A novel artificial neural network methodology to produce high-resolution bioclimatic maps using Earth Observation data: A case study for Cyprus

Philippopoulos, Kostas; Pantavou, Katerina; Cartalis, Constantinos; Agathangelidis, Ilias; Mavrakou, Thaleia; Polydoros, Anastasios; Nikolopoulos, Georgios K.

doi:10.1016/j.scitotenv.2023.164734

Cited by 2 publications

(2 citation statements)

References 51 publications

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“…There are different methods for selecting the most vulnerable areas in the city. Researchers are investigating the use of participatory mapping and various machine learning algorithms and developing new methods based on artificial neural networks (ANNs) [8][9][10]. The use of these new methods makes it possible to supplement and confirm the results obtained with other methods, e.g., as part of a multi-criteria analysis with GIS models [10].…”

Section: Introductionmentioning

confidence: 99%

Delimitation and Prioritization of Climate-Affected Areas Using the Example of a Post-Industrial City

Bronder,

Kurianowicz,

Piasecka

et al. 2024

Sustainability

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This study adapted and tested an approach to identifying areas that are particularly vulnerable to climate-related hazards using the example of the post-industrial city of Knurów in Poland. This study applied a multi-criteria method using the analytical hierarchy process based on GIS map data. The analysis was divided into statistical regions defined for the city. Fifteen attributes were defined for each statistical region. The applied methods provided verified spatial information related to specific climate change hazards. The results showed that the most vulnerable areas were the areas with intensive development in the city center and in the southwestern part of the city. Among the 15 attributes, the most significant were T1 (number of inhabitants in zones with a higher potential thermal risk index by statistical district) with a value of 0.163, G2 (percentage of the sum of tree-shaded areas in built-up areas within the territory of a given statistical district) with 0.143 and H3 (number of buildings in areas of drainless basins and 100-year water). This method effectively identified the most vulnerable areas. The use of such a method can help in the preparation of planning documents and urban adaptation plans by determining the thermally and hydrologically vulnerable areas with the least developed green infrastructure as an exposure-mitigating factor.

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Section: Introductionmentioning

confidence: 99%

Delimitation and Prioritization of Climate-Affected Areas Using the Example of a Post-Industrial City

Bronder,

Kurianowicz,

Piasecka

et al. 2024

Sustainability

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“…Nonetheless, a notable constraint observed in preceding studies is their failure to incorporate a deliberate examination of the phylogenetic interconnections among species. This oversight has led to an inadequacy in portraying the multifaceted evolutionary chronicle of floristic territories, as well as a deficiency in bioclimatic and palaeobiogeographic contextual elucidation [16,17].…”

Section: Introductionmentioning

confidence: 99%

Phylogenetic Partitioning of Gansu Flora: Unveiling the Core Transitional Zone of Chinese Flora

Li,

Tian,

Chong

et al. 2023

Plants

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Floristic regions, conventionally established using species distribution patterns, have often overlooked the phylogenetic relationships among taxa. However, how phylogenetic relationships influence the historical interconnections within and among biogeographic regions remains inadequately understood. In this research, we compiled distribution data for seed plants in Gansu, a region of significant biogeographic diversity located in northwestern China.We proposed a novel framework for floristic regions within Gansu, integrating distribution data and phylogenetic relationships of genera-level native seed plants, aiming to explore the relationship between phylogenetic relatedness, taxonomic composition, and regional phylogenetic delineation. We found that (1) phylogenetic relatedness was strongly correlated with the taxonomic composition among floras in Gansu. (2) The southeastern Gansu region showed the lowest level of spatial turnover in both phylogenetic relationships and the taxonomic composition of floristic assemblages across the Gansu region. (3) Null model analyses indicated nonrandom phylogenetic structure across the region, where most areas showed higher phylogenetic turnover than expected given the underlying taxonomic composition between sites. (4) Our results demonstrated a consistent pattern across various regionalization schemes and highlighted the preference for employing the phylogenetic dissimilarity approach in biogeographical regionalization investigations. (5) Employing the phylogenetic dissimilarity approach, we identified nine distinct floristic regions in Gansu that are categorized into two broader geographical units, namely the northwest and southeast. (6) Based on the phylogenetic graphic regions of China across this area.

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A novel artificial neural network methodology to produce high-resolution bioclimatic maps using Earth Observation data: A case study for Cyprus

Cited by 2 publications

References 51 publications

Delimitation and Prioritization of Climate-Affected Areas Using the Example of a Post-Industrial City

Delimitation and Prioritization of Climate-Affected Areas Using the Example of a Post-Industrial City

Phylogenetic Partitioning of Gansu Flora: Unveiling the Core Transitional Zone of Chinese Flora

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