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Analyzing spatio-temporal pattern of the forest fire burnt area in Uttarakhand using Sentinel-2 data / Shailja Mamgain in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 533 - 539 Titre : Analyzing spatio-temporal pattern of the forest fire burnt area in Uttarakhand using Sentinel-2 data Type de document : Article/Communication Auteurs : Shailja Mamgain, Auteur ; Harish Chandra Karnatak, Auteur ; Arijit Roy, Auteur ; Prakash Chauhan, Auteur Année de publication : 2022 Article en page(s) : pp 533 - 539 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] image Sentinel-MSI [Termes IGN] incendie de forêt [Termes IGN] indice de végétation [Termes IGN] régression multiple [Termes IGN] Uttarakhand (Inde ; état) [Termes IGN] zone sinistrée Résumé : (auteur) Forest fire burnt area estimation using Normalized Burn Ratio at regional level helps in understanding the pattern of the frequency and severity of forest fires. In this study, burnt area is estimated for all the thirteen districts of Indian state Uttarakhand for last six years from 2016 to 2021 using Sentinel 2A and 2B datasets. The spatial and temporal pattern of the burnt area was analyzed by incorporating different parameters such as meteorological parameters like land surface temperature, rainfall; edaphic parameter like surface soil moisture and vegetation parameters like Normalized Difference Vegetation Index & Enhanced Vegetation Index. The estimated burnt area was statistically analyzed with respect to the parameters stated and the relationship among them was quantified. It was found that burnt area is positively correlated with the land surface temperature, while it showed negative correlation with the pre-fire precipitation, pre-fire NDVI & EVI and the surface soil moisture for 11 out of 13 districts. The district-wise forest fire burnt area assessment and analysis of its spatio-temporal pattern can be used in the preparedness and mitigation planning to prevent drastic ecological impacts of forest fires on the landscape. Numéro de notice : A2022-443 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.5194/isprs-annals-V-3-2022-533-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-533-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100778 [article]

Persistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images / Hari Shankar in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 11 (November 2021) . - pp 853 - 862 Titre : Persistent scatterer interferometry for Pettimudi (India) landslide monitoring using Sentinel-1A images Type de document : Article/Communication Auteurs : Hari Shankar, Auteur ; Arijit Roy, Auteur ; Prakash Chauhan, Auteur Année de publication : 2021 Article en page(s) : pp 853 - 862 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] déformation de la croute terrestre [Termes IGN] effondrement de terrain [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] Inde [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] précipitation [Termes IGN] risque naturel [Termes IGN] série temporelle [Termes IGN] surveillance géologique Résumé : (Auteur) The continuous monitoring of land surface movement over time is of paramount importance for assessing landslide triggering factors and mitigating landslide hazards. This research focuses on measuring horizontal and vertical surface displacement due to a devastating landslide event in the west-facing slope of the Rajamala Hills, induced by intense rainfall. The landslide occurred in Pettimudi, a tea-plantation village of the Idukki district in Kerala, India, on August 6–7, 2020. The persistent-scatterer synthetic aperture radar interferometry (PSInSAR ) technique, along with the Stanford Method for Persistent Scatterers (StaMPS), was applied to investigate the land surface movement over time. A stack of 20 Sentinel-1A single-look complex images (19 interferograms) acquired in descending passes was used for PSInSAR processing. The line-of-sight (LOS ) displacement in long time series, and hence the average LOS velocity, was measured at each measurement-point location. The mean LOS velocity was decomposed into horizontal east–west (EW ) and vertical up–down velocity components. The results show that the mean LOS, EW, and up–down velocities in the study area, respectively, range from –18.76 to +11.88, –10.95 to +6.93, and –15.05 to +9.53 mm/y, and the LOS displacement ranges from –19.60 to +19.59 mm. The displacement values clearly indicate the instability of the terrain. The time-series LOS displacement trends derived from the applied PSInSAR technique are very useful for providing valuable inputs for disaster management and the development of disaster early-warning systems for the benefit of local residents. Numéro de notice : A2021-897 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00020R3 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.14358/PERS.21-00020R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99275 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021111	SL	Revue	Centre de documentation	Revues en salle	Disponible

Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data / C.M. Bhatt in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 84 - 102 Titre : Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data Type de document : Article/Communication Auteurs : C.M. Bhatt, Auteur ; Amitesh Gupta, Auteur ; Arijit Roy, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 84 - 102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie des risques [Termes IGN] crue [Termes IGN] données spatiotemporelles [Termes IGN] Gange (fleuve) [Termes IGN] humidité du sol [Termes IGN] image Aqua-AMSR [Termes IGN] image Aqua-MODIS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] image Terra-MODIS [Termes IGN] Inde [Termes IGN] inondation [Termes IGN] précipitation Résumé : (auteur) During late September, 2019 Bihar was struggling with severe flooding problem, which otherwise is marked as a period of flood recession due to withdrawal of south-east monsoons. The present study assess the flood situation using Sentinel-1 SAR images and complements the understanding about the flood event using long term (2000-18) multi-temporal space based flood sensitive proxy indicators like precipitation (GPM), soil moisture (AMSR-2), vegetation condition (MODIS) together with ground based river gauge (CWC) data. The study reveals that in 2019 during the 39th week of the year (late September) the central and eastern parts of Bihar witnessed heavy precipitation (176 percent higher than average), leading to enhanced soil moisture build up (19 percent higher than average) and consequently triggering severe flooding. River Ganga was observed to be flowing above danger level for almost two weeks. Due to the prolonged submergence by floodwaters a significant drop was observed in the NDVI and EVI values of about 13.7 and 11.1 percent respectively from the normal. About 8.36 lakh ha area was observed to be inundated, impacting about 9.26 million population. Patna followed by Bhagalpur were the two worst affected districts with almost 30% and 36% of districts geographical area being flooded. Numéro de notice : A2021-107 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1861113 Date de publication en ligne : 24/12/2020 En ligne : https://doi.org/10.1080/19475705.2020.1861113 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96904 [article]