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Volunteered geographic information mobile application for participatory landslide inventory mapping / Raden Muhammad Anshori in Computers & geosciences, vol 161 (April 2022)  

Public [article]  inComputers & geosciences > vol 161 (April 2022) . - n° 105073 Titre : Volunteered geographic information mobile application for participatory landslide inventory mapping Type de document : Article/Communication Auteurs : Raden Muhammad Anshori, Auteur ; Guruh Samodra, Auteur ; Djati Mardiatno, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105073 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] approche participative [Termes IGN] base de données [Termes IGN] cartographie thématique [Termes IGN] données localisées des bénévoles [Termes IGN] effondrement de terrain [Termes IGN] géopositionnement [Termes IGN] inventaire [Termes IGN] Java (île de) [Termes IGN] téléphonie mobile Résumé : (auteur) Participatory landslide inventory mapping using the Volunteered Geographic Information (VGI) mobile app is a promising method to produce a landslide inventory map. The aim of this research is to describe the development and implementation of the VGI mobile app for participatory landslide inventory mapping. The architecture VGI mobile app is developed on the basis of Free Open-source Software for Geospatial Application server-client software to ensure reproducibility and flexibility, and to reduce cost. Anyone can reproduce, modify, and share the code, which suggests improvement in the collective ability to use, prepare, and landslide inventory update. Landslide inventory using VGI mobile app shows that the tool and method successfully map landslides in the landslide prone area (Magelang Regency, Central Java Province, Indonesia) with fairly high levels of effectiveness and convenience. Magelang Regency, one of the landslide prone areas in Java, is located in the intermountain basin surrounded by Menoreh Mountain, Merapi, Merbabu, Suropati-Telomoyo Complex, and Sumbing Volcano. In this study, landslide inventory mapping using VGI mobile app was applied in Magelang Regency by 17 volunteers from BPBD (Regional Agency for Disaster Management) Magelang Regency for three days. Landslides area occurred from 2017 to 2019 were properly identified and mapped by the volunteers. The sizes of landslides varied from 5.2 m2 to 4,632.5 m2, and the average was 208.2 m2. A team of volunteer was able to map 7-10 landslides per day. Participatory mapping using VGI mobile app reduces the time in transferring field data to a GIS database, in contrast to conventional participatory landslide inventory mapping. VGI mobile app allows users to provide new geographical landslide data, share landslide data rapidly, ensure consistency of landslide data, and improve accessibility of landslide data. The use of the VGI mobile app for participatory landslide inventory mapping provides new opportunities to improve risk assessment, preparedness, and early action and warning to landslide hazard. Numéro de notice : A2022-189 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.cageo.2022.105073 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105073 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99918 [article]

Co-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements / Mokhamad Nur Cahyadi in Remote sensing, vol 14 n° 2 (January-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 2 (January-2 2022) . - n° 401 Titre : Co-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements Type de document : Article/Communication Auteurs : Mokhamad Nur Cahyadi, Auteur ; Buldan Muslim, Auteur ; Danar Guruh Pratomo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 401 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] diffusion de Rayleigh [Termes IGN] données GLONASS [Termes IGN] données GNSS [Termes IGN] Indonésie [Termes IGN] onde acoustique [Termes IGN] perturbation ionosphérique [Termes IGN] propagation ionosphérique [Termes IGN] séisme [Termes IGN] Sumatra [Termes IGN] teneur totale en électrons [Termes IGN] tsunami Résumé : (auteur) The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with amplitude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly amplitude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s−1 for the 2016 West Sumatra earthquake and ~0.97–1.08 km s−1 for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction. Numéro de notice : A2022-103 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs14020401 Date de publication en ligne : 16/01/2022 En ligne : https://doi.org/10.3390/rs14020401 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99571 [article]

Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [15/01/2022] . - pp 366 - 376 Titre : Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation Type de document : Article/Communication Auteurs : Narissara Nuthammachot, Auteur ; Askar Askar, Auteur ; Dimitris Stratoulias, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 366 - 376 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] biomasse aérienne [Termes IGN] corrélation [Termes IGN] échantillonnage de données [Termes IGN] forêt privée [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] Indonésie [Termes IGN] précision de l'estimation Résumé : (auteur) Above-ground Biomass (AGB) represents the largest amount of biomass found on earth. Passive and active remote sensors have been a useful tool in estimating AGB for this purpose; nevertheless, both data sources suffer from saturation problems in dense vegetation. A combination of optical and radar data could potentially increase the accuracy of AGB estimation. In this study we evaluate the synergistic use of Sentinel-1 and Sentinel-2 for assessing AGB in a private forest in Yogyakarta, Indonesia. Forty five sample plots of 20 m x 20 m were used as ground truth data. AGB correlated with Sentinel-1 backscatter and Sentinel-2 derived variables with R2 = 0.34 and R2 = 0.82, respectively; nevertheless, the synergistic use of Sentinel-1 and Sentinel-2 yielded the highest accuracy (i.e., R2 = 0.84). The results indicate that AGB in Yogyakarta is most accurately estimated based on the synergy of optical and radar satellite images. Numéro de notice : A2022-049 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1726507 Date de publication en ligne : 13/02/2020 En ligne : https://doi.org/10.1080/10106049.2020.1726507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99440 [article]

Artificial intelligence methods applied to urban remote sensing and GIS / Chang-Wook Lee (2021)  

Public Titre : Artificial intelligence methods applied to urban remote sensing and GIS Type de document : Monographie Auteurs : Chang-Wook Lee, Éditeur scientifique ; Hyangsun Han, Éditeur scientifique ; Hoonyol Lee, Éditeur scientifique ; Yu-Chul Park, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 166 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-1603-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] carte thématique [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] Corée du sud [Termes IGN] effondrement de terrain [Termes IGN] espace vert [Termes IGN] image à très haute résolution [Termes IGN] image radar moirée [Termes IGN] indice de végétation [Termes IGN] intelligence artificielle [Termes IGN] Jakarta (Indonésie) [Termes IGN] méthode de Monte-Carlo [Termes IGN] Mexique [Termes IGN] milieu urbain [Termes IGN] pollution des eaux [Termes IGN] réseau local sans fil [Termes IGN] segmentation sémantique [Termes IGN] séisme [Termes IGN] système d'information géographique Résumé : (éditeur) This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas. Note de contenu : 1- Improvement of earthquake risk awareness and seismic literacy of Korean citizens through earthquake vulnerability map from the 2017 Pohang earthquake, South Korea 2- Land subsidence susceptibility mapping in Jakarta using functional and meta-ensemble machine learning algorithm based on time-series InSAR data 3- Integration of InSAR time-series data and GIS to assess Llnd subsidence along subway lines in the Seoul metropolitan area, South Korea 4- Mapping urban green spaces at the metropolitan level using very high resolution satellite imagery and deep learning techniques for semantic segmentation 5- Susceptibility analysis of the Mt. Umyeon landslide area using a physical slope model and probabilistic method 6- Intelligent WSN system for water quality analysis using machine learning algorithms: A case study (Tahuando River from Ecuador) 7- Groundwater potential mapping using remote sensing and GIS-based machine learning techniques Numéro de notice : 28667 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1603-5 En ligne : https://doi.org/10.3390/books978-3-0365-1603-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99870

Impact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 1 (January 2021) . - pp 128 - 138 Titre : Impact of forest disturbance on InSAR surface displacement time series Type de document : Article/Communication Auteurs : Paula M. Bürgi, Auteur ; Rowena B. Lohman, Auteur Année de publication : 2021 Article en page(s) : pp 128 - 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] changement d'occupation du sol [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] détection du signal [Termes IGN] erreur de phase [Termes IGN] erreur systématique [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] retard ionosphèrique [Termes IGN] retard troposphérique [Termes IGN] série temporelle [Termes IGN] Sumatra [Termes IGN] surveillance géologique Résumé : (auteur) As interferometric synthetic aperture radar (InSAR) data improve in their global coverage and temporal sampling, studies of ground deformation using InSAR are becoming feasible even in heavily vegetated regions such as the American Pacific Northwest (PNW) and Sumatra. However, ongoing forest disturbance due to logging, wildfires, or disease can introduce time-variable signals which could be misinterpreted as ground displacements. This study constrains the error introduced into InSAR time series in the presence of time-variable forest disturbance using synthetic data. For satellite platforms with randomly distributed orbital positions in time (e.g., Sentinel-1), mid-time series forest disturbance results in random error on the order of 0.2 and 10 cm/year for 1-year secular and time-variable velocities, respectively. If the orbital positions are not randomly distributed in time (e.g., ALOS-1), a biased error on the order of 10 cm/year is introduced to the inferred secular velocity. A time series using real ALOS-1 data near Eugene, OR, USA, shows agreement with the bias estimated by synthetic models. Mitigation of time-variable land cover change effects can be achieved if their timing is known, either through independent observations of surface properties (e.g., Landsat/Sentinel-2) or through the use of more computationally expensive, nonlinear inversions with additional terms for the timing of height changes. Inclusion of these additional terms reduces the potential for misinterpretation of InSAR signals associated with land surface change as ground deformation. Numéro de notice : A2021-032 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2992938 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2992938 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96727 [article]

Soil erosion / António Vieira (2021)  

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Combination of Landsat 8 OLI and Sentinel-1 SAR time-series data for mapping paddy fields in parts of West and Central Java provinces, Indonesia / Sanjiwana Arjasakusuma in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

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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])  

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What Is threatening forests in protected areas? A global assessment of deforestation in protected areas, 2001–2018 / Christopher M. Wade in Forests, vol 11 n° 5 (May 2020)  

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Combining radar and optical imagery to map oil palm plantations in Sumatra, Indonesia, using the Google Earth Engine / Thuan Sarzynski in Remote sensing, vol 12 n° 7 (April 2020)  

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Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series / Maylis Lopes in Methods in ecology and evolution, vol 11 n° 4 (April 2020)  

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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)  

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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)  

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Improving large area population mapping using geotweet densities / Nirav N. Patel in Transactions in GIS, vol 21 n° 2 (April 2017)  

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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)  

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