Centre de documentation
scientifique

Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 94 - 104 Titre : Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Jean-Claude Thill, Auteur ; Sutee Anantsuksomsri, Auteur ; Nij Tontisirin, Auteur ; Ran Tao, Auteur Année de publication : 2018 Article en page(s) : pp 94 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] Birmanie [Termes IGN] Chine [Termes IGN] croissance des arbres [Termes IGN] dendrochronologie [Termes IGN] Hevea brasiliensis [Termes IGN] image Landsat [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Laos [Termes IGN] modèle de croissance végétale [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] plantation forestière [Termes IGN] série temporelle Résumé : (Auteur) Rubber (Hevea brasiliensis) plantations are a rapidly increasing source of land cover change in mainland Southeast Asia. Stand age of rubber plantations obtained at fine scales provides essential baseline data, informing the pace of industrial and smallholder agricultural activities in response to the changing global rubber markets, and local political and socioeconomic dynamics. In this study, we developed an integrated pixel- and object-based tree growth model using Landsat annual time series to estimate the age of rubber plantations in a 21,115 km2 tri-border region along the junction of China, Myanmar and Laos. We produced a rubber stand age map at 30 m resolution, with an accuracy of 87.00% for identifying rubber plantations and an average error of 1.53 years in age estimation. The integration of pixel- and object-based image analysis showed superior performance in building NDVI yearly time series that reduced spectral noises from background soil and vegetation in open-canopy, young rubber stands. The model parameters remained relatively stable during model sensitivity analysis, resulting in accurate age estimation robust to outliers. Compared to the typically weak statistical relationship between single-date spectral signatures and rubber tree age, Landsat image time series analysis coupled with tree growth modeling presents a viable alternative for fine-scale age estimation of rubber plantations. Numéro de notice : A2018-399 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.003 Date de publication en ligne : 13/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90828 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018101	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018103	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018102	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery / J. Dong in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 74 (Novembrer 2012) . - pp 20 - 33 Titre : Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery Type de document : Article/Communication Auteurs : J. Dong, Auteur ; X. Xiao, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 20 - 33 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] afforestation [Termes IGN] carte de la végétation [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal [Termes IGN] forêt tropicale [Termes IGN] Hainan (Chine) [Termes IGN] Hevea brasiliensis [Termes IGN] image ALOS-PALSAR [Termes IGN] image Terra-MODIS [Termes IGN] traitement d'image [Termes IGN] zone tropicale humide Résumé : (Auteur) Knowledge of the spatial distribution of forest types in tropical regions is important for implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD), better understanding of the global carbon cycle, and optimal forest management. Frequent cloud cover in moist tropical regions poses challenges for using optical images to map and monitor forests. Recently, Japan Aerospace Exploration Agency (JAXA) released a 50 m orthorectified mosaic product from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS). PALSAR data provides information about the land surface without cloud interference. In this study we use the fine beam dual (FBD) polarization PALSAR 50 m mosaic imagery and a Neural Network (NN) method to produce a land cover map in Hainan Island, China. Subsequently, forest areas are classified into evergreen and deciduous forests and rubber plantations are mapped using vegetation and land surface water indices derived from 250 to 500 m resolution MODIS products. The PALSAR 50 m forest cover map, MODIS-based forest types and rubber plantation maps are fused to generate fractional maps of evergreen forest, deciduous forest and rubber plantation within 500 m or 250 m pixels. PALSAR data perform well for land cover classification (overall accuracy = 89% and Kappa Coefficient = 0.79) and forest identification (both the Producer’s Accuracy and User’s Accuracy are higher than 92%). The resulting land cover maps of forest, cropland, water and urban lands are consistent with the National Land Cover Dataset of China in 2005 (NLCD-2005). Validation from ground truth samples indicates that the resultant rubber plantation map is highly accurate (the overall accuracy = 85%). Overall, this study provides insight on the potential of integrating cloud-free 50 m PALSAR and temporal MODIS data on mapping forest types and rubber plantations in moist tropical regions. Numéro de notice : A2012-603 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.07.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.07.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32049 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2012081	SL	Revue	Centre de documentation	Revues en salle	Disponible

Cours d'apprentissage agricole 2ème année, 4. L'hévéa / Inades-formation (1986)

Public Titre de série : Cours d'apprentissage agricole 2ème année, 4 Titre : L'hévéa Type de document : Guide/Manuel Auteurs : Inades-formation, Auteur Editeur : Abidjan : Inadès-Formation Année de publication : 1986 Collection : Productions de l'agriculteur Importance : 50 p. Format : 14 x 21 cm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Agriculture [Termes IGN] Hevea brasiliensis [Termes IGN] plantation agricole Numéro de notice : 56681D Affiliation des auteurs : non IGN Thématique : FORET Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=48406

Voir aussi

• Cours d'apprentissage agricole 2ème année, 1. Le caféier robusta / Inades-formation (1986)
• Cours d'apprentissage agricole 2ème année, 2. Le cacaoyer / Inades-formation (1986)
• Cours d'apprentissage agricole 2ème année, 3. Le palmier à huile / Inades-formation (1986)