• crisp - binary yes/no pixel assignment,
• fuzzy - probability-per-class pixel assignment,
• hybrid - combination using ancillary data,
• cart - classification and regression tree analysis.

Object Based Classification  -  We segment the imagery into homologous vector polygon "objects" by using:  scale, color, texture parameters and apply hierarchical rules for per pixel classification.

Pixel Based Classification  -  We use spectral clustering / ISODATA (Iterative Self Organizing Data Analysis Technique) to implement various statistically based classifiers that consider each pixel's multi-layer value without consideration of its neighbors.  Innovative classifier supervision is possible.

Classification Accuracy Assessment  -  Accuracy specifications cited in our proposals are meant to endure rigorous comparisons to independent accuracy assessment surveys reporting omission and commission error on a per-theme and overall basis.

Raster to Vector Feature Extraction  -  We offer geometrically smooth lightweight accurate thematic data in topologically clean "line" and "polygon" formats from the following data sources.

• Multi-spectral and Panchromatic Imagery
• Lidar Data
• Paper Maps

Land Cover / Land Use (LC/LU) Change Analysis
Imagery based thematic change detection analysis provides methodological versatility when updating LC/LU layers.  A good change analysis product is augmented with a thematic "from-to" category layer and various statistics.  We are experienced with these general methods ...

• multi-temporal compositing  -  offers quick and potentially effective results.  It requires cloud-free imagery collected on near-anniversary dates by similar sensor models.
• cross correlation  -  offers more flexibility with source data requirements by allowing the initial ("from") image data to be thematically classified.
• post classification  -  offers the most flexibility by accepting thematically classified ("from") and ("to") input imagery.  It can be effectively used to mitigate extreme variation between ("from") and ("to") environmental conditions.