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Remote Sensing Solutions for Environmental and Climate Change Analysis

The potential wetland areas for restoration at the MolyCorp Mine Site, New Mexico. Abt Global uses remote sensing in a range of environmental applications.

Identifying Habitats Suitable for Restoration

For example, we classified wetlands from high resolution multispectral satellite data (Quickbird) as part of natural resource damage assessment (NRDA) at the former MolyCorp Mine Site in New Mexico. The satellite imagery was used to help identify wetland areas that might be suitable for restoration to compensate for damages quantified in the NRDA.

Finding Mine Waste Areas

At another NRDA site, we classified mine waste from panchromatic aerial photos and Landsat TM imagery to quantify and delineate mine waste areas. To differentiate mine waste from other barren features – such as urban areas and fallow fields – we used a combination of supervised and unsupervised classification techniques to increase spectral differences between similar features. We then checked these results against high-resolution photographs of known waste piles to confirm that our technique was effective.

Evaluating Drinking Water Quality in Peru

Analysis of snow cover using remote sensing imagery used for analysis of impacts of climate change on ski areas. We have also used geographic information systems (GIS) and remote sensing to evaluate potential water quality and water quantity effects near the Yanacocha Mining District in Peru, one of the largest gold mines in the world. For a project on behalf of the Compliance Advisor Ombudsman for International Finance Corporation, we evaluated how large-scale changes in vegetation communities influenced the timing and magnitude of infiltration, runoff, and the availability of drinking water for downstream users using land cover data from a combination of remotely sensed data sets as inputs to a water quantity model.

Studying the Impact of Climate Change on Skiing

Abt staff also used spatial outputs from Global Climate Models and snow-covered area to model how climate change estimates will affect the recreational skiing and water supply for several resorts and communities, including ski resorts in Aspen, Colo., Park City, Utah, and water quantity in the Boulder, Colo. watershed. We used remote sensing analysis to derive snow cover area used in the modeling from remotely sensed data sets (Landsat, ASTER, and MODIS) using the Normalized Difference Snow Index (NDSI). 
North America