Geology topics

Rick Mueller

Publications and source records attributed to Rick Mueller.

3 recordsLinked to original sources

USGS2025

An interagency perspective on improving consistency and transparency of land use and land cover mapping

Executive Summary Geospatial products of land use and land cover are broadly used in many applications. For example, the annual national greenhouse gas inventory uses the National Land Cover Database, the Coastal Change Analysis Program, Landscape Fire and Resource Management Planning Tools, the Forest Inventory and Analysis, and the National Resources Inventory to represent the land use and management base of the United States and attribute sources and sinks of greenhouse gas emissions. Federally produced land use and land cover datasets for the United States, including those from the Multi-Resolution Land Characteristics Consortium, set the foundation for developing and informing applications such as land change, conservation, greenhouse gas monitoring, urban planning, agricultural production, ecosystem functions, and water quantity and use. No single land use and land cover product is optimal for all land use and land cover applications. Approaches for defining and mapping land use and land cover classes differ across Federal map products, reflecting the tailoring of product specifications to match specific agency needs. These differing approaches present a challenge when attempting to integrate and harmonize multiple land use and land cover products into single analysis or application frameworks. Nuanced understanding of how these products are designed and produced may not be immediately evident to users; however, the availability of a diverse suite of products also represents an opportunity, providing multiple approaches for observing landscape change. In response to the National Strategy to Advance an Integrated U.S. Greenhouse Gas Measurement, Monitoring, and Information System, this Multi-Resolution Land Characteristics Consortium-led interagency report presents (1) the current status of U.S. Federal land use and land cover products (as of May 2024), (2) existing synergies and integration among these federally produced land use and land cover products, (3) inherent challenges of creating a single consistent framework, and (4) strategies for collectively tackling these challenges to improve coordination and collaboration among data producers and facilitate the adoption of land use and land cover products for greenhouse gas monitoring and a variety of other applications.

Circular↗

USGS2014

The Multi-Resolution Land Characteristics (MRLC) Consortium: 20 years of development and integration of USA national land cover data

The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Project (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.

Remote Sensing↗

USGS2014

Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm

Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer’s accuracy of 93% and a user’s accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of ≥95% for cultivated croplands and ≥76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.

California↗