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Drought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) / Buruk Kitachew Wossenyeleh in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 21 n° 1 (January 2021) . - pp 39 - 51 Titre : Drought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) Type de document : Article/Communication Auteurs : Buruk Kitachew Wossenyeleh, Auteur ; Kaleb Asnake Worku, Auteur ; Boud Verbeiren, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 39 - 51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Belgique [Termes IGN] carte hydrographique [Termes IGN] données météorologiques [Termes IGN] eau souterraine [Termes IGN] hydrogéologie [Termes IGN] réserve naturelle [Termes IGN] sécheresse [Termes IGN] surveillance hydrologique [Termes IGN] zone humide Résumé : (auteur) Drought can be described as a temporary decrease in water availability over a significant period that affects both surface and groundwater resources. Droughts propagate through the hydrological cycle and may impact vulnerable ecosystems. This paper investigates drought propagation in the hydrological cycle, focusing on assessing its impact on a groundwater-fed wetland ecosystem. Meteorological drought indices were used to analyze meteorological drought severity. Moreover, a method for assessing groundwater drought and its propagation in the aquifer was developed and applied. Groundwater drought was analyzed using the variable threshold method. Furthermore, meteorological drought and groundwater drought on recharge were compared to investigate drought propagation in the hydrological cycle. This research is carried out in the Doode Bemde wetland in central Belgium. The results of this research show that droughts are attenuated in the groundwater system. The number and severity of drought events on groundwater discharge were smaller than for groundwater recharge. However, the onset of both drought events occurred at the same time, indicating a quick response of the groundwater system to hydrological stresses. In addition, drought propagation in the hydrological cycle indicated that not all meteorological droughts result in groundwater drought. Furthermore, this drought propagation effect was observed in the wetland. Numéro de notice : A2021-133 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/nhess-21-39-2021 date de publication en ligne : 08/01/2021 En ligne : https://doi.org/10.5194/nhess-21-39-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96994 [article]

Analyse de la déforestation dans la périphérie ouest de la réserve de biosphère du Dja au Cameroun, à partir d'une série multi-annuelle d'images Landsat / Eric Wilson Tegno Nguekam in Revue Française de Photogrammétrie et de Télédétection, n° 222 (novembre 2020)  

Public [article]  inRevue Française de Photogrammétrie et de Télédétection > n° 222 (novembre 2020) . - pp 29 - 39 Titre : Analyse de la déforestation dans la périphérie ouest de la réserve de biosphère du Dja au Cameroun, à partir d'une série multi-annuelle d'images Landsat Type de document : Article/Communication Auteurs : Eric Wilson Tegno Nguekam, Auteur ; Salomon C. Nguembe Fils, Auteur ; Joachim Etouna, Auteur ; Simon Njeudeng Tenku, Auteur Année de publication : 2020 Article en page(s) : pp 29 - 39 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Cameroun [Termes IGN] carte d'occupation du sol [Termes IGN] classification dirigée [Termes IGN] déboisement [Termes IGN] données spatiotemporelles [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-OLI [Termes IGN] réserve naturelle Résumé : (Auteur) Dans cet article, il est question d’évaluer la déforestation dans la périphérie Ouest de la réserve de Biosphère du Dja à travers les techniques de télédétection et de système d’information géographique. Pour cela, huit images Landsat de date différentes (2011 à 2018) ont été utilisées pour produire les cartes d’occupation du sol, à travers la méthode de classification supervisée et l’algorithme « maximum likelihood ». Les classes d’occupation de sol retenues pour cette classification sont : forêt dense, forêt dégradée, zone de culture, zone marécageuse, zone d’habitation, sol nu et eau. L’analyse des changements a été faite avec la technique de « change detection ». Les résultats de cette étude ont montré que la déforestation a été importante pendant la période d’étude (2011 – 2018). Les surfaces forestières se sont principalement transformées en zone de culture, marécage, forêt dégradée, sol nu. Le taux de déforestation observé est de 6,8% et dénote une importante baisse du couvert forestier dense. L’étude a montré des tendances de déforestation dans cette périphérie. Elle a permis d’observer que les zones tendancieuses sont concentrées principalement autour de certaines activités anthropiques présentes dans cette zone (la plantation agricole SUDCAM, le barrage de Mekin, les lieux habités). Numéro de notice : A2020-761 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2020.434 date de publication en ligne : 25/11/2020 En ligne : https://doi.org/10.52638/rfpt.2020.434 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96402 [article]

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 IGN] automate cellulaire [Termes IGN] Bangladesh [Termes IGN] classification par maximum de vraisemblance [Termes IGN] couvert forestier [Termes IGN] déboisement [Termes IGN] dégradation de l'environnement [Termes IGN] détection de changement [Termes IGN] gestion forestière durable [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] mangrove [Termes IGN] modèle de Markov [Termes IGN] modèle de simulation [Termes IGN] occupation du sol [Termes IGN] réserve forestière [Termes IGN] réserve naturelle [Termes IGN] santé des forêts [Termes IGN] série temporelle [Termes 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]

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102085 Titre : Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches Type de document : Article/Communication Auteurs : S.M. Hamylton, Auteur ; R.H. Morris, Auteur ; R.C. Carvalho, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] carte de la végétation [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification pixellaire [Termes IGN] détection de changement [Termes IGN] données de terrain [Termes IGN] image captée par drone [Termes IGN] Nouvelle-Galles du Sud [Termes IGN] pesticide [Termes IGN] réserve naturelle [Termes IGN] série temporelle [Termes IGN] surveillance de la végétation Résumé : (auteur) We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected. Numéro de notice : A2020-716 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102085 date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102085 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96287 [article]

Visualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 14 p. Titre : Visualizing when, where, and how fires happen in U.S. parks and protected areas Type de document : Article/Communication Auteurs : Nicole C. Inglis, Auteur ; Jelena Vukomanovic, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aire protégée [Termes IGN] changement climatique [Termes IGN] Floride (Etats-Unis) [Termes IGN] géodatabase [Termes IGN] incendie de forêt [Termes IGN] lutte contre l'incendie [Termes IGN] modèle dynamique [Termes IGN] parc naturel national [Termes IGN] prévention des risques [Termes IGN] réserve naturelle [Termes IGN] variation saisonnière [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Fire management in protected areas faces mounting obstacles as climate change alters disturbance regimes, resources are diverted to fighting wildfires, and more people live along the boundaries of parks. Evidence-based prescribed fire management and improved communication with stakeholders is vital to reducing fire risk while maintaining public trust. Numerous national fire databases document when and where natural, prescribed, and human-caused fires have occurred on public lands in the United States. However, these databases are incongruous and non-standardized, making it difficult to visualize spatiotemporal patterns of fire and engage stakeholders in decision-making. We created interactive decision analytics (“VISTAFiRe”) that transform fire history data into clear visualizations of the spatial and temporal dimensions of fire and its management. We demonstrate the utility of our approach using Big Cypress National Preserve and Everglades National Park as examples of protected areas experiencing fire regime change between 1980 and 2017. Our open source visualizations may be applied to any data from the National Park Service Wildland Fire Events Geodatabase, with flexibility to communicate shifts in fire regimes over time, such as the type of ignition, duration and magnitude, and changes in seasonal occurrence. Application of the tool to Everglades and Big Cypress revealed that natural wildfires are occurring earlier in the wildfire season, while human-caused and prescribed wildfires are becoming less and more common, respectively. These new avenues of stakeholder communication are allowing the National Park Service to devise research plans to prepare for environmental change, guide resource allocation, and support decision-making in a clear and timely manner. Numéro de notice : A2020-298 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050333 date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.3390/ijgi9050333 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95138 [article]

La Réserve biologique intégrale du Mont-Ventoux, un espace d’étude des écosystèmes forestiers hors sylviculture / Jérémy Terracol in Naturae, n° 5 ([29/03/2017])  

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Inventaires : les bryophytes de la Réserve naturelle régionale des étangs de Mépieu / Frédéric Gourges in Lo Parvi, n° 24 (2016) 

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Effects of landscape design of forest reserves on Saproxylic beetle diversity / Christophe Bouget in Conservation biology, vol 30 n° 1 (February 2016)  

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Integrating a raster geographical information system with multi-objective land allocation optimization for conservation reserve design / WeiWei Dai in Transactions in GIS, vol 18 n° 6 (December 2014)  

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Detecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm / Abduwasit Ghulam in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)

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Zoologische und botanische Untersuchungen „Haard“ 2011-2013 / Danièle Murat (2014)  

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Cartographie et participation pour la coopération environnementale : le terrain et la restitution des savoirs traditionnels en Afrique subsaharienne / F. Burini in Annales de géographie, n° 687 - 688 (septembre - décembre 2012)  

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Spatially modelling pathways of migratory birds for nature reserve site selection / J.A. Downs in International journal of geographical information science IJGIS, vol 22 n° 6-7 (june 2008)

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Amélioration du SIG des espaces protégés alpins / Marion Drye (2008)

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Réserves biologiques des espaces naturels remarquables en forêt publique / Office national des forêts (France) (2008) 

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