Centre de documentation
scientifique

L-band SAR for estimating aboveground biomass of rubber plantation in Java Island, Indonesia / Bambang H Trisasongko in Geocarto international, vol 35 n° 12 ([01/09/2020])  

Public [article]  inGeocarto international > vol 35 n° 12 [01/09/2020] . - pp 1327 - 1342 Titre : L-band SAR for estimating aboveground biomass of rubber plantation in Java Island, Indonesia Type de document : Article/Communication Auteurs : Bambang H Trisasongko, Auteur ; David J. Paull, Auteur Année de publication : 2020 Article en page(s) : pp 1327 - 1342 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage automatique [Termes IGN] arbre hors forêt [Termes IGN] bande L [Termes IGN] bilan du carbone [Termes IGN] biomasse aérienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données allométriques [Termes IGN] données polarimétriques [Termes IGN] hevea (genre) [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] Java (île de) Résumé : (auteur) This article discusses an experiment on the estimation of rubber tree biomass using L-band Synthetic Aperture Radar (SAR), to support recent efforts to include trees outside forest in global biomass and carbon accounting. We noted that date of acquisition is important, but certainly the selection of allometric equation serving as the reference data was paramount. Similarly, choosing a proper form of fully polarimetric data was instrumental, although this requires validation in different environmental settings. As expected, modern data mining approaches consistently delivered high accuracy. Extreme learning machine yielded the best estimate in terms of R2 (0.98) and RMSE (1.88 Mg/ha); nonetheless, it also delivered a slight negative estimation. In this case, we found that a variant of random forest produced an outcome without any negative estimation. This research suggests that estimated biomass or carbon information from rubber plantations would be an invaluable candidate for the improvement of global biomass data. Numéro de notice : A2020-480 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1573855 Date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1573855 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95630 [article]

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 rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)  

Public [article]  inGeocarto international > vol 33 n° 6 (June 2018) . - pp 627 - 650 Titre : Mapping rubber trees based on phenological analysis of Landsat time series data-sets Type de document : Article/Communication Auteurs : Janatul Aziera binti Abd Razak, Auteur ; Abdul Rashid bin M. Shariff, Auteur ; Noordin bin Ahmad, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 627 - 650 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] arbre sempervirent [Termes IGN] Arecaceae [Termes IGN] carte agricole [Termes IGN] hevea (genre) [Termes IGN] image Landsat [Termes IGN] Malaisie [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] phénologie [Termes IGN] série temporelle Résumé : (Auteur) This study proposes a strategy for accurate mapping of rubber trees through the analysis of Landsat time series datasets. The phenological dynamics of rubber trees were derived from the Normalized Difference Vegetation Index (NDVI) to verify the three important phenological metrics of rubber trees; defoliation, foliation and their growing stages. A decade (2006–2015) ago, Landsat time series NDVIs were used to study the strength of relationship between rubber trees, evergreen trees and oil palm trees. Two important results that could discriminate these three types of vegetation were found; firstly, a weak relationship of NDVIs between rubber trees and evergreen trees during the defoliation period (r2 = 0.1358) and secondly between rubber trees and oil palm trees during the growing period (r2 = 0.2029). This analysis was verified using Support Vector Machine to map the distribution of the three types of vegetation. An accurate mapping strategy of rubber trees was successfully formulated. Numéro de notice : A2018-143 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1289559 Date de publication en ligne : 13/02/2017 En ligne : https://doi.org/10.1080/10106049.2017.1289559 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89701 [article]

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)