Geology topics

Research about Greater Platte River Basin

Source-linked reports with geographic coverage including Greater Platte River Basin.

4 recordsLinked to original sources

USGS2013

NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA

In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVI sat _ adjust ) based on RVI was developed. A 10-year (2000–2009) NDVI sat _ adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CP non _ sat _ adjust , CP sat _ adjust ) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CP sat _ adjust and the NASS average corn yield data ( r = 0.78, 113 samples) is stronger than the relationship between CP non _ sat _ adjust and the NASS average corn yield data ( r = 0.67, 113 samples), indicating that the new CP sat _ adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.

Colorado, Kansas, Nebraska, South Dakota, Wyoming↗

USGS2012

Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA

With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data ( R 2 = 0.90).

Greater Platte River Basin↗

USGS2012

Mapping grasslands suitable for cellulosic biofuels in the Greater Platte River Basin, United States

Biofuels are an important component in the development of alternative energy supplies, which is needed to achieve national energy independence and security in the United States. The most common biofuel product today in the United States is corn-based ethanol; however, its development is limited because of concerns about global food shortages, livestock and food price increases, and water demand increases for irrigation and ethanol production. Corn-based ethanol also potentially contributes to soil erosion, and pesticides and fertilizers affect water quality. Studies indicate that future potential production of cellulosic ethanol is likely to be much greater than grain- or starch-based ethanol. As a result, economics and policy incentives could, in the near future, encourage expansion of cellulosic biofuels production from grasses, forest woody biomass, and agricultural and municipal wastes. If production expands, cultivation of cellulosic feedstock crops, such as switchgrass ( Panicum virgatum L. ) and miscanthus ( Miscanthus species ), is expected to increase dramatically. The main objective of this study is to identify grasslands in the Great Plains that are potentially suitable for cellulosic feedstock (such as switchgrass) production. Producing ethanol from noncropland holdings (such as grassland) will minimize the effects of biofuel developments on global food supplies. Our pilot study area is the Greater Platte River Basin, which includes a broad range of plant productivity from semiarid grasslands in the west to the fertile corn belt in the east. The Greater Platte River Basin was the subject of related U.S. Geological Survey (USGS) integrated research projects.

Colorado;Nebraska;South Dakota;Wyoming↗

USGS2011

Identifying grasslands suitable for cellulosic feedstock crops in the Greater Platte River Basin: dynamic modeling of ecosystem performance with 250 m eMODIS

This study dynamically monitors ecosystem performance (EP) to identify grasslands potentially suitable for cellulosic feedstock crops (e.g., switchgrass) within the Greater Platte River Basin (GPRB). We computed grassland site potential and EP anomalies using 9-year (2000–2008) time series of 250 m expedited moderate resolution imaging spectroradiometer Normalized Difference Vegetation Index data, geophysical and biophysical data, weather and climate data, and EP models. We hypothesize that areas with fairly consistent high grassland productivity (i.e., high grassland site potential) in fair to good range condition (i.e., persistent ecosystem overperformance or normal performance, indicating a lack of severe ecological disturbance) are potentially suitable for cellulosic feedstock crop development. Unproductive (i.e., low grassland site potential) or degraded grasslands (i.e., persistent ecosystem underperformance with poor range condition) are not appropriate for cellulosic feedstock development. Grassland pixels with high or moderate ecosystem site potential and with more than 7 years ecosystem normal performance or overperformance during 2000–2008 are identified as possible regions for future cellulosic feedstock crop development (ca. 68 000 km 2 within the GPRB, mostly in the eastern areas). Long-term climate conditions, elevation, soil organic carbon, and yearly seasonal precipitation and temperature are important performance variables to determine the suitable areas in this study. The final map delineating the suitable areas within the GPRB provides a new monitoring and modeling approach that can contribute to decision support tools to help land managers and decision makers make optimal land use decisions regarding cellulosic feedstock crop development and sustainability.

Nebraska;Wyoming;Colorado;Kansas;South Dakota↗