Centre de documentation
scientifique

The application of ASTER imageries and mathematical evaluation method in detecting cyanobacteria in biological soil crust, Chadormalu area, Central Iran / A. Moghtaderi in Photo interprétation, European journal of applied remote sensing, vol 47 n° 2 - 3 (juin 2011)

Public [article]  inPhoto interprétation, European journal of applied remote sensing > vol 47 n° 2 - 3 (juin 2011) . - pp 41 - 55 Titre : The application of ASTER imageries and mathematical evaluation method in detecting cyanobacteria in biological soil crust, Chadormalu area, Central Iran Titre original : Détection de croûtes biologiques à l'aide de l'imagerie ASTER. Exemple de la zone de Chadormalu, Iran central Type de document : Article/Communication Auteurs : A. Moghtaderi, Auteur ; F. Moore, Auteur ; M. Taghavi, Auteur ; R. Rezaei, Auteur Année de publication : 2011 Article en page(s) : pp 41 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] croute terrestre [Termes IGN] désert [Termes IGN] image multibande [Termes IGN] image Terra-ASTER [Termes IGN] Iran [Termes IGN] micro-organisme [Termes IGN] réflectance du sol Résumé : (Auteur) Soil surfaces in arid and semi-arid lands often lack photoautotrophic life but are covered by communities of soil surface covering organisms able to tolerate dehydration and thus adapted to aridity. One of the important objectives of multi-spectral remote sensing instruments is the detection of the optical characteristics of the Earth's surface using high spectral resolution bands. In this study ASTER imagery and reflected radiation in VNIR bands were used to investigate Biological Soil Crusts (BSCs) in the field. By applying IARR (Internal Average Relative Reflectance), FCC (False Color Composite), MNF (Minimum Noise Fraction Transform), MEM (Mathematical Evaluation Method) techniques, BSCs are successfully detected in the Chadormalu desert area of central Iran.This study clearly shows the capability of ASTER data (VNIR bands) to detect BSC or cyanobacteria soil crusts. The MEM method is suggested as an accurate tool for full scale studies. Numéro de notice : A2011-533 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73757 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
104-2011021	SL	Revue	Centre de documentation	Revues en salle	Exclu du prêt