Mapping Agricultural Landuse in the
Report on the Mississippi Alluvial Valley of Arkansas
Landuse/Landcover (MAVA-LULC) Project
Copyright 1999; Comments to Bruce Gorham; bruce@cast.uark.edu
Section 9: Results and Conclusions
| Overall, the results of the study are quite positive. The dataset produced
for this project has several deficiencies mostly dealing with issues of
resolution. Increased frequency in temporal resolution offers the most promise
for improving agricultural studies. Large portions of Northeast Arkansas
(Group 1), an important cotton growing region, were obscured by clouds on
four consecutive TM acquisition dates from mid June to early August. The
addition of TM 7, and anticipated 8 day temporal resolution, could be very
beneficial to the study of intra-annual temporal landuse patterns and crop
identification: finding the right date to separate cotton from soybeans
using cotton's defoliation period.
An increase in spectral resolution: hyperspectral sensors, or the addition of thermal IR data, will also improve future agricultural landuse mapping projects. Fine spectral detail will allow analysts to detect subtle differences between and within various crop types, making it feasible to conduct large scale studies of crop varieties. Spatial resolution was not a major factor in this study. While the new high resolution sensors may benefit precision ag studies, the high cost of the data and tremendous disk space requirements are currently cost prohibitive for large scale mapping projects. TM 7's improved spatial resolution in the thermal band, however, could benefit future studies of the type conducted here, and TM 7's new 15 meter resolution panchromatic band may help to better delineate field boundaries at a considerably lower cost than SPOT imagery. In the past most agricultural landuse maps portrayed a somewhat static, year to year, picture of the landscape. The maps generated for the MAVA-LULC project depict season to season landuse/landcover patterns. Combined with other natural resource and socio-economic data, the information discussed here should prove to be a very useful information base for natural resource planners. |
