Land Cover Mapping Overview Resource Mapping -- Remote Sensing and GIS for Conservation
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Land Cover Mapping
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Land Cover Mapping

Our multi-scale 3D approach uses a combination of heuristic photointerpretation and spectral classification to map the landscape from the individual tree level to regional vegetation communities and land utilization.

Resource Mapping’s Multi-scale Approach to Vegetation and Land Use Classification

GAP map
  • Fly large-scale transects that identify individual trees, plants or crops.
  • Work with local experts to build a visual key of critical species using selected images from the transects.
  • Classify transects as a geographically distributed sample of species and plant communities across differing topography.
  • Use the transect samples to drive the classification of smaller scale coverage or multispectral satellite imagery.

Mapping vegetation from imagery is complicated by the unique intricacies of each ecosystem. A local expert may understand his region and identify every plant from the ground or small aircraft, but he rarely has the time, skills or inclination to undertake a computerized classification of the vegetation communities. Resource Mapping’s approach captures that local expert’s knowledge to drive its own multispectral classification of the region.

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We fly a low-altitude grid over the area (either in conjunction with higher altitude imagery or as the first step to mapping from satellite data) at a large enough scale for the expert to easily identify and mark individual trees and plants. We then work with the expert in Stereo Analyst to develop a visual key for the critical species as they appear in that specific set of images. This key is used to feature-map and classify large sections of the aerial transects, capturing examples of the different vegetation communities over the range of slope and aspect that will affect their spectral reflectance. When a large enough sample has been processed, the spectral mixture models that characterize each community can be determined and used to drive the regional classification.