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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 #292653
Title: Influence of angular effects on surface reflections for crops

Author
item Gao, Feng
item HE, TAO - University Of Maryland
item MASEK, JEFFREY - National Aeronautics And Space Administration (NASA)

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/10/2013
Publication Date: 8/12/2013
Citation: Gao, F.N., He, T., Masek, J. 2013. Influence of angular effects on surface reflections for crops [abstract]. Second International Conference on Agro-Geoinformatics 2013. DOI:10.1109/Argo-Geoinformatics.2013.6621925.

Interpretive Summary:

Technical Abstract: Remote sensing imageries with wide swath have been broadly used in mapping crop types and monitoring crop conditions at the regional, continental or global scales. In recent years, the U.S. Department of Agriculture (USDA) has used the Moderate Resolution Imaging Spectroradiometer (MODIS, 250m–1km) data for crop condition monitoring and the medium resolution (30-60m) wide swath sensor data for crop type classification. Angular effects have been observed in these data, and it’s desired to understand and correct angular effects for the quantitative applications. Angular effects arising from variable viewing and solar geometry can cause significant variation in retrieved directional reflectance, even in the absence of changes in vegetation type, condition, or pigmentation. Three types of angular effect can be considered. The first arises from variations in view angle across a single remote sensing image frame, or from one image frame to an adjacent, overlapping frame (“view angle effect”). The second arises from variations in solar geometry associated with different anniversary acquisition dates (“day of year effect”). The third arises from drift in mean local time (MLT) throughout the life of the mission (“MLT drift effect”). In general, all three effects are caused by inconsistent sun-target-sensor geometry, which results in inconsistent sampling of the bi-directional reflectance distribution function (BRDF) in space and time. As crop condition monitoring requires dense time-series of remote sensing imageries to map changes through time, it becomes critical to demonstrate that observed temporal changes are due to crop condition, and not simply to changes in sun-target-sensor geometry. In this presentation, we evaluate the magnitude of each of these three angular effects using BRDF parameters derived from in-situ measurements and MODIS data for specific land cover or crop types. A BRDF look-up table (LUT) for major crop types from different growth stages is established using MODIS BRDF products and the crop data layer (CDL) from USDA National Agricultural Statistics Service (NASS). The magnitude of variability of bi-directional reflectance in a time series of remote sensing imageries will be examined and discussed. The approach to correct angular effects will be presented. The corrected reflectances from typical remote sensing sensors will be compared and analyzed. Future direction and operational application on improving data quality for quantitative analysis will be discussed.