Thomas Loveland (Former Employee)

The US Geological Survey's Land Cover Trends is a research projects aimed to understand the rates, trends, causes, and consequences of contemporary US land use and land-cover change. The project is using the EPA Level III eco-regions as a geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The results are expected

The international land-cover community has been working with GEO since 2005 to build the foundations for land-cover observations as an integral part of a Global Earth Observation System of Systems (GEOSS). The Group on Earth Observation (GEO) has provided the platform to elevate the societal relevance of land cover monitoring and helped to link a diverse set of global, regional, and national activ

Quantification of the effects of land use/land cover (LULC) changes on proximal measurements of near-surface air temperature is crucial to a better understanding of natural and anthropogenically induced climate change. In this study, data from stations utilized in deriving U.S. climatological temperature normals were analyzed in conjunction with NCEP-NCAR 50-Year Reanalysis (NNR) estimates and hig

Landsat data have enabled continuous global monitoring of both human-caused and other land cover disturbances since 1972. Recently degraded performance and intermittent service of the Landsat 7 and Landsat 5 sensors, respectively, have raised concerns about the condition of global Earth observation programs. However, Landsat imagery is still useful for landscape change detection and this capabilit

Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. Thes

Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy resp

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, managemen

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern Unite

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project

Mapping tools are needed to document the location and extent of Phragmites australis, a tall grass that invades coastal marshes throughout North America, displacing native plant species and degrading wetland habitat. Mapping Phragmites is particularly challenging in the freshwater Great Lakes coastal wetlands due to dynamic lake levels and vegetation diversity. We tested the applicability of Hyper

BackgroundTillage practices greatly affect carbon (C) stocks in agricultural soils. Quantification of the impacts of tillage on C stocks at a regional scale has been challenging because of the spatial heterogeneity of soil, climate, and management conditions. We evaluated the effects of tillage management on the dynamics of soil organic carbon (SOC) in croplands of the Northwest Great Plains ecore

Two spatially-explicit estimates of gross primary production (GPP) are available for the Northern Great Plains. An empirical piecewise regression (PWR) GPP model was developed from flux tower measurements to map carbon flux across the region. The Moderate Resolution Imaging Spectrometer (MODIS) GPP model is a process-based model that uses flux tower data to calibrate its parameters. Verification a