High Resolution Satellite Imagery for Environmental Engineering
Posted on June 27th, 2012

High Resolution Satellite Imagery in Support of Environmental Engineering

Project Description

Arcadis is an international engineering, consultancy and design firm with 15,000+ professionals solving water, infrastructure and environmental challenges. In late 2011, Apollo Mapping assisted Arcadis with its need for high resolution satellite imagery in support of an environmental project. Working on a rural site in New Mexico for a local mining company, this multi-decade project involves a variety of players including government regulatory agencies, the local community and resource users. Arcadis works closely with these groups, balancing their individual needs in support of the larger project goals of environmental restoration, monitoring and remediation of past and current mining activities. Of particular concern is wind-blown dust and mine tailings given the wide-open rural landscape, dry weather conditions and common wind gusts.

Geospatial Data and Spatial Analysis

Spatial analysis utilizing a variety of geospatial datasets and technologies is an important component of Arcadis’ overall decision making process for this environmental project. Apollo Mapping was contracted to provide high resolution satellite imagery from the vender that could deliver newly tasked data the quickest during a narrow section of the growing season. IKONOS was selected for this project as Geoeye provided us with the shortest tasking feasibility at one month. GeoEye obtained and delivered a cloud-free bundle of georeferenced IKONOS 3.2-meter 4-band multispectral and 80-centimeter panchromatic imagery less than two weeks after order confirmation.


Natural color 80-cm IKONOS imagery collected over Arcadis’ rural site in New Mexico, USA.

Upon receipt of the raw imagery, Arcadis processed the data with ERDAS IMAGINE to create a variety of layers for further spatial analysis. By fusing the multispectral and panchromatic data in a process called pansharpening, they were able to create natural color imagery with 80-cm resolution. Orthorectification of both the pansharpened and raw IKONOS imagery allowed Arcadis to match the 2011 imagery to historic datasets – a step that is important for assessing changes in ecological communities through time. ERDAS was also used to calculate several indices that assess plant health, including the Normalized Difference Vegetation Index (NDVI) and the Transformed Normalized Difference Vegetation Index (TNDVI).


False color 80-cm IKONOS imagery collected over Arcadis’ rural site in New Mexico; red areas are healthy vegetation.

For the next steps in the analysis, Arcadis employed Esri ArcMap 10.0 for its ability to display and work with multiple spatial datasets simultaneously. Visual inspection of the pansharpened natural color IKONOS imagery was used to map the extent of vegetation communities. These digital maps (i.e. vectors) were compared to similar maps that were extracted from historic datasets in order to assess change in their extents through time. The NDVI and TNDVI layers created with ERDAS can reveal areas of unhealthy vegetation that might not be visible with the human eye. Unhealthy vegetation can be an early indicator of environment damage that warrants additional study and remediation by Arcadis.

The true power of ArcMap for spatial analysis is its ability to combine multiple spatial layers with unbiased statistical and mathematical approaches. These approaches, which include cluster analysis, geographically weighted regression and spatial overlays, can reveal patterns in data that might be missed by visual inspection alone. In their project, Arcadis used a wide variety of spatial layers – e.g. cultural data, current and past vegetative health, soil chemistry – to identify areas that: were healthy and stable; had improving health; and those that were at-risk of further environmental degradation. The results of this spatial analysis have been key to making informed decisions on where to focus remediation efforts and where additional field research is required.

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