_LBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fw_LBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fw_LBand retrievals showed favorable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fw_LBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.

Original language	English
Pages (from-to)	1-17
Number of pages	17
Journal	Remote Sensing of Environment
Volume	213
DOIs	https://doi.org/10.1016/j.rse.2018.04.054
State	Published - Aug 2018

Funding

SMAP brightness temperature data and land cover classification maps were provided courtesy of the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), located in Boulder, CO. https://earthdata.nasa.gov/about/daacs/daac-nsidc . River discharge data are available from the U.S. Geological Survey; Landsat-8 OLI and TIRS data are distributed by the Land Processes Distributed Active Archive Center (LP DAAC), located at USGS/EROS, Sioux Falls, SD. http://lpdaac.usgs.gov . The WBD is a coordinated effort between the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS), the United States Geological Survey (USGS), and the Environmental Protection Agency (EPA). The WBD was created from a variety of sources from each state and aggregated into a standard national layer for use in strategic planning and accountability. The SMOS data were obtained from the “Centre Aval de Traitement des Données SMOS” (CATDS), operated for the “Centre National d'Etudes Spatiales” (CNES, France) by IFREMER (Brest, France). This work was conducted at the University of Montana with funding from NASA ( NNX14AI50G , NNX15AB59G ). R. Reichle was supported by SMAP Science Team funding. Appendix A

Funders	Funder number
National Aeronautics and Space Administration	NNX15AB59G, NNX14AI50G

Keywords

AMSR2
Flood risk
Landsat
SMAP
Surface water inundation

Access to Document

10.1016/j.rse.2018.04.054

Cite this

@article{2cee43153eac430383ded0f1abd48525,

title = "Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat",

abstract = "A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1–3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favorably (R = 0.85, p-value < 0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favorable spatial accuracy for water (commission error 31.46\%, omission error 30.20\%) and land (commission error 0.87\%, omission error 0.96\%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.",

keywords = "AMSR2, Flood risk, Landsat, SMAP, Surface water inundation",

author = "Jinyang Du and Kimball, \{John S.\} and John Galantowicz and Kim, \{Seung Bum\} and Chan, \{Steven K.\} and Rolf Reichle and Jones, \{Lucas A.\} and Watts, \{Jennifer D.\}",

note = "Publisher Copyright: {\textcopyright} 2018 Elsevier Inc.",

year = "2018",

month = aug,

doi = "10.1016/j.rse.2018.04.054",

language = "English",

volume = "213",

pages = "1--17",

journal = "Remote Sensing of Environment",

issn = "0034-4257",

publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat

AU - Du, Jinyang

AU - Kimball, John S.

AU - Galantowicz, John

AU - Kim, Seung Bum

AU - Chan, Steven K.

AU - Reichle, Rolf

AU - Jones, Lucas A.

AU - Watts, Jennifer D.

PY - 2018/8

Y1 - 2018/8

N2 - A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1–3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favorably (R = 0.85, p-value < 0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favorable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.

AB - A method to assess global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1–3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favorably (R = 0.85, p-value < 0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favorable spatial accuracy for water (commission error 31.46%, omission error 30.20%) and land (commission error 0.87%, omission error 0.96%) classifications and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics and potential flood risk.

KW - AMSR2

KW - Flood risk

KW - Landsat

KW - SMAP

KW - Surface water inundation

UR - https://www.scopus.com/pages/publications/85046748732

U2 - 10.1016/j.rse.2018.04.054

DO - 10.1016/j.rse.2018.04.054

M3 - Article

AN - SCOPUS:85046748732

SN - 0034-4257

VL - 213

SP - 1

EP - 17

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

ER -

Assessing global surface water inundation dynamics using combined satellite information from SMAP, AMSR2 and Landsat

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this