Publications

Evaluation of litterfall production is important for understanding nutrient cycling, forest growth, successional pathways, and interactions with environmental variables in forest ecosystems. Litterfall was intensively studied during the period of 1982-2001 in two subtropical monsoon vegetation gradients in the Dinghushan Biosphere Reserve, Guangdong Province, China. The two gradients include: (1)

[No abstract available]

The Landsat archive provides more than 35 years of uninterrupted multispectral remotely sensed data of Earth observations. Since 1972, Landsat missions have carried different types of sensors, from the Return Beam Vidicon (RBV) camera to the Enhanced Thematic Mapper Plus (ETM+). However, the Thematic Mapper (TM) sensors on Landsat 4 (L4) and Landsat 5 (L5), launched in 1982 and 1984 respectively,

Mass distributions of different soil organic carbon (SOC) fractions are influenced by land use and management. Concentrations of C and N in light- and heavy fractions of bulk soils and aggregates in 0–20 cm were determined to evaluate the role of aggregation in SOC sequestration under conventional tillage (CT), no-till (NT), and forest treatments. Light- and heavy fractions of SOC were separated u

We used seasonal ground total counts and remote sensing and GIS technology to relate elephant (Loxodonta africana africana) distribution at Nazinga Game Ranch to environmental and anthropogenic factors. Variables used in analyses were normalized difference vegetation index, elevation, stream density, density of poaching and human illegal activities, distance to dams, distance to rivers, distance t

Jeff Eidenshink, Brian Schwind, Ken Brewer, Zhi-Liang Zhu, Brad Quayle, and Elected officials and leaders of environmental agencies need information about the effects of large wildfires in order to set policy and make management decisions. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates the National Fire Plan (NFP) and Federal Wildland Fire Management Polici

The ready availability of high-resolution, high-accuracy elevation data proved valuable for development of topographybased products to determine rough estimates of the inundation of New Orleans, La., from Hurricane Katrina. Because of its high level of spatial detail and vertical accuracy of elevation measurements, light detection and ranging (lidar) remote sensing is an excellent mapping technolo

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to

Access to satellite images has been largely limited to communities with specialized tools and expertise, even though images could also benefit other communities. This situation has resulted in underutilization of the data. TerraLook, which consists of collections of georeferenced JPEG images and an open source toolkit to use them, makes satellite images available to those lacking experience with r

The Landsat-5 (L5) Thematic Mapper (TM) detectors of the short wave infrared (SWIR) bands 5 and 7 are maintained on cryogenic temperatures to minimize thermal noise and allow adequate detection of scene energy. Over the instrument's lifetime, gain oscillations are observed in these bands that are caused by an ice-like contaminant that gradually builds up on the window of a dewar that houses these

In an era when the number of Earth-observing satellites is rapidly growing and measurements from these sensors are used to answer increasingly urgent global issues, it is imperative that scientists and decision-makers rely on the accuracy of Earth-observing data products. The characterization and calibration of these sensors are vital to achieve an integrated Global Earth Observation System of Sys

Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts' experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require gra