Extraction of Remote Sensing Information of LONGAN Under Support of “3S” Technology in Guangxi Province - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

Extraction of Remote Sensing Information of LONGAN Under Support of “3S” Technology in Guangxi Province

Résumé

This paper presents an automatic approach to planting areas extraction for mixed vegetation and hilly region, more cloud using moderate spatial resolution and high temporal resolution MODIS data around Guangxi province, south of China. The Maximum likelihood was used to extract the information of longan planting and their spatial distribution through the calculation of multiple-phase MODIS-NDVI in Guangxi and ten stylebook training regions of longan of being selected by GPS. Compared with the large and little regions of longan planting in monitoring image and the investigation of on the spot with GPS, the resolute shows that the longan planting information in remote sensing image are true. In this research, multiple-phase MODIS data were received during longan main growing season and preprocessed; NDVI temporal profiles of longan were generated; models for planting areas extraction were developed based on the analysis of temporal NDVI curves; and spatial distribution map of planting areas of longan in Guangxi in 2009 were created. The study suggests that it is possible to extract planting areas automatically from MODIS data for large areas.
Fichier principal
Vignette du fichier
978-3-642-18333-1_85_Chapter.pdf (1.63 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01559592 , version 1 (10-07-2017)

Licence

Paternité

Identifiants

Citer

Xin Yang, Chaohui Wu, Weiping Lu, Yuhong Li, Shiquan Zhong. Extraction of Remote Sensing Information of LONGAN Under Support of “3S” Technology in Guangxi Province. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.711-716, ⟨10.1007/978-3-642-18333-1_85⟩. ⟨hal-01559592⟩
38 Consultations
70 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More