Advanced Classification of Remote Sensing High Resolution Imagery. An Application for the Management of Natural Resources

Advanced image processing techniques applied to high-resolution remote sensing imagery significantly enhance the accuracy of thematic maps for ecosystem conservation, particularly in UNESCO World Heritage Sites. The study demonstrates that both pixel-based and object-based (OBIA) approaches using Support Vector Machine classifiers yield highly accurate results when combined with optimized pre-processing steps, such as Weighted Wavelet ‘à trous’ and Fast Intensity Hue Saturation techniques, followed by orthorectification via RPC models and atmospheric correction using the 6S algorithm. These methods were effectively applied to three Canary Island ecosystems—Teide National Park, Maspalomas Natural Reserve, and Corralejo and Islote de Lobos Natural Park—showing promise for improving natural resource management through precise thematic mapping.

Ibarrola-Ulzurrun, E., Marcello, J., & Gonzalo-Martin, C. (2017). Advanced Classification of Remote Sensing High Resolution Imagery. An Application for the Management of Natural Resources. Developments and Advances in Intelligent Systems and Applications, 1–13. https://doi.org/10.1007/978-3-319-58965-7_1