Integrating Traditional Ecological Knowledge and Remote Sensing for Monitoring Rangeland Dynamics in the Altai Mountain Region.

Integrating traditional ecological knowledge (TEK) with remote sensing capabilities to monitor rangeland dynamics could lead to more acceptable, efficient, and beneficial rangeland management schemes for stakeholders of grazing systems. We contrasted pastoralists' perception of summer pasture quality in the Altai Mountains of Central Asia with normalized difference vegetation index (NDVI) metrics obtained from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. The spatial relationship between satellite-based assessment of the grassland quality and on-the-ground evaluation by local herders was first assessed for a single year using 49, 1 × 1 km grassland blocks sampled in July 2013.

Glacial lake inventory and lake outburst potential in Uzbekistan.

Climate change has been shown to increase the number of mountain lakes across various mountain ranges in the World. In Central Asia, and in particular on the territory of Uzbekistan, a detailed assessment of glacier lakes and their evolution over time is, however lacking. For this reason we created the first detailed inventory of mountain lakes of Uzbekistan based on recent (2002-2014) satellite observations using WorldView-2, SPOT5, and IKONOS imagery with a spatial resolution from 2 to 10m.

Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands.

Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions.

Accuracy assessment of land cover/land use classifiers in dry and humid areas of Iran.

Land cover/land use (LCLU) maps are essential inputs for environmental analysis. Remote sensing provides an opportunity to construct LCLU maps of large geographic areas in a timely fashion. Knowing the most accurate classification method to produce LCLU maps based on site characteristics is necessary for the environment managers.

Sustainable development under population pressure: lessons from developed land consumption in the conterminous U.S.

Population growth will result in a significant anthropogenic environmental change worldwide through increases in developed land (DL) consumption. DL consumption is an important environmental and socioeconomic process affecting humans and ecosystems. Attention has been given to DL modeling inside highly populated cities.

Integrating local and global error statistics for multi-scale RBF network training: an assessment on remote sensing data.

Background: This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the proposed MSRBF network relies on the integration of both local and global error statistics in the node selection process.

Methodology And Principal Findings: The method was tested on a binary classification task, detection of impervious surfaces using a Landsat satellite image, and a regression problem, simulation of waveform LiDAR data.

Spatial wildlife-vehicle collision models: a review of current work and its application to transportation mitigation projects.

In addition to posing a serious risk to motorist safety, vehicle collisions with wildlife are a significant threat for many species. Previous spatial modeling has concluded that wildlife-vehicle collisions (WVCs) exhibit clustering on roads, which is attributed to specific landscape and road-related factors. We reviewed twenty-four published manuscripts that used generalized linear models to statistically determine the influence that numerous explanatory predictors have on the location of WVCs.