Gerald A. Nielsen

Wheat yield estimates using multi-temporal NDVI satellite imagery

We examined seasonal growth profiles developed from AVHRR-NDVI for estimating wheat yield at regional and farm scales in Montana for the years 1989-1997. Both regions and farms showed strong relationships between wheat yields and integrated NDVI over the entire growing season, and with late-season NDVI parameters. The use of AVHRR-NDVI growth profiles at the regional level provided the strongest yield estimates. At the farm scale, the spatial resolution (1 km 2 ) limited the certainty for accurate portrayal of field locations. However, our models provide a basis for further examination of time-series satellite data.

Cesium-137 in Montana soils

Fallout 137Cs levels in soil were measured at 11 diverse sites throughout Montana. Concentrations in near-surface samples ranged from 20-200 mBq g-1 (0.51-5.41 pCi g-1). Most of the 137Cs was in the top 10 cm of soil. Deeper occurrences were attributed to disturbances by animals and to interstitial flow of small sediment particles within saturated soils. The areal concentrations ranged from 130-748 mBq cm-2 (3.6-20.2 pCi cm-2) and were highly correlated with annual precipitation.

Modeling Vegetation Amount Using Bandwise Regression and Ecological Site Descriptions as an Alternative to Vegetation Indices

Ecological site descriptions (ESDs) based on soil maps, Landsat 7 ETM+ band values, and vegetation index data from 12 scenes were used as predictive variables in linear regression estimates of total biomass using field data from five Montana ranches. Bandwise regression explained the most variability (53%) when ESDs were not included, followed by tasseled cap components (51%), the soil adjusted vegetation index (44%), and the normalized difference vegetation index (41%). ESDs improved the amount of variability explained to 66% for bandwise regression and 65% using tasseled cap components.

Ecological site descriptions and remotely sensed imagery as a tool for rangeland evaluation

We classified Landsat-7 enhanced thematic mapper plus (ETM+) satellite imagery within ecological site descriptions to identify spectrally anomalous locations and determine whether these correlated with anomalous ground locations. Sites located in the Montana plains were classified by their departure from mean values in tasseled cap brightness, greenness, and wetness components, stratified by ecological site description. The classification had 98% overall accuracy in identifying locations that were or were not outside the norm in productivity and exposed soil for their ecological site description. Success was explained by the high correlations between field measures of productivity and exposed soil compared with tasseled cap components. Using this modeling technique might help rangeland managers identify sites needing more detailed field inventory and (or) management attention.

Climate, soil and crop yield relationships in Cascade County, Montana

Abstract The Productivity Index (PI) model estimates the productivity effects of erosion by the simulated removal of surface soil and consideration of available water-holding capacity, bulk density and pH. Although it has performed well in the US Corn Belt and elsewhere, further testing is required to demonstrate its applicability in other semi-arid environments. Evaluation of model performance in four fields in Hill and Jefferson counties, Montana, revealed a weak relationship between PI and small grain yield, possibly due to local conditions. Therefore, soils and crop data were extracted from the USDA-SCS SOILS-5 and Montana Agricultural Potentials System (MAPS) databases, as well as the county soil survey, to evaluate PI model performance and indicate appropriate changes in its design in Cascade County, Montana. Results indicate that model performance can be improved with the addition of factors to account for water balance, slope, growing degree days and calcium carbonate content. Regression of barley, spring wheat and winter wheat yield data against PI values from the original model accounted for 34, 31 and 31 per cent of the variability in yields of these three crops, respectively. R 2 increased an average of 77 per cent and accounted for 54, 59 and 58 per cent of the variations in yields when the four new factors were added to the model. These results have encouraged further efforts to develop a modified version of the PI model that uses computerized databases for county-scale assessments of semi-arid environments.

Precision farming management via information dissemination

In the Northern Great Plains of the United States, growing seasons are short (80-120 days) but extremely productive. Farms and ranches are large (>1000 acres), so many of precision agricultures early adopters reside in the region. Management optimization depends on decisions taken based on past as well as in-season information. Spatial data is an ideal tool to answer both the long term and the short-term needs.

Applications of remote sensing to precision agriculture with dual economic and environmental benefits

In the U.S. Northern Great Plains, growing seasons are short but extremely productive. Farms and ranches are large, so many of precision agricultures early adopters reside in the region. Crop yield maps at seasons end reveal sizable variations across fields. Farm management relying upon uniform chemical applications is ineffective and wasteful. We provided information about crop and range status in near- real-time, so that in-season decisions could be made to optimize final yields and minimize environmental degradation. We created learning communities, in which information is shared among scientists, farmers, ranchers, and data providers. The new information for agricultural producers was satellite and aerial imagery. Value-added information was derived from ETM+, AVHRR, IKONOS, and MIDOS sensors. The emphasis was on reducing the time between acquisition of data by a satellite and delivery of value-added products to farmers and ranchers. To distribute large spatial data sets in short times to rural users we relied upon satellite transmission (Direct PC). Results include: (1) management zone delineation, (2) variable-rate fertilizer applications, (3) weed detection, (4) irrigation efficiency determination, (5) detection of insect infestation, (6) specification of crop damage due to inadvertent chemical application, and (7) determination of livestock carrying capabilities on rangelands.

Mapping potential of digitized aerial photographs and space images for site-specific crop management

In site-specific crop management, treatments (e.g., fertilizer and herbicides) are applied precisely where they are needed. Global positioning system receivers allow accurate navigation of field implements and creation of crop yield maps. Remote sensing products help producers explain the wide range of yields shown on these maps and become the basis for digitized field management maps. Previous sources of remote sensing products for agriculture did not provide services that generated a sustained demand by crop producers, often because data were not delivered quickly enough. Public Access Resource Centers could provide a nearly uninterrupted electronic flow of data from NASAs MODIS and other sensors that could help producers and their advisors monitor crop conditions. This early warning/opportunity system would provide a low-cost way to discover conditions that merit examination on the ground. High-spatial-resolution digital aerial photographs or data from new commercial satellite companies would provide the basis for site-specific treatments. These detailed data are too expensive to acquire often and must be timed so as to represent differences in water supply characteristics and crop yield potentials. Remote sensing products must be linked to specific prescriptions that crop produces use to control operations and improve outcomes.

Soil-Specific Farming: A North American Perspective

Growing demand for soil-specific fertilizer management is currently met with about 100 variable-rate fertilizer applicators. One company alone in 1992 contracted 28,000 ha for variable-rate application. Data from several states indicate variable-rate programs cost

Agroecosystems and Land Resources of the Northern Great Plains

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