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Mapping active paddy rice area over monsoon asia using time-series Sentinel-2 images in Google earth engine : a case study over lower gangetic plain / Arabinda Maiti in Geocarto international, vol 38 n° inconnu ([01/01/2023])
[article]
Titre : Mapping active paddy rice area over monsoon asia using time-series Sentinel-2 images in Google earth engine : a case study over lower gangetic plain Type de document : Article/Communication Auteurs : Arabinda Maiti, Auteur ; Prasenjit Acharya, Auteur ; Srikanta Sannigrahi, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] Gange (fleuve)
[Termes IGN] Google Earth Engine
[Termes IGN] image Sentinel-SAR
[Termes IGN] Inde
[Termes IGN] mousson
[Termes IGN] plaine
[Termes IGN] rizièreRésumé : (auteur) We proposed a modification of the existing approach for mapping active paddy rice fields in monsoon-dominated areas. In the existing PPPM approach, LSWI higher than EVI at the transplantation stage enables the identification of rice fields. However, it fails to recognize the fields submerged later due to monsoon floods. In the proposed approach (IPPPM), the submerged fields, at the maximum greenness time, were excluded for better estimation. Sentinel–2A/2B time-series images were used for the year 2018 to map paddy rice over the Lower Gangetic Plain (LGP) using Google earth engine (GEE). The overall accuracy (OA) obtained from IPPPM was 85%. Further comparison with the statistical data reveals the IPPPM underestimates (slope (β1) = 0.77) the total reported paddy rice area, though R2 remains close to 0.9. The findings provide a basis for near real-time mapping of active paddy rice areas for addressing the issues of production and food security. Numéro de notice : A2022-924 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2022.2032396 En ligne : https://doi.org/10.1080/10106049.2022.2032396 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99963
in Geocarto international > vol 38 n° inconnu [01/01/2023][article]A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing / Yali Zhang in GIScience and remote sensing, vol 60 n° 1 (2023)
[article]
Titre : A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing Type de document : Article/Communication Auteurs : Yali Zhang, Auteur ; Ni Wang, Auteur ; Yuliang Wang, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 2163574 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] données multisources
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-MSI
[Termes IGN] phénologie
[Termes IGN] puits de carbone
[Termes IGN] santé des forêtsRésumé : (auteur) Spatially explicit information on the distribution of dominant tree species groups and aboveground biomass (AGB) in forested areas is essential for developing targeted forest management and biodiversity conservation measures, as well as assessing forest carbon sequestration capacity. There is a shortage of continuously updated 30-m spatial resolution products for mapping dominant tree species groups. The vast majority of remote sensing-based AGB estimation approaches have relatively low accuracy for dominant tree species groups or forest types and are unsuitable for AGB modeling. Therefore, this study aims to develop an integrated framework that considers the phenological characteristics of different tree species to improve the mapping accuracies of forest dominant tree groups and corresponding AGB estimates. Thirty-meter resolution maps of dominant tree species groups were created using machine learning algorithms and phenological parameters. Features extracted from optical and radar images and phenological characteristics were used to construct AGB estimation models in a temporally consistent manner to improve the AGB estimation accuracy and perform dynamic AGB monitoring. The proposed method accurately characterized the dynamic distribution of the dominant tree species groups in the study area. The traditional AGB model that does not consider different forest types or species had an R2 value of 0.52, whereas the proposed model that considers phenology and forest types had an R2 value of 0.67. This result indicates that incorporating information on phenology and dominant species improves the accuracy of AGB estimations. The AGB in most regions was 30–55 t/ha, showing that the majority of the forests were young or middle-aged stands, and the areal percentage of AGB greater than 30 t/ha increased during the study period, suggesting an improvement in forest quality. Furthermore, the oak AGB was the highest, indicating that oak afforestation should be encouraged to enhance the carbon sequestration capacity of future forest ecosystems. The results provide new insights for researchers and managers to understand the trends of forest development and forest health, as well as technical information and a database for formulating more rational forest management strategies. Numéro de notice : A2023-121 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/15481603.2022.2163574 Date de publication en ligne : 03/01/2023 En ligne : https://doi.org/10.1080/15481603.2022.2163574 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102496
in GIScience and remote sensing > vol 60 n° 1 (2023) . - n° 2163574[article]Production of orthophoto map using mobile photogrammetry and comparative assessment of cost and accuracy with satellite imagery for corridor mapping: a case study in Manesar, Haryana, India / Manuj Dev in Annals of GIS, vol 29 n° 1 (January 2023)
[article]
Titre : Production of orthophoto map using mobile photogrammetry and comparative assessment of cost and accuracy with satellite imagery for corridor mapping: a case study in Manesar, Haryana, India Type de document : Article/Communication Auteurs : Manuj Dev, Auteur ; Shetru M. Veerabhadrappa, Auteur ; Ashutosh Kainthola, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 163 - 176 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage
[Termes IGN] aérotriangulation
[Termes IGN] analyse comparative
[Termes IGN] image panoramique
[Termes IGN] image satellite
[Termes IGN] modèle stéréoscopique
[Termes IGN] orthoimage
[Termes IGN] orthophotocarte
[Termes IGN] point d'appui
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] système de numérisation mobileRésumé : (auteur) The study aims to find a low-cost alternate technology to get imagery, using mobile platform, and produce digital orthophoto for corridor mapping, with a higher degree of accuracy and which can reduce the lag time of acquisition of data. The present study uses digital single-lens reflex cameras, mounted on a mobile vehicle, and acquisition of data in the video format rather than still photographs, as traditionally used in mobile mapping systems. The videos are used to create a set of images and orthophotos. A widespread ground control points were recorded in the study area, using the global navigation satellite system receiver, which measured the control points in real-time kinematic mode. Generation of digital orthophoto has been completed using the captured mobile imagery and ground control point. Furthermore, procurement of satellite imagery and aerial triangulation using ground control points have been done. While comparing the planimetric accuracy of orthophoto against satellite imagery using the ground control points, the achieved root mean square error value of produced orthophoto is 0.171 m in X axis and 0.205 m in Y axis. However, for Cartosat -1 satellite imagery, the RMSE value for X is 1.22 m and for Y is 1.98 m. This research proposes the alternate low-cost mobile mapping method to capture the imagery for orthophoto production. The cost of orthophoto production from mobile image was found 77% cheaper than the orthophoto cost from fresh/latest satellite imagery procurement, while the overall production was 70% cost-effective than the orthophoto maps made from archived imagery. Numéro de notice : A2023-161 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/19475683.2022.2141853 Date de publication en ligne : 12/11/2022 En ligne : https://doi.org/10.1080/19475683.2022.2141853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102864
in Annals of GIS > vol 29 n° 1 (January 2023) . - pp 163 - 176[article]Remote sensing techniques for water management and climate change monitoring in drought areas: case studies in Egypt and Tunisia / Lifan Ji in European journal of remote sensing, vol 56 n° 1 (2023)
[article]
Titre : Remote sensing techniques for water management and climate change monitoring in drought areas: case studies in Egypt and Tunisia Type de document : Article/Communication Auteurs : Lifan Ji, Auteur ; Yihao Shao, Auteur ; Jianjun Liu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] changement climatique
[Termes IGN] Egypte
[Termes IGN] gestion de l'eau
[Termes IGN] humidité du sol
[Termes IGN] image optique
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] stress hydrique
[Termes IGN] Tunisie
[Termes IGN] zone semi-arideRésumé : (auteur) This study focused on monitoring the water status of vegetation and soil by exploiting the synergy of optical and microwave satellite data with the aim of improving the knowledge of water cycle in cultivated lands in Egyptian Delta and Tunisian areas. Environmental analysis approaches based on optical and synthetic aperture radar data were carried out to set up the basis for future implementation of practical and cost-effective methods for sustainable water use in agriculture. Long-term behaviors of vegetation indices were thus analyzed between 2000 and 2018. By using SAR data from Sentinel-1, an Artificial Neural Network-based algorithm was implemented for estimating soil moisture and monthly maps for 2018 have been generated to be compared with information derived from optical indices. Moreover, a novel drought severity index was developed and applied to available data. The index was obtained by combining vegetation soil difference index, derived from optical data, and soil moisture content derived from SAR data. The proposed index was found capable of complementing optical and microwave sensitivity to drought-related parameters, although ground data are missing for correctly validating the results, by capturing drought patterns and their temporal evolution better than indices based only on microwave or optical data. Numéro de notice : A2023-103 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2022.2157335 Date de publication en ligne : 06/01/2023 En ligne : https://doi.org/10.1080/22797254.2022.2157335 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102430
in European journal of remote sensing > vol 56 n° 1 (2023) . - pp 1 - 16[article]Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia / Dawit Kanito in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)
[article]
Titre : Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia Type de document : Article/Communication Auteurs : Dawit Kanito, Auteur ; Dawit Bedadi, Auteur ; Samuel Feyissa, Auteur Année de publication : 2023 Article en page(s) : n° 2167614 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse de sensibilité
[Termes IGN] bassin hydrographique
[Termes IGN] Ethiopie
[Termes IGN] image Landsat
[Termes IGN] modèle RUSLE
[Termes IGN] précipitation
[Termes IGN] sédiment
[Termes IGN] système d'information géographiqueRésumé : (auteur) Soil erosion and sediment yields are the current limitations and future threats to agriculture, water resources and hydropower projects particularly in developing countries. Estimating the extent and comprehending the spatial distribution of hotspot area is crucial to implement evidence-based soil and water conservation (SWC) measures with limited resources. The study used RUSLE and SDR models in ArcGIS 10.8 environment. The RUSLE model was found to be highly sensitive to C factor followed by LS factor. The result indicated that the annual soil loss varies from 0 to 359.99 t ha−1 yr−1 with 22.31 t ha−1 yr−1 as a mean annual. Besides, the estimated sediment yield ranged from 0 to 42.5 t ha−1 yr−1 with a mean value of 12.02 t ha−1 yr−1. The finding revealed that the central west (SW_5) and northeast (SW_4) parts of the watershed yield higher sediment. The result also signified that about 52.9% of the eroded materials including soil and nutrients are transferred to the outlet. The outcome of our finding undoubtedly aids in the identification of hotspot areas for the adoption of appropriate SWC measures. Hence, adopting RUSLE and SDR for Gununo watershed and another watershed having similar biophysical and environmental factors is suggested. Numéro de notice : A2023-155 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2023.2167614 Date de publication en ligne : 26/01/2023 En ligne : https://doi.org/10.1080/19475705.2023.2167614 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102841
in Geomatics, Natural Hazards and Risk > vol 14 n° 1 (2023) . - n° 2167614[article]A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band / Xinjie Liu in Remote sensing of environment, vol 284 (January 2023)PermalinkSimplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)PermalinkSolid waste mapping based on very high resolution remote sensing imagery and a novel deep learning approach / Bowen Niu in Geocarto international, vol 38 n° 1 ([01/01/2023])PermalinkThe cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)PermalinkUsing Google Earth Engine to classify unique forest and agroforest classes using a mix of Sentinel 2a spectral data and topographical features: a Sri Lanka case study / W.D.K.V. Nandasena in Geocarto international, vol 38 n° inconnu ([01/01/2023])PermalinkAutomatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery / Yuxin Wang in Science of the total environment, vol 853 (December 2022)PermalinkConsistency assessment of multi-date PlanetScope imagery for seagrass percent cover mapping in different seagrass meadows / Pramaditya Wicaksono in Geocarto international, vol 37 n° 27 ([20/12/2022])PermalinkBathymetry and benthic habitat mapping in shallow waters from Sentinel-2A imagery: A case study in Xisha islands, China / Wei Huang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 12 (December 2022)PermalinkDeep learning detects invasive plant species across complex landscapes using Worldview-2 and Planetscope satellite imagery / Thomas A. Lake in Remote sensing in ecology and conservation, vol 8 n° 6 (December 2022)PermalinkA deep learning framework based on generative adversarial networks and vision transformer for complex wetland classification using limited training samples / Ali Jamali in International journal of applied Earth observation and geoinformation, vol 115 (December 2022)Permalink