Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed in Ohio, USA, which was one of the largest hyperspectral image acquisitions. A hierarchical approach was employed using two different classification algorithms: 'image object segmentation' for level 1 and 'spectral angle mapper' (SAM) for level 2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land-use/land-cover (LULC) classes were urban/built, corn, soya bean, wheat, forest, dry herbaceous, grass, lentic, lotic, urban barren, rural barren and unclassified. The final phase of processing was completed after an extensive quality assurance and quality control (QA/QC) phase with 902 points. The overall accuracy was 83.9%. The data set was made available for public research and application; certainly, this product represents an improvement over more commonly utilized, coarser spatial resolution data sets such as National Land Cover Data (NLCD).
Bibliographical noteFunding Information:
This research was funded by the US Environmental Protection Agency (EPA) through its Office of Research and Development under Contract No. 68-C-02-060. We thank Francois Smith, Christopher Bolton, Michael Diller and Christopher Jengo at the Earth Satellite Corporation for their contributions in classification works, and William Jones, Laura Roy and Michelle Warr for provision of CASI images and related supports. Essential fieldwork and ground truth data were provided by the following scientists from the US EPA’s research facilities in Cincinnati, Ohio: Drs F. Bernard Daniel, Michael B. Griffith, James M. Lazorchak, Tara Maddock, Matthew A. Morrison, Bruce W. Peirano, Joseph P. Schubauer-Berigan, Christopher Schultz and William Shuster. Additional aerial imagery used in this project was generously provided by Dr Lawrence Spencer from the Ohio State University Center for Mapping. We also appreciate Nina Lam at the Louisiana State University, Victor Mesev at the Florida State University and R. Douglas Ramsey at the Utah State University for their external peer review.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)