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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #381745
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Comparison between dense L-band and C-band Synthetic Aperture Radar (SAR) time series for crop area mapping over a NISAR calibration-validation site

Author
item KRAATZ, S. - University Of Massachusetts, Amherst
item TORBICK, N. - Applied Geosolutions, Llc
item JIAO, X. - Agriculture And Agri-Food Canada
item HUANG, X. - Applied Geosolutions, Llc
item DINGLE ROBERTSON, L. - Agriculture And Agri-Food Canada
item DAVIDSON, A. - Agriculture And Agri-Food Canada
item MCNAIM, H. - Agriculture And Agri-Food Canada
item Cosh, Michael
item SIQUEIRA, P. - University Of Massachusetts, Amherst

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/3/2021
Publication Date: 2/5/2021
Citation: Kraatz, S., Torbick, N., Jiao, X., Huang, X., Dingle Robertson, L., Davidson, A., Mcnaim, H., Cosh, M.H., Siqueira, P. 2021. Comparison between dense L-band and C-band Synthetic Aperture Radar (SAR) time series for crop area mapping over a NISAR calibration-validation site. Agronomy. 11(2):273. https://doi.org/10.3390/agronomy11020273.
DOI: https://doi.org/10.3390/agronomy11020273

Interpretive Summary: Crop area mapping is an important geographic product for supporting food security and production forecasts. Active microwave radiometry is a viable and novel approach to estimating crop area at moderate spatial and temporal resolutions and the number of active sensors is increasing. A study was conducted over a field site in Canada to determine the capability of a collection of these new sensors to estimate crop area for the 2019 growing season. The current visible and near infrared band product was compared to the active sensor products available from two active satellites and it was determined that they performed reasonably well. This study will provide a foundation for future investigation of crop area mapping as new sensors are launched and new algorithms are developed for crop area mapping.

Technical Abstract: Crop area mapping is important for tracking agricultural production and supporting food security. Spaceborne approaches using Synthetic Aperture Radar (SAR) now allow for mapping crop area at moderate spatial and temporal resolutions. Multi-frequency SAR data is highly useful for crop monitoring because backscatter response from vegetation canopies is wavelength dependent. This study evaluates the utility of C-band Sentinel-1B (Sentinel-1) and L-band ALOS-2 (PALSAR) data, collected during the 2019 growing season, for generating accurate active crop extent (crop vs. non-crop) classifications over a future NISAR calibration-validation site in western Canada. Evaluations are performed against the Agriculture and Agri-Food Canada Annual satellite-based Cropland Inventory (ACI), an open data product that maps land cover across Canada’s agricultural extent. Classifications are performed using the temporal Coefficient of Variation (CV) approach, where an optimal crop/non-crop delineating CV threshold (CVthr) is selected according to Youden’s J-statistic. Results show that crop area mapping agreed better with the ACI when using Sentinel-1 data (84%) compared to PALSAR (74%). Analysis of performance by crop reveals that PALSAR’s poorer performance can be attributed to soybean, urban, grassland and pasture ACI classes. This study also compared CV values to in situ wet biomass data for canola and soybeans, showing that crops with lower biomass (soybean) had correspondingly lower CV values.