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Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)
[article]
Titre : Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors Type de document : Article/Communication Auteurs : Pauline Perbet, Auteur ; Michelle Fortin, Auteur ; Anouk Ville, Auteur ; Martin Béland, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : pp 7439 - 7458 Note générale : bibliographie
This work was supported by the Natural Sciences and Engineering Research Council of Canada.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse vectorielle
[Termes IGN] déboisement
[Termes IGN] défrichement
[Termes IGN] détection de changement
[Termes IGN] forêt tropicale
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Indonésie
[Termes IGN] Malaisie
[Termes IGN] surveillance forestièreRésumé : (auteur) Malaysia and Indonesia have been affected by deforestation caused in great part by the proliferation of oil palm plantations. To survey this loss of forest, several studies have monitored these southeast Asian nations with satellite remote sensing alert systems. The methods used have shown potential for this approach, but they are limited by imagery with coarse spatial resolution, low revisit times, and cloud cover. The objective of this research is to improve near real-time operational deforestation detection by combining three sensors: Sentinel-1, Sentinel-2 and Landsat-8. We used Change Vector Analysis to detect changes between non-affected forest and images under analysis. The results were validated using 166 plots of undisturbed forest and confirmed deforestation events throughout Sabah Malaysian State, and from 70 points from drone pictures in Sumatra, Indonesia. Sentinel-2 and Landsat-8 yielded sufficient results in terms of accuracy (less than 11% of commission and omission error). Sentinel-1 had lower accuracy (14% of commission error and 28% of omission error), probably resulting from geometric distortions and speckle noise. During the high cloud-cover season optical sensors took about twice the time to detect deforestation compared to Sentinel-1 which was not affected by cloud cover. By combining the three sensors, we detected deforestations about 8 days after forest clearing events. Deforestations were only detectable during approximately the first 100 days, before bare soils were often coved by legume crop. Our results indicate that near real-time deforestation detection can reveal most events, but the number of false detections could be improved using a multiple event detection process. Numéro de notice : A2019-321 Affiliation des auteurs : ENSG+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2019.1579390 Date de publication en ligne : 17/02/2019 En ligne : https://doi.org/10.1080/01431161.2019.1579390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93295
in International Journal of Remote Sensing IJRS > vol 40 n°19 (February 2019) . - pp 7439 - 7458[article]Long-term land deformation monitoring using quasi-persistent scatterer (Q-PS) technique observed by sentinel-1A : case study Kelok Sembilan / Pakhrur Razi in Advances in Remote Sensing, vol 7 n° 4 (December 2018)
[article]
Titre : Long-term land deformation monitoring using quasi-persistent scatterer (Q-PS) technique observed by sentinel-1A : case study Kelok Sembilan Type de document : Article/Communication Auteurs : Pakhrur Razi, Auteur ; Josaphat Tetuko Sri Sumantyo, Auteur ; Daniele Perissin, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 277 - 289 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] coin réflecteur
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données polarimétriques
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] mouvement de terrain
[Termes IGN] Sumatra
[Termes IGN] surveillance géologiqueRésumé : (Auteur) Located on the mountainous area, Kelok Sembilan flyover area in West Sumatra, Indonesia has a long history of land deformation, therefore monitoring and analyzing as continuously is a necessity to minimize the impact. Notably, in the rainy season, the land deformation occurs along this area. The zone is crucial as the center of transportation connection in the middle of Sumatra. Quasi-Persistent Scatterer (Q-PS) Interferometry technique was applied for extracting information of land deformation on the field from time to time. Not only does the method have high performance for detecting land deformation but also improve the number of PS point, especially in a non-urban area. This research supported by 90 scenes of Sentinel-1A (C-band) taken from October 2014 to November 2017 for ascending and descending orbit with VV and VH polarization in 5 × 20 m (range × azimuth) resolution. Both satellite orbits detected two critical locations of land deformation namely as zone A and Zone B, which located in positive steep slope where there is more than 500 mm movement in the Line of Sight (LOS) during acquisition time. Deformations in the vertical and horizontal direction for both zone, are 778.9 mm, 795.7 mm and 730.5 mm, 751.7 mm, respectively. Finally, the results were confirmed by ground truth data using Unmanned Aerial Vehicle (UAV) observation. Numéro de notice : A2018-617 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.4236/ars.2018.74019 Date de publication en ligne : 14/12/2018 En ligne : https://doi.org/10.4236/ars.2018.74019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92848
in Advances in Remote Sensing > vol 7 n° 4 (December 2018) . - pp 277 - 289[article]Improving large area population mapping using geotweet densities / Nirav N. Patel in Transactions in GIS, vol 21 n° 2 (April 2017)
[article]
Titre : Improving large area population mapping using geotweet densities Type de document : Article/Communication Auteurs : Nirav N. Patel, Auteur ; Forrest R. Stevens, Auteur ; Zhuojie Huang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 317 – 331 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartographie dynamique
[Termes IGN] cartographie statistique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Indonésie
[Termes IGN] recensement
[Termes IGN] répartition géographique
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Many different methods are used to disaggregate census data and predict population densities to construct finer scale, gridded population data sets. These methods often involve a range of high resolution geospatial covariate datasets on aspects such as urban areas, infrastructure, land cover and topography; such covariates, however, are not directly indicative of the presence of people. Here we tested the potential of geo-located tweets from the social media application, Twitter, as a covariate in the production of population maps. The density of geo-located tweets in 1x1 km grid cells over a 2-month period across Indonesia, a country with one of the highest Twitter usage rates in the world, was input as a covariate into a previously published random forests-based census disaggregation method. Comparison of internal measures of accuracy and external assessments between models built with and without the geotweets showed that increases in population mapping accuracy could be obtained using the geotweet densities as a covariate layer. The work highlights the potential for such social media-derived data in improving our understanding of population distributions and offers promise for more dynamic mapping with such data being continually produced and freely available. Numéro de notice : A2017-166 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12214 En ligne : http://dx.doi.org/10.1111/tgis.12214 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84700
in Transactions in GIS > vol 21 n° 2 (April 2017) . - pp 317 – 331[article]Evidence of postseismic deformation signal of the 2007 m8.5 Bengkulu earthquake and the 2012 m8.6 Indian ocean earthquake in southern Sumatra, Indonesia, based on GPS data / Satrio Muhammad Alif in Journal of applied geodesy, vol 10 n° 2 (June 2016)
[article]
Titre : Evidence of postseismic deformation signal of the 2007 m8.5 Bengkulu earthquake and the 2012 m8.6 Indian ocean earthquake in southern Sumatra, Indonesia, based on GPS data Type de document : Article/Communication Auteurs : Satrio Muhammad Alif, Auteur ; Irwan Meilano, Auteur ; Endra Gunawan, Auteur ; Joni Efendi, Auteur Année de publication : 2016 Article en page(s) : pp 103 - 108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse diachronique
[Termes IGN] coordonnées GPS
[Termes IGN] déformation de la croute terrestre
[Termes IGN] faille géologique
[Termes IGN] Sumatra
[Termes IGN] vitesseRésumé : (auteur) GPS data in southern Sumatra, Indonesia, indicate crustal deformation associated to subduction zone and inland fault of Great Sumatran Fault (GSF). We analyze these deformation characteristics using campaign and continuous GPS data available in southern Sumatra from 2006–2014. After removing the effect of GSF in southern Sumatra and coseismic displacements of 2007 Bengkulu and 2012 Indian Ocean earthquake, we find that GPS sites experienced northwest-ward direction. These GPS velocities correspond to postseismic deformation of the 2007 Bengkulu earthquake and the 2012 Indian Ocean earthquake. We analyze strain using these velocities, and we find that postseismic strains in southern Sumatra are in the range of 0.8–20 nanostrain. Numéro de notice : A2016-558 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2015-0019 En ligne : http://dx.doi.org/10.1515/jag-2015-0019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81737
in Journal of applied geodesy > vol 10 n° 2 (June 2016) . - pp 103 - 108[article]A review of forest and tree plantation biomass equations in Indonesia / Kamalakumari Anitha in Annals of Forest Science, vol 72 n° 8 (December 2015)
[article]
Titre : A review of forest and tree plantation biomass equations in Indonesia Type de document : Article/Communication Auteurs : Kamalakumari Anitha, Auteur ; Louis V. Verchot, Auteur ; Shijo Joseph, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 981 - 997 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] allométrie
[Termes IGN] biomasse forestière
[Termes IGN] distribution spatiale
[Termes IGN] équation
[Termes IGN] Indonésie
[Termes IGN] troncRésumé : (auteur) Key message: We compiled 2,458 biomass equations from 168 destructive sampling studies in Indonesia. Unpublished academic theses contributed the largest share of the biomass equations. The availability of the biomass equations was skewed to certain regions, forest types, and species. Further research is necessary to fill the data gaps in emission factors and to enhance the implementation of climate change mitigation projects and programs.
Context: Locally derived allometric equations contribute to reducing the uncertainty in the estimation of biomass, which may be useful in the implementation of climate change mitigation projects and programs in the forestry sector. Many regional and global efforts are underway to compile allometric equations.
Aims: The present study compiles the available allometric equations in Indonesia and evaluates their adequacy in estimating biomass in the different types of forest across the archipelago.
Methods: A systematic survey of the scientific literature was conducted to compile the biomass equations, including ISI publications, national journals, conference proceedings, scientific reports, and academic theses. The data collected were overlaid on a land use/land cover map to assess the spatial distribution with respect to different regions and land cover types. The validation of the equations for selected forest types was carried out using independent destructive sampling data.
Results: A total of 2,458 biomass equations from 168 destructive sampling studies were compiled. Unpublished academic theses contributed the majority of the biomass equations. Twenty-one habitat types and 65 species were studied in detail. Diameter was the most widely used single predictor in all allometric equations. The cumulative number of individual trees cut was 5,207. The islands of Java, Kalimantan, and Sumatra were the most studied, while other regions were underexplored or unexplored. More than half of the biomass equations were for just seven species. The majority of the studies were carried out in plantation forests and secondary forests, while primary forests remain largely understudied. Validation using independent data showed that the allometric models for peat swamp forest had lower error departure, while the models for lowland dipterocarp forest had higher error departure.
Conclusion: Although biomass studies are a major research activity in Indonesia due to its high forest cover, the majority of such activities are limited to certain regions, forest types, and species. More research is required to cover underrepresented regions, forest types, particular growth forms, and very large tree diameter classes.Numéro de notice : A2015-895 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-015-0507-4 Date de publication en ligne : 12/10/2015 En ligne : https://doi.org/10.1007/s13595-015-0507-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79448
in Annals of Forest Science > vol 72 n° 8 (December 2015) . - pp 981 - 997[article]Geospatial analysis of urban landscape patterns in three major cities of Southeast Asia / Ronald C. Estoque in Tsukuba geoenvironmental sciences, vol 10 (december 2014)PermalinkPermalinkSeeking the truth in Aceh / Anonyme in GEO: Geoconnexion international, vol 11 n° 7 (july - august 2012)PermalinkThe potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)PermalinkLong-term consecutive DInSAR for volume change estimation of land deformation / S. Sumantyo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkPermalinkElaboration d'une carte dynamique des dégâts causés par les lahars au Merapi (Java centre, Indonésie) dans le cadre du programme MIA VITA / A.K. Robin (2011)PermalinkUpper mantle rheology from GRACE and GPS postseismic deformation after the 2004 Sumatra‐Andaman earthquake / Isabelle Panet in Geochemistry, Geophysics, Geosystems, vol 11 n° 6 (June 2010)PermalinkParticipatory mapping: why maps and GIS matter / T. Aditya in GIM international, vol 22 n° 9 (September 2008)PermalinkUplift and subsidence due to the 26 December 2004 Indonesian earthquake detected by SAR data / Marco Chini in International Journal of Remote Sensing IJRS, vol 29 n°13-14 (July 2008)Permalink