|Title:||Extended linear mixing model in an ecosytem with high spectral variability||Authors:||Ibarrola-Ulzurrun, Edurne
|UNESCO Clasification:||250616 Teledetección (Geología)||Keywords:||Ecosystem Management
|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:||Hyperspectral imagery (HSI) has become an important tool in ecosystem conservation due to its capability to perform accurate spectral unmixing, for vegetation mapping and ecosystem monitoring. An issue to be solved is the spectral variability of endmembers that can be induced by sensor noise and topographic changes. This spectral variability is considered by the Extended Linear Mixing Model (ELMM), which is applied to a mountainous ecosystem with high spectral variability and radiometric changes in each swath. The results obtained are very satisfactory, achieving reasonable abundance estimations and accurate characterization of the variability within the scene. ELMM allows studying the features of each pixel, including additional information about the characterization of the mixed pixels, in HSI by taking spectral variability into account. Moreover, it is observed that ELMM is robust to the absence of pure pixels as well as to noise.||URI:||http://hdl.handle.net/10553/69872||ISBN:||9781538671504||ISSN:||2153-6996||DOI:||10.1109/IGARSS.2018.8519128||Source:||International Geoscience and Remote Sensing Symposium (IGARSS) [ISSN 2153-6996], v. 2018-July, p. 2685-2688|
|Appears in Collections:||Actas de congresos|
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