Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/69801
Title: Comparison of land cover maps using high resolution multispectral and hyperspectral imagery
Authors: Marcello, J. 
Rodríguez-Esparragón, D. 
Vega Moreno, Daura 
UNESCO Clasification: 2504 Geodesia
Keywords: Casi
Hyperspectral
Land Use Land Cover
Obia Classification
Support Vector Machines
Issue Date: 2018
Journal: IEEE International Geoscience and Remote Sensing Symposium proceedings 
Conference: 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 
Abstract: Land cover information is a fundamental parameter in a wide range of applications like urban growth, land degradation, climate change, food security, environmental sustainability, etc. In this context, remote sensing satellites can provide valuable data to allow the generation of thematic maps. On the other hand, the recent availability of hyperspectral sensors on board aircrafts and drones offers an opportunity to improve the resolution and accuracy of land cover maps. In island territories, where land is usually a scarce resource, the need of very high spatial resolution (VHR) is essential. In this context, we have generated VHR land cover maps using multispectral Worldview data and hyperspectral airborne CASI information. In particular, after corrections and pansharpening enhancements, we have analyzed pixel-based and object-based classification approaches using different input band combinations. We have compared the performance when using multispectral or hyperspectral imagery and its robustness depending on the quality of the training samples considered.
URI: http://hdl.handle.net/10553/69801
ISBN: 9781538671504
ISSN: 2153-6996
DOI: 10.1109/IGARSS.2018.8517878
Source: International Geoscience and Remote Sensing Symposium (IGARSS) [2153-6996] ,v. 2018-July, p. 7312-7315
Appears in Collections:Actas de congresos
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