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Proceedings Paper

Vulnerable land ecosystems classification using spatial context and spectral indices
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Paper Abstract

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

Paper Details

Date Published: 5 October 2017
PDF: 10 pages
Proc. SPIE 10428, Earth Resources and Environmental Remote Sensing/GIS Applications VIII, 104280V (5 October 2017); doi: 10.1117/12.2278496
Show Author Affiliations
Edurne Ibarrola-Ulzurrun, Univ. de Las Palmas de Gran Canaria (Spain)
Univ. Politécnica de Madrid (Spain)
Consuelo Gonzalo-Martín, Univ. Politécnica de Madrid (Spain)
Javier Marcello, Univ. de Las Palmas de Gran Canaria (Spain)

Published in SPIE Proceedings Vol. 10428:
Earth Resources and Environmental Remote Sensing/GIS Applications VIII
Ulrich Michel; Karsten Schulz, Editor(s)

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