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Applying multi-temporal Landsat satellite data and Markov-cellular automata to predict forest cover change and forest degradation of sundarban reserve forest, Bangladesh / Mohammad Emran Hasan in Forests, vol 11 n° 9 (September 2020)  

Public [article]  inForests > vol 11 n° 9 (September 2020) . - N° 1016 Titre : Applying multi-temporal Landsat satellite data and Markov-cellular automata to predict forest cover change and forest degradation of sundarban reserve forest, Bangladesh Type de document : Article/Communication Auteurs : Mohammad Emran Hasan, Auteur ; Biswajit Nath, Auteur ; A.H.M. Raihan Sarker, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : N° 1016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] automate cellulaire [Termes descripteurs IGN] Bangladesh [Termes descripteurs IGN] classification par maximum de vraisemblance [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] dégradation de l'environnement [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] gestion forestière durable [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] mangrove [Termes descripteurs IGN] modèle de Markov [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] réserve forestière [Termes descripteurs IGN] réserve naturelle [Termes descripteurs IGN] santé des forêts [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] système d'information géographique Résumé : (auteur) Overdependence on and exploitation of forest resources have significantly transformed the natural reserve forest of Sundarban, which shares the largest mangrove territory in the world, into a great degradation status. By observing these, a most pressing concern is how much degradation occurred in the past, and what will be the scenarios in the future if they continue? To confirm the degradation status in the past decades and reveal the future trend, we took Sundarban Reserve Forest (SRF) as an example, and used satellite Earth observation historical Landsat imagery between 1989 and 2019 as existing data and primary data. Moreover, a geographic information system model was considered to estimate land cover (LC) change and spatial health quality of the SRF from 1989 to 2029 based on the large and small tree categories. The maximum likelihood classifier (MLC) technique was employed to classify the historical images with five different LC types, which were further considered for future projection (2029) including trends based on 2019 simulation results from 1989 and 2019 LC maps using the Markov-cellular automata model. The overall accuracy achieved was 82.30%~90.49% with a kappa value of 0.75~0.87. The historical result showed forest degradation in the past (1989–2019) of 4773.02 ha yr−1, considered as great forest degradation (GFD) and showed a declining status when moving with the projection (2019–2029) of 1508.53 ha yr−1 and overall there was a decline of 3956.90 ha yr−1 in the 1989–2029 time period. Moreover, the study also observed that dense forest was gradually degraded (good to bad) but, conversely, light forest was enhanced, which will continue in the future even to 2029 if no effective management is carried out. Therefore, by observing the GFD, through spatial forest health quality and forest degradation mapping and assessment, the study suggests a few policies that require the immediate attention of forest policy-makers to implement them immediately and ensure sustainable development in the SRF. Numéro de notice : A2020-752 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f11091016 date de publication en ligne : 21/09/2020 En ligne : https://doi.org/10.3390/f11091016 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96432 [article]

A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 4 (April 2020) . - pp 2471 - 2480 Titre : A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions Type de document : Article/Communication Auteurs : Shahryar K. Ahmad, Auteur ; Faisal Hossain, Auteur ; Hisham Eldardiry, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2471 - 2480 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Bangladesh [Termes descripteurs IGN] climat tropical [Termes descripteurs IGN] eau de surface [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image PlanetScope [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] plan d'eau [Termes descripteurs IGN] radar à antenne synthétique [Termes descripteurs IGN] reconnaissance de surface [Termes descripteurs IGN] surveillance hydrologique [Termes descripteurs IGN] télédétection spatiale [Termes descripteurs IGN] zone humide Résumé : (auteur) Consistent estimation of water surface area from remote sensing remains challenging in regions such as South Asia with vegetation, mountainous topography, and persistent monsoonal cloud cover. High-resolution optical imagery, which is often used for global inundation mapping, is highly impacted by clouds, while synthetic aperture radar (SAR) imagery is not impacted by clouds and is affected by both topographic layover and vegetation. Here, we compare and contrast inundation extent measurements from visible (Landsat-8 and Sentinel-2) and SAR (Sentinel-1) imagery. Each data type (wavelength) has complementary strengths and weaknesses which were gauged separately over selected water bodies in Bangladesh. High-resolution cloud-free PlanetScope imagery at 3-m resolution was used as a reference to check the accuracy of each technique and data type. Next, the optical and radar images were fused for a rule-based water area classification algorithm to derive the optimal decision for the water mask. Results indicate that the fusion approach can improve the overall accuracy by up to 3.8%, 18.2%, and 8.3% during the wet season over using the individual products of Landsat8, Sentinel-1, and Sentinel-2, respectively, at three sites, while providing increased observational frequency. The fusion-derived products resulted in overall accuracy ranging from 85.8% to 98.7% and Kappa coefficient varying from 0.61 to 0.83. The proposed SAR-visible fusion technique has potential for improving satellite-based surface water monitoring and storage changes, especially for smaller water bodies in humid tropical climate of South Asia. Numéro de notice : A2020-198 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2950705 date de publication en ligne : 19/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2950705 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94868 [article]

Retrieval of tropical forest biomass information from ALOS PALSAR data / Mahmudur Rahman in Geocarto international, vol 28 n° 5-6 (August - October 2013)  

Public [article]  inGeocarto international > vol 28 n° 5-6 (August - October 2013) . - pp 382 - 403 Titre : Retrieval of tropical forest biomass information from ALOS PALSAR data Type de document : Article/Communication Auteurs : Mahmudur Rahman, Auteur ; Josaphat Tetuko Sri Sumantyo, Auteur Année de publication : 2013 Article en page(s) : pp 382 - 403 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bande L [Termes descripteurs IGN] Bangladesh [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] régression [Termes descripteurs IGN] rétrodiffusion Résumé : (Auteur) Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r 2) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polarimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions. Numéro de notice : A2013-547 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.710652 date de publication en ligne : 04/09/2012 En ligne : https://doi.org/10.1080/10106049.2012.710652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32683 [article]

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Observations of urban and suburban environments with global satellite scatterometer data / Son V. Nghiem in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 367 - 380 Titre : Observations of urban and suburban environments with global satellite scatterometer data Type de document : Article/Communication Auteurs : Son V. Nghiem, Auteur ; D. Balk, Auteur Année de publication : 2009 Article en page(s) : pp 367 - 380 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] banlieue [Termes descripteurs IGN] BOGOTA [Termes descripteurs IGN] Canton (Kouangtoung) [Termes descripteurs IGN] Dallas (Texas) [Termes descripteurs IGN] densité de population [Termes descripteurs IGN] densité du bâti [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] Dhaka (Bangladesh) [Termes descripteurs IGN] diffusomètre [Termes descripteurs IGN] échantillonnage d'image [Termes descripteurs IGN] éclairage public [Termes descripteurs IGN] image Landsat-ETM+ [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] Phoenix [Termes descripteurs IGN] QUITO [Termes descripteurs IGN] télédétection en hyperfréquence Résumé : (Auteur) A global and consistent characterization of land use and land change in urban and suburban environments is crucial for many fundamental social and natural science studies and applications. Presented here is a dense sampling method (DSM) that uses satellite scatterometer data to delineate urban and intraurban areas at a posting scale of about 1 km. DSM results are analyzed together with information on population and housing censuses, with Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, and with Defense Meteorological Satellite Program (DMSP) night-light data. The analyses include Dallas-Fort Worth and Phoenix in the United States, Bogotá in Colombia, Dhaka in Bangladesh, Guangzhou in China, and Quito in Ecuador. Results show that scatterometer signatures correspond to buildings and infrastructures in urban and suburban environments. City extents detected by scatterometer data are significantly smaller than city light extents, but not all urban areas are detectable by the current SeaWinds scatterometer on the QuikSCAT satellite. Core commercial and industrial areas with high buildings and large factories are identified as high-backscatter centers. Data from DSM backscatter and DMSP nighttime lights have a good correlation with population density. However, the correlation relations from the two satellite datasets are different for different cities indicating that they contain complementary information. Together with night-light and census data, DSM and satellite scatterometer data provide new observations to study global urban and suburban environments and their changes. Furthermore, the capability of DSM to identify hydrological channels on the Greenland ice sheet and ecological biomes in central Africa demonstrates that DSM can be used to observe persistent structures in natural environments at a km scale, providing contemporaneous data to study human impacts beyond urban and suburban areas. Copyright ISPRS Numéro de notice : A2009-295 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29925 [article]

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Use of TRMM in determining the climatic characteristics of rainfall over Bangladesh / M.N. Islam in Remote sensing of environment, vol 108 n° 3 (15/06/2007)

Public [article]  inRemote sensing of environment > vol 108 n° 3 (15/06/2007) . - pp 264 - 276 Titre : Use of TRMM in determining the climatic characteristics of rainfall over Bangladesh Type de document : Article/Communication Auteurs : M.N. Islam, Auteur ; H. Uyeda, Auteur Année de publication : 2007 Article en page(s) : pp 264 - 276 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] Bangladesh [Termes descripteurs IGN] climatologie [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] estimation statistique [Termes descripteurs IGN] image radar [Termes descripteurs IGN] image TRMM-MI [Termes descripteurs IGN] précipitation Résumé : (Auteur) Five years of data from 1998 to 2002 of TRMM-3B42 version 5 (V5), 3B43 V5, 3B42 version 6 (V6), 3B43 V6, and the Bangladesh Meteorological Department rain-gauge network were analyzed to understand the climatic characteristics of rainfall over Bangladesh. TRMM-PR 2A25 data were used to obtain the precipitation field of the convection events. Daily rainfall measured by TRMM V5 3B42 was compared to that of rain-gauge values from pre-monsoon to post-monsoon months (March–November). The time sequence patterns of the daily rainfall determined by the V5 3B42 and those from rain gauges were remarkably similar. The spatial and temporal averages of rainfall revealed good estimations of rainfall: during March to November, the V5 3B42- and rain gauge-estimated daily rainfall was 8.12 and 8.34 mm, respectively. In annual scale, TRMM V5 3B42-, V5 3B43-, V6 3B42-, V6 3B43- and rain-gauge estimated rainfall was 6.9, 6.4, 6.6, 6.8 and 7.1 mm/day, respectively. The average percentage of rainy days determined by V5 3B42 data with respect to the rain-gauge value was 96%. TRMM is useful for estimating the average values of rainfall in Bangladesh. The prominent difference between rainfall estimated by rain-gauge and V5 3B42 was found to be period- and location-dependent. The V5 3B42 overestimated the rainfall during the pre-monsoon period and in dry regions but underestimated it during the monsoon period and in wet regions. The reason for the differences according to season and locations is considered to be the vertical cross section of convection obtained by TRMM-PR 2A25 data. The rainfall overestimation in pre-monsoon and underestimation in monsoon period measured by V5 3B42 is reduced to reasonable amount by V6 3B42 and V6 3B43. In this manner, the merit of using TRMM data for climatological studies of rainfall over Bangladesh is shown. Copyright Elsevier Numéro de notice : A2007-298 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28661 [article]

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The derivation of a sub-canopy digital terrain model of a flooded forest using synthetic aperture radar / M.L. Imhoff in Photogrammetric Engineering & Remote Sensing, PERS, vol 56 n° 8 (august 1990)

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Study of river flood hydrology in Bangladesh with AVHRR data / A. Ali in International Journal of Remote Sensing IJRS, vol 10 n° 12 (December 1989)

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Floods in Bangladesh, a preliminary study with Spot 1 data / François Blasco (1989)

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Agricultural, hydrologic and oceanographic studies in Bangladesh with NOAA AVHRR data / A. Ali in International Journal of Remote Sensing IJRS, vol 8 n° 6 (June 1987)

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Monsoon flood boundary delineation and damage assessment using space borne imaging radar and Landsat data / M.L. Imhoff in Photogrammetric Engineering & Remote Sensing, PERS, vol 53 n° 4 (april 1987)

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Regional seminar on the application of remote sensing techniques to coastal zone management and environmental monitoring, Dhaka, Bangladesh, 18-26 november 1986 / M.A.H. Pramanik in International Journal of Remote Sensing IJRS, vol 8 n° 4 (April 1987)

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Report of the workshop on high resolution satellite data, Jakarta, Indonesia, 19 - 21 October 1987 / Programme des Nations unies pour le développement PNUD UNDP/ESCAP (1987)

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Étude de l'aridité au nord-ouest du Bangladesh (Barind Tract) par télédétection / S. Ahmed (1985)

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Télédétection et végétation tropicale / F. Lavenu (1984)

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