Search results for: hough forest

Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

Abstract:

Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

Procedia PDF Downloads 40

Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

Abstract:

Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

Procedia PDF Downloads 146

Authors: Angshuman Raha, Abesh Kumar Sanyal, Uttaran Bandyopadhyay, Kaushik Mallick, Kamalika Bhattacharyya, Subrata Gayen, Gaurab Nandi Das, Mohd. Ali, Kailash Chandra

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Indian Himalayan Region (IHR), due to its sheer latitudinal and altitudinal expanse, acts as a mixing ground for different zoogeographic faunal elements. The innumerable unique and distributional restricted rare species of IHR are constantly being threatened with extinction by the ongoing climate change scenario. Many of which might have faced extinction without even being noticed or discovered. Monitoring the community dynamics of a suitable taxon is indispensable to assess the effect of this global perturbation at micro-habitat level. Lepidoptera, particularly moths are suitable for this purpose due to their huge diversity and strict herbivorous nature. The present study aimed to collate scattered historical records of moths from IHR and spatially disseminate the same in Geographic Information System (GIS) domain. The study also intended to identify moth species with significant altitudinal shifts which could be prioritised for monitoring programme to assess the effect of climate change on biodiversity. A robust database on moths recorded from IHR was prepared from voluminous secondary literature and museum collections. Historical sampling points were transformed into richness grids which were spatially overlaid on altitude, annual precipitation and vegetation layers separately to show moth richness patterns along major environmental gradients. Primary samplings were done by setting standard light traps at 11 Protected Areas representing five Indian Himalayan biogeographic provinces. To identify significant altitudinal shifts, past and present altitudinal records of the identified species from primary samplings were compared. A consolidated list of 4107 species belonging to 1726 genera of 62 families of moths was prepared from a total of 10,685 historical records from IHR. Family-wise assemblage revealed Erebidae to be the most speciose family with 913 species under 348 genera, followed by Geometridae with 879 species under 309 genera and Noctuidae with 525 species under 207 genera. Among biogeographic provinces, Central Himalaya represented maximum records with 2248 species, followed by Western and North-western Himalaya with 1799 and 877 species, respectively. Spatial analysis revealed species richness was more or less uniform (up to 150 species record per cell) across IHR. Throughout IHR, the middle elevation zones between 1000-2000m encompassed high species richness. Temperate coniferous forest associated with 1500-2000mm rainfall zone showed maximum species richness. Total 752 species of moths were identified representing 23 families from the present sampling. 13 genera were identified which were restricted to specialized habitats of alpine meadows over 3500m. Five historical localities with high richness of >150 species were selected which could be considered for repeat sampling to assess climate change influence on moth assemblage. Of the 7 species exhibiting significant altitudinal ascend of >2000m, Trachea auriplena, Diphtherocome fasciata (Noctuidae) and Actias winbrechlini (Saturniidae) showed maximum range shift of >2500m, indicating intensive monitoring of these species. Great Himalayan National Park harbours most diverse assemblage of high-altitude restricted species and should be a priority site for habitat conservation. Among the 13 range restricted genera, Arichanna, Opisthograptis, Photoscotosia (Geometridae), Phlogophora, Anaplectoides and Paraxestia (Noctuidae) were dominant and require rigorous monitoring, as they are most susceptible to climatic perturbations.

Keywords: altitudinal shifts, climate change, historical records, Indian Himalayan region, Lepidoptera

Procedia PDF Downloads 155

Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

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Natural hazard assessment and monitoring are crucial components in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology led to the development of state-of-the-art systems for assessing and monitoring these hazards. These technologies, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. Enhancing disaster resilience is crucial as it significantly improves our ability to predict, prepare for, and mitigate the impacts of natural disasters, ultimately saving lives and reducing economic losses. For wildfire risk assessment, a scalar wildfire occurrence risk index has been created based on the predictions of machine learning models. Our objective was to train an ML model that learns to derive a fire susceptibility score when given as input a vector of features assigned to certain spatiotemporal coordinates. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. For flood risk assessment, a multi-faceted approach has been employed, including the application of remote sensing techniques, the collection and processing of data from population, buildings, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. For geohazards monitoring (e.g., landslides, subsidence), synthetic aperture radar (SAR) and optical satellite imagery have been combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR (Interferometric SAR) methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through knowledge transfer activities, fostering continuous collaboration between Greek and Cypriot experts. Furthermore, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the entire region's resilience to disasters. The EXCELSIOR project, funding this opportunity, is committed to empowering Cyprus with the tools and expertise needed to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgment: Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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