Publications

Federal Clean Water Act requires that states develop Total Maximum Daily Loads (TMDLs) for water bodies. Once the state has developed an inventory of TMDLs, it is required to provide public notice of the report and have it approved by the Environmental Protection Agency. The South Dakota Department of Environment and Natural Resources (DENR) is using the USDA’s annualized Agricultural...

Urban development has expanded rapidly in Las Vegas, Nevada, over the last fifty years. To assess urban land use change in the area, a sub-pixel change detection approach has been used to map urban extent and its temporal changes by determining sub-pixel level impervious surface areas from Landsat satellite remote sensing data in conjunction with digital orthophotography. Sub-pixel...

Current uncertainty in quantifying the global carbon budget remains a major contributing source of uncertainty in reliably projecting future climate change. Furthermore, quantifying the global carbon budget and characterizing uncertainties have emerged as critical to a successful implementation of United National Framework Convention on Climate Change and its Kyoto Protocol. Beyond...

Carbon-cycle models have uncertainties associated with data inputs, parameters, and model algorithms. The prerequisite for an applicable model is that it should perform at an acceptable level of accuracy and uncertainties should be documented. In this study, we validated the gross primary productivity (GPP) data from a piecewise regression (PWR) model and the MODIS GPP model at five...

No abstract available.

Over the past 200 years, changes to the Nation's urban areas have been dramatic. Changes that have occurred relate both to the location of urban centers, as well as to the spatial extent of land dedicated to urban uses. Urban areas at the beginning of the 19th century were located primarily along major rivers or bodies of water, as waterways provided the most efficient means for...

The long-term, 34+ year record of global Landsat remote sensing data is a critical resource to study the Earth system and human impacts on this system. The National Satellite Land Remote Sensing Data Archive (NSLRSDA) is charged by public law to: “maintain a permanent, comprehensive Government archive of global Landsat and other land remote sensing data for long-term monitoring and study...

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI...

The Landsat-7 Enhanced Thematic Mapper Plus instrument has two selectable gains for each spectral band. In the acquisition plan, the gains were initially set to maximize the entropy in each scene. One unintended consequence of this strategy was that, at times, dense vegetation saturated band 4 and deserts saturated all bands. A revised strategy, based on a land-cover classification and...

Oscillations in radiometric gains of the short wave infrared (SWIR) bands in Landsat-4 (L4) and Landsat-5 (L5) Thematic Mappers (TMs) are observed through an analysis of detector responses to the Internal Calibrator (IC) pulses. The oscillations are believed to be caused by an interference effect due to a contaminant film buildup on the window of the cryogenically cooled dewar that...

Tethered balloon remote sensing platforms can be used to study radiometric issues in terrestrial ecosystems by effectively bridging the spatial gap between measurements made on the ground and those acquired via airplane or satellite. In this study, the Short Wave Aerostat-Mounted Imager (SWAMI) tethered balloon-mounted platform was utilized to evaluate linear and nonlinear spectral...

Much of the effort in data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand...