|Lesch, Scott - USDA-ARS-GEB SALINITY LAB|
|Yang, Chenghai - KIKA DE LKA GARZA SUBTROP|
Submitted to: Journal of Photogrammetric Engineering and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 15, 2002
Publication Date: June 1, 2003
Citation: Barnes, E.M., Sudduth, K.A., Hummel, J.W., Lesch, S.M., Corwin, D.L., Yang, C., Daughtry, C.S., Bausch, W.C. 2003. Remote- and ground-based sensor techniques to map soil properties.. Journal of Photogrammetric Engineering and Remote Sensing. 69(6):619-630. Interpretive Summary: With the increased availability of yield maps, farm managers are becoming increasingly aware of the variability of crop production within their fields. Yield maps are generated from sensors that estimate crop yield as it is harvested and relate the yield to a spatial coordinate determined from a global positioning system receiver. In many cases, it has been found that much of the yield variability can be related to changes in soil properties such as water holding capacity, salinity conditions, or fertility levels. Determining soil properties at a fine spatial resolution using traditional sampling techniques can become cost and time prohibitive. This article provides a review of research on efforts related to the rapid mapping of soil properties using airborne- and satellite-based imagery and data from equipment-mounted sensors. The potential for integration of various data sources and models to improve the estimation of soil properties is also discussed. This work will be of interest to other scientists who are conducting precision farming research and to farm managers and agricultural consultants who are interested in new technologies to map variations in soil properties.
Technical Abstract: Farm managers are becoming increasingly aware of the spatial variability in crop production with the growing availability of yield monitors. Often this variability can be related to differences in soil properties (e.g., texture, organic matter, salinity levels, and nutrient status) within the field. To develop management approaches to address this variability, high spatial resolution soil property maps are often needed. Some soil properties have been related directly to a soil spectral response or inferred based on remotely sensed measurements of crop canopies including soil texture, nitrogen level, organic matter content, and salinity status. While many studies have obtained promising results, several interfering factors can limit approaches based solely on spectral response including tillage conditions and crop residue. A number of different ground-based sensors that have been used to rapidly assess soil properties "on-the-go" (e.g., sensor mounted on a tractor and data mapped with coincident position information), and the data from these sensors complement image-based data. On-the-go sensors have been developed to rapidly map soil organic matter content, electrical conductivity, nitrate content, and compaction. Model and statistical methods show promise to integrate these ground- and image-based data sources to maximize the information from each source for soil property mapping.