Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Agriculture”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40Linked to original sources
USGS1999

Waterfowl density on agricultural fields managed to retain water in winter

Managed water on private and public land provides habitat for wintering waterfowl in the Mississippi Valley, where flood control projects have reduced the area of natural flooding. We compared waterfowl densities on rice, soybean, and moist-soil fields under cooperative agreements to retain water from 1 November through 28 February in Arkansas and Mississippi and assessed temporal changes in waterfowl density during winter in 1991-1992 and 1992-1993. Fields flooded earlier in Arkansas, but retained water later in Mississippi. Over winter, waterfowl densities decreased in Arkansas and increased in Mississippi. Densities of waterfowl, including mallard (Anas platyrhynchos), the most abundant species observed, were greatest on moist-soil fields. However, soybean fields had the greatest densities of northern shoveler (Spatula clypeata).

Wildlife Society Bulletin↗
USGS2011

Hyperspectral remote sensing of vegetation and agricultural crops: Knowledge gain and knowledge gap after 40 years of research

The focus of this chapter was to summarize the advances made over last 40+ years, as reported in various chapters of this book, in understanding, modeling, and mapping terrestrial vegetation using hyperspectral remote sensing (or imaging spectroscopy) using sensors that are ground-based, truck-mounted, airborne, and spaceborne. As we have seen in various chapters of this book and synthesized in this chapter, the advances made include: (a) significantly improved characterization and modeling of a wide array of biophysical and biochemical properties of vegetation, (b) ability to discriminate plant species and vegetation types with high degree of accuracies (c) reducing uncertainties in determining net primary productivity or carbon assessments from terrestrial vegetation, (d) improved crop productivity and water productivity models, (b), (e) ability to access stress resulting from causes such as management practices, pests and disease, water deficit or excess; , and (f) establishing more sensitive wavebands and indices to detect plant water\moisture content. The advent of spaceborne hyperspectral sensors (e.g., NASA’s Hyperion, ESA’s PROBA, and upcoming NASA’s HyspIRI) and numerous methods and techniques espoused in this book to overcome Hughes phenomenon or data redundancy when handling large volumes of hyperspectral data have generated tremendous interest in advancing our hyperspectral applications knowledge base over larger spatial extent such as region, nation, continent, and globe.

Book chapter↗
USGS2015

Water data to answer urgent water policy questions: Monitoring design, available data and filling data gaps for determining the effectiveness of agricultural management practices for reducing tributary nutrient loads to Lake Erie

Throughout its history, the United States has made major investments in assessing natural resources, such as soils, timber, oil and gas, and water. These investments allow policy makers, the private sector and the American public to make informed decisions about cultivating, harvesting or conserving these resources to maximize their value for public welfare, environmental conservation and the economy. As policy issues evolve, new priorities and challenges arise for natural resource assessment, and new approaches to monitoring are needed. For example, informed conservation and use of the nation’s finite fresh water resources in the context of increasingly intensive land development is a priority for today’s policy decisionmakers. There is a need to evaluate whether today’s water monitoring programs are generating the information needed to answer questions surrounding these new policy priorities. The Northeast-Midwest Institute (NEMWI), in cooperation with the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program, initiated this project to explore the types and amounts of water data needed to address water-quality related policy questions of critical concern to today’s policy makers. The collaborating entities identified two urgent water policy questions and conducted case studies in the Northeast-Midwest region to determine the water data needed, water data available, and the best ways to fill the data gaps relative to those questions. This report details the output from one case study and focuses on the Lake Erie drainage basin, a data-rich area expected to be a best-case scenario in terms of water data availability.

Indiana, Michigan, New York, Ohio, Pennsylvania↗