SMAP Validation Experiment 2019–2022 (SMAPVEX19–22): Field Campaign to Improve Soil Moisture and Vegetation Optical Depth Retrievals in Temperate Forests

Satellite-based retrieval of forest soil moisture (SM) and vegetation optical depth (VOD) are two long-standing unresolved issues hindering advances in hydrology, ecology, and Earth system science. A key obstacle is the lack of adequate reference data in forested regions. NASA's Soil Moisture Active Passive (SMAP) mission, with its partners, conducted the SMAP Validation Experiment 2019–2022 (SMAPVEX19–22) to improve the SMAP SM and VOD retrievals in temperate forests of the northeastern USA. The scope and scale of the campaign exceeded anything done thus far to develop forest satellite-based SM and VOD retrieval algorithms. The field campaign measured SM, surface conditions, and vegetation properties, with results demonstrating the value of tree sensors with SM measurements and destructive sampling of the vegetation water content of branches and leaves to capture the water distribution in soil and trees. Using low-cost zenith-pointing cameras proved effective in tracking vegetation phenology, aiding the interpretation of brightness temperature (TB). Airborne and mobile terrestrial laser scanning measurements captured the three-dimensional forest structure necessary for microwave measurement interpretation. Challenges included characterizing SM in organic forest soils and determining volumetric SM due to spatially variable soil bulk density. Comparisons of the field measurements with SMAP data revealed its ability to retrieve the soil permittivity (correlation of 0.68 and 0.75 for the two experiment sites) alongside VOD, including the frozen conditions. The findings indicated that L-band scattering albedo is temporally variable, and L-band TB is sensitive to deciduous forest leaves, influencing the development of SM and VOD retrieval algorithms.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/jstars.2025.3553085
Citations
10
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
7.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SMAP Validation Experiment 2019–2022 (SMAPVEX19–22): Field Campaign to Improve Soil Moisture and Vegetation Optical Depth Retrievals in Temperate Forests

Simon Kraatz, Simon Yueh, Tarendra Lakhankar, Andreas Colliander et al.
10 citations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Soil Moisture and Remote Sensing
7.99
article

SMAP Validation Experiment 2019–2022 (SMAPVEX19–22): Field Campaign to Improve Soil Moisture and Vegetation Optical Depth Retrievals in Temperate Forests

Simon Kraatz, Simon Yueh, Tarendra Lakhankar, Andreas Colliander, Alexandre Roy, John S. Kimball, Xiaolan Xu, Victoria A. Walker, Michael H. Cosh, Sidharth Misra, Laura Bourgeau‐Chavez, N. Steiner, Paul Siqueira, Aaron Berg, Victoria R. Kelly, Mehmet Kurum, Mehmet Öğüt, Cristina Vittucci, Dara Entekhabi, Seung-Bum Kim, Kyle C. McDonald, Xingjian Chen
article en
10 citations

Abstract

Satellite-based retrieval of forest soil moisture (SM) and vegetation optical depth (VOD) are two long-standing unresolved issues hindering advances in hydrology, ecology, and Earth system science. A key obstacle is the lack of adequate reference data in forested regions. NASA's Soil Moisture Active Passive (SMAP) mission, with its partners, conducted the SMAP Validation Experiment 2019–2022 (SMAPVEX19–22) to improve the SMAP SM and VOD retrievals in temperate forests of the northeastern USA. The scope and scale of the campaign exceeded anything done thus far to develop forest satellite-based SM and VOD retrieval algorithms. The field campaign measured SM, surface conditions, and vegetation properties, with results demonstrating the value of tree sensors with SM measurements and destructive sampling of the vegetation water content of branches and leaves to capture the water distribution in soil and trees. Using low-cost zenith-pointing cameras proved effective in tracking vegetation phenology, aiding the interpretation of brightness temperature (TB). Airborne and mobile terrestrial laser scanning measurements captured the three-dimensional forest structure necessary for microwave measurement interpretation. Challenges included characterizing SM in organic forest soils and determining volumetric SM due to spatially variable soil bulk density. Comparisons of the field measurements with SMAP data revealed its ability to retrieve the soil permittivity (correlation of 0.68 and 0.75 for the two experiment sites) alongside VOD, including the frozen conditions. The findings indicated that L-band scattering albedo is temporally variable, and L-band TB is sensitive to deciduous forest leaves, influencing the development of SM and VOD retrieval algorithms.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
University of Rome Tor Vergata (IT), Michigan Technological University (US), City College of New York (US), Agricultural Research Service (US), Jet Propulsion Laboratory (US), University of Georgia (US), University of Massachusetts Amherst (US), Cary Institute of Ecosystem Studies (US), Innovation and Economic Development Trois Rivières (CA), Université du Québec à Trois-Rivières (CA), Massachusetts Institute of Technology (US), University of Montana (US), University of Guelph (CA)
Zero hunger
Openalex Percentile: Top 2%
Soil Moisture and Remote Sensing
7.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.