TY - CONF
T1 - Evaluation of remotely sensed soil moisture products using crowdsourced measurements
AU - Zappa, Luca
AU - Woods, Mel
AU - Hemment, Drew
AU - Xaver, Angelika
AU - Dorigo, Wouter
PY - 2020/8/26
Y1 - 2020/8/26
N2 - Global soil moisture products retrieved from various sensors onboard satellites are becoming readily available. However, validation of such products is a crucial step to ensure their reliability. In-situ measurements, which provide the most accurate soil moisture estimates, are often used as reference dataset, but they are limited in number. The GROW Observatory (GROW) was initiated to demonstrate that a 'Citizens' Observatory' (CO) can provide and utilise unprecedented amounts of data. We present GROW as a case study and demonstrate, for the first time, the use of crowdsourced observations to assess the temporal and spatial consistency of various satellite-derived soil moisture products. In particular, we provide evidence of the added value to Earth Observation, thanks to (i) the high number of sensors deployed, covering a wide range of land use, environmental, and climatic conditions, and (ii) the unique spatial density in GROW. Our results confirmed that SMAP and ESA CCI SM can better capture the temporal dynamics compared to the other products investigated. We found high uncertainties due to the spatial mismatch between in-situ and satellite observations, not only for coarse scale but also for high-resolution soil moisture products. This finding highlights the importance of crowdsourced observations, which have the potential to reduce representativeness errors. Finally, a preliminary analysis of the spatial consistency of Sentinel-1 soil moisture showed a poor agreement against GROW data. We conclude presenting the challenges and the steps that will follow this preliminary analysis, as well as design guidelines for COs to meaningfully contribute to Earth Observation.
AB - Global soil moisture products retrieved from various sensors onboard satellites are becoming readily available. However, validation of such products is a crucial step to ensure their reliability. In-situ measurements, which provide the most accurate soil moisture estimates, are often used as reference dataset, but they are limited in number. The GROW Observatory (GROW) was initiated to demonstrate that a 'Citizens' Observatory' (CO) can provide and utilise unprecedented amounts of data. We present GROW as a case study and demonstrate, for the first time, the use of crowdsourced observations to assess the temporal and spatial consistency of various satellite-derived soil moisture products. In particular, we provide evidence of the added value to Earth Observation, thanks to (i) the high number of sensors deployed, covering a wide range of land use, environmental, and climatic conditions, and (ii) the unique spatial density in GROW. Our results confirmed that SMAP and ESA CCI SM can better capture the temporal dynamics compared to the other products investigated. We found high uncertainties due to the spatial mismatch between in-situ and satellite observations, not only for coarse scale but also for high-resolution soil moisture products. This finding highlights the importance of crowdsourced observations, which have the potential to reduce representativeness errors. Finally, a preliminary analysis of the spatial consistency of Sentinel-1 soil moisture showed a poor agreement against GROW data. We conclude presenting the challenges and the steps that will follow this preliminary analysis, as well as design guidelines for COs to meaningfully contribute to Earth Observation.
KW - Citizens' Observatory
KW - Crowdsourcing
KW - Remote Sensing
KW - Soil Moisture
KW - Satellite Validation
KW - In-situ
KW - Citizen Science
KW - Design
UR - http://www.scopus.com/inward/record.url?scp=85083157505&partnerID=8YFLogxK
U2 - 10.1117/12.2571913
DO - 10.1117/12.2571913
M3 - Paper
SP - 88
EP - 102
T2 - Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020)
Y2 - 16 March 2020 through 18 March 2020
ER -