Background Much of the Red River Valley in Minnesota and North Dakota is low lying and flat, resulting in poor drainage conditions. Drains are used to remove the excess water from the root zone of the crop and prevent flooding of farmland. These drains increase crop yield by enhancing soil oxygen, which is necessary for healthy roots. They also lower losses of gaseous nitrogen and aerobic microbial activity. Remote sensing of agricultural areas can give detailed insight into the environmental conditions that must be managed by farmers.

Drainage anomaly is one of the parameters that can be detected and identified using imagery. Such imagery is useful for detecting drainage problems that are otherwise hidden well below the vegetation canopy. Yield map alone is useful for observing important yield heterogeneities. But combined with the use of imagery, the farmer can identify poor drainage as the cause of anomalies in the crop.

 Use of DataIndicators of anomalies were determined by comparing different information layers. The farmer used yield maps, satellite images, and other thematic maps as different layers to find similar patterns. The patches of low reflectance noticed on the Landsat false color composite matched the lower yield regions observed on the yield map.

On July 23, which was the date the Landsat scene was acquired, the wheat had reached its flowering stage. The spots of lower reflectance indicated lesser biomass, confirmed at harvest as lower yields. Then, the farmer overlaid the drainage map of the field over the imagery. As shown in the figure, a clear correlation was noticed between some of the drainage ditches and the lower reflectance pixels, highlighting a deficiency in the drainage system.

 Economic and Environmental Benefits The farmer, using imagery, successfully diagnosed the yield problem as one that could be remedied with drainage system improvements. This was an economical option, given the profits lost in yield.