Publications

The ASPRS Lidar Cal/Val (calibration/validation) Working Group led by the US Geological Survey (USGS) to establish “Guidelines on Geometric Accuracy and Quality of Lidar Data” has made excellent progress via regular teleconferences and meetings. The group is focused on identifying data quality metrics and establishing a set of guidelines for quantifying the quality of lidar data. The...

The El Niño–Southern Oscillation (ENSO) is the leading mode of interannual variability, with global impacts on weather and climate that have seasonal predictability. Research on the link between interannual ENSO variability and the leading mode of intraseasonal variability, the Madden–Julian oscillation (MJO), has focused mainly on the role of MJO initiating or terminating ENSO. We use

Landsat Surface Reflectance Climate Data Records (CDRs) are high level Landsat data products that support land surface change studies. Climate Data Records, as defined by the National Research Council, are a time series of measurements with sufficient length, consistency, and continuity to identify climate variability and change. The U.S. Geological Survey (USGS) is using the valuable 40...

Continental Africa has the highest volume of water stored in wetlands, large lakes, reservoirs, and rivers, yet it suffers from problems such as water availability and access. With climate change intensifying the hydrologic cycle and altering the distribution and frequency of rainfall, the problem of water availability and access will increase further. Famine Early Warning Systems...

With increased changes in land cover and global climate, early detection and warning of dust storms in conjunction with effective and widespread information broadcasts will be essential to the prevention and mitigation of future risks and impacts. Human activities, seasonal variations and long-term climatic patterns influence dust storms. More research is needed to analyse these factors...

U.S. Geological Survey (USGS) data represent corporate assets with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. Recognizing these motives, a USGS team developed a Science Data Lifecycle Model (SDLM) as a high-level view of data—from conception through preservation and sharing—to illustrate how...

Increasing pressure to feed the growing population with scarce water resources requires accurate and routine cropland mapping. This paper develops and implements a rule-based automated cropland classification algorithm (ACCA) using multi-sensor remote sensing data. Pixel-by-pixel accuracy assessments showed that ACCA produced an overall accuracy of 96 percent (Khat = 0.8) when tested...

With the acquisition of lidar data for over 30 percent of the US, it is now possible to assess the three-dimensional distribution of features at the national scale. This paper integrates over 350 billion lidar points from 28 disparate datasets into a national-scale database and evaluates if height above ground is an important variable in the context of other nationalscale layers, such as...

In this study we implement and evaluate a simple 'hybrid' forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble's (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and...

The U.S. Soil Survey Geographic (SSURGO) database provides detailed soil mapping for most of the conterminous United States (CONUS). These data have been used to formulate estimates of soil carbon stocks, and have been useful for environmental models, including plant productivity models, hydrologic models, and ecological models for studies of greenhouse gas exchange. The data were...

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than...

The LANDFIRE National Project (LF_1.0.0) was successfully completed in 2009. The goal of LANDFIRE National was to generate consistent 2001 vintage 30 meter spatial data sets for all 50 States for fire and other natural resource applications. This report highlights results from the continuation of LANDFIRE as a program to update the spatial data layers through 2008. The focus of this...