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En el instante 23 de junio de 2026, 15:59:29 UTC,
-
Modificado el valor del campo
spatial_coverage
a[{'bbox': '{"type": "Polygon", "coordinates": [[[-18.16, 27.64], [4.32, 27.64], [4.32, 43.79], [-18.16, 43.79], [-18.16, 27.64]]]}', 'centroid': '{"type": "Point", "coordinates": [-6.92, 35.715]}', 'text': 'España', 'uri': 'http://datos.gob.es/recurso/sector-publico/territorio/Pais/España'}]
en Comparing spatial statistical methods to detect amphibian road mortality hotspots.
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| 76 | "notes": "Animal mortality on roads is one of the main concerns on | 76 | "notes": "Animal mortality on roads is one of the main concerns on | ||
| 77 | wildlife conservation. Due to their habitat requirements, amphibians | 77 | wildlife conservation. Due to their habitat requirements, amphibians | ||
| 78 | became one of the most commonly road-killed group and this may affect | 78 | became one of the most commonly road-killed group and this may affect | ||
| 79 | their population viability. Implementation of mitigation measures may | 79 | their population viability. Implementation of mitigation measures may | ||
| 80 | overcome the problem. However, due to the extensive road network, | 80 | overcome the problem. However, due to the extensive road network, | ||
| 81 | their application is very expensive and required a better | 81 | their application is very expensive and required a better | ||
| 82 | understanding in where they should be implemented. Mortality hotspots | 82 | understanding in where they should be implemented. Mortality hotspots | ||
| 83 | can be identified as clusters of road-killed records) using GIS | 83 | can be identified as clusters of road-killed records) using GIS | ||
| 84 | (Geographic Information Systems). Although there are several | 84 | (Geographic Information Systems). Although there are several | ||
| 85 | statistical methods available, it is lacking a comparison analysis of | 85 | statistical methods available, it is lacking a comparison analysis of | ||
| 86 | them in order to understand their pros and contras. The aim of this | 86 | them in order to understand their pros and contras. The aim of this | ||
| 87 | study was to analyse possible differences between global, multi-scale | 87 | study was to analyse possible differences between global, multi-scale | ||
| 88 | and local spatial analysis methods in defining hotspots using | 88 | and local spatial analysis methods in defining hotspots using | ||
| 89 | amphibian road fatality data collected in northern Portugal country | 89 | amphibian road fatality data collected in northern Portugal country | ||
| 90 | roads. We calculated the Nearest neighbor index, Morans I and | 90 | roads. We calculated the Nearest neighbor index, Morans I and | ||
| 91 | Getis-ord General in order to compare the global clustering of points | 91 | Getis-ord General in order to compare the global clustering of points | ||
| 92 | in seven sampled roads, and three were identified as clustered. We | 92 | in seven sampled roads, and three were identified as clustered. We | ||
| 93 | used Ripley K-function, Ripley L-function and F function to calculate | 93 | used Ripley K-function, Ripley L-function and F function to calculate | ||
| 94 | the best scale for Malo's equation and Kernel density analysis in | 94 | the best scale for Malo's equation and Kernel density analysis in | ||
| 95 | detecting hotspots and we compared their detection performance with | 95 | detecting hotspots and we compared their detection performance with | ||
| 96 | Local Indicators of Association (LISA) (i.e Local Moran's I and | 96 | Local Indicators of Association (LISA) (i.e Local Moran's I and | ||
| 97 | Getis-ord Gi*). Three different GIS software applications were used: | 97 | Getis-ord Gi*). Three different GIS software applications were used: | ||
| 98 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | 98 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | ||
| 99 | Results showed the importance of using multidistance spatial cluster | 99 | Results showed the importance of using multidistance spatial cluster | ||
| 100 | analysis to define the best scale for hotspot detection with | 100 | analysis to define the best scale for hotspot detection with | ||
| 101 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | 101 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | ||
| 102 | the advantages of Local Indicators of Association (LISA) for detecting | 102 | the advantages of Local Indicators of Association (LISA) for detecting | ||
| 103 | clusters with the contribution of each individual observation (Local | 103 | clusters with the contribution of each individual observation (Local | ||
| 104 | Morans I and Getis-ord Gi*).", | 104 | Morans I and Getis-ord Gi*).", | ||
| 105 | "notes_translated": { | 105 | "notes_translated": { | ||
| 106 | "en": "Animal mortality on roads is one of the main concerns on | 106 | "en": "Animal mortality on roads is one of the main concerns on | ||
| 107 | wildlife conservation. Due to their habitat requirements, amphibians | 107 | wildlife conservation. Due to their habitat requirements, amphibians | ||
| 108 | became one of the most commonly road-killed group and this may affect | 108 | became one of the most commonly road-killed group and this may affect | ||
| 109 | their population viability. Implementation of mitigation measures may | 109 | their population viability. Implementation of mitigation measures may | ||
| 110 | overcome the problem. However, due to the extensive road network, | 110 | overcome the problem. However, due to the extensive road network, | ||
| 111 | their application is very expensive and required a better | 111 | their application is very expensive and required a better | ||
| 112 | understanding in where they should be implemented. Mortality hotspots | 112 | understanding in where they should be implemented. Mortality hotspots | ||
| 113 | can be identified as clusters of road-killed records) using GIS | 113 | can be identified as clusters of road-killed records) using GIS | ||
| 114 | (Geographic Information Systems). Although there are several | 114 | (Geographic Information Systems). Although there are several | ||
| 115 | statistical methods available, it is lacking a comparison analysis of | 115 | statistical methods available, it is lacking a comparison analysis of | ||
| 116 | them in order to understand their pros and contras. The aim of this | 116 | them in order to understand their pros and contras. The aim of this | ||
| 117 | study was to analyse possible differences between global, multi-scale | 117 | study was to analyse possible differences between global, multi-scale | ||
| 118 | and local spatial analysis methods in defining hotspots using | 118 | and local spatial analysis methods in defining hotspots using | ||
| 119 | amphibian road fatality data collected in northern Portugal country | 119 | amphibian road fatality data collected in northern Portugal country | ||
| 120 | roads. We calculated the Nearest neighbor index, Morans I and | 120 | roads. We calculated the Nearest neighbor index, Morans I and | ||
| 121 | Getis-ord General in order to compare the global clustering of points | 121 | Getis-ord General in order to compare the global clustering of points | ||
| 122 | in seven sampled roads, and three were identified as clustered. We | 122 | in seven sampled roads, and three were identified as clustered. We | ||
| 123 | used Ripley K-function, Ripley L-function and F function to calculate | 123 | used Ripley K-function, Ripley L-function and F function to calculate | ||
| 124 | the best scale for Malo's equation and Kernel density analysis in | 124 | the best scale for Malo's equation and Kernel density analysis in | ||
| 125 | detecting hotspots and we compared their detection performance with | 125 | detecting hotspots and we compared their detection performance with | ||
| 126 | Local Indicators of Association (LISA) (i.e Local Moran's I and | 126 | Local Indicators of Association (LISA) (i.e Local Moran's I and | ||
| 127 | Getis-ord Gi*). Three different GIS software applications were used: | 127 | Getis-ord Gi*). Three different GIS software applications were used: | ||
| 128 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | 128 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | ||
| 129 | Results showed the importance of using multidistance spatial cluster | 129 | Results showed the importance of using multidistance spatial cluster | ||
| 130 | analysis to define the best scale for hotspot detection with | 130 | analysis to define the best scale for hotspot detection with | ||
| 131 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | 131 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | ||
| 132 | the advantages of Local Indicators of Association (LISA) for detecting | 132 | the advantages of Local Indicators of Association (LISA) for detecting | ||
| 133 | clusters with the contribution of each individual observation (Local | 133 | clusters with the contribution of each individual observation (Local | ||
| 134 | Morans I and Getis-ord Gi*).", | 134 | Morans I and Getis-ord Gi*).", | ||
| 135 | "es": "Animal mortality on roads is one of the main concerns on | 135 | "es": "Animal mortality on roads is one of the main concerns on | ||
| 136 | wildlife conservation. Due to their habitat requirements, amphibians | 136 | wildlife conservation. Due to their habitat requirements, amphibians | ||
| 137 | became one of the most commonly road-killed group and this may affect | 137 | became one of the most commonly road-killed group and this may affect | ||
| 138 | their population viability. Implementation of mitigation measures may | 138 | their population viability. Implementation of mitigation measures may | ||
| 139 | overcome the problem. However, due to the extensive road network, | 139 | overcome the problem. However, due to the extensive road network, | ||
| 140 | their application is very expensive and required a better | 140 | their application is very expensive and required a better | ||
| 141 | understanding in where they should be implemented. Mortality hotspots | 141 | understanding in where they should be implemented. Mortality hotspots | ||
| 142 | can be identified as clusters of road-killed records) using GIS | 142 | can be identified as clusters of road-killed records) using GIS | ||
| 143 | (Geographic Information Systems). Although there are several | 143 | (Geographic Information Systems). Although there are several | ||
| 144 | statistical methods available, it is lacking a comparison analysis of | 144 | statistical methods available, it is lacking a comparison analysis of | ||
| 145 | them in order to understand their pros and contras. The aim of this | 145 | them in order to understand their pros and contras. The aim of this | ||
| 146 | study was to analyse possible differences between global, multi-scale | 146 | study was to analyse possible differences between global, multi-scale | ||
| 147 | and local spatial analysis methods in defining hotspots using | 147 | and local spatial analysis methods in defining hotspots using | ||
| 148 | amphibian road fatality data collected in northern Portugal country | 148 | amphibian road fatality data collected in northern Portugal country | ||
| 149 | roads. We calculated the Nearest neighbor index, Morans I and | 149 | roads. We calculated the Nearest neighbor index, Morans I and | ||
| 150 | Getis-ord General in order to compare the global clustering of points | 150 | Getis-ord General in order to compare the global clustering of points | ||
| 151 | in seven sampled roads, and three were identified as clustered. We | 151 | in seven sampled roads, and three were identified as clustered. We | ||
| 152 | used Ripley K-function, Ripley L-function and F function to calculate | 152 | used Ripley K-function, Ripley L-function and F function to calculate | ||
| 153 | the best scale for Malo's equation and Kernel density analysis in | 153 | the best scale for Malo's equation and Kernel density analysis in | ||
| 154 | detecting hotspots and we compared their detection performance with | 154 | detecting hotspots and we compared their detection performance with | ||
| 155 | Local Indicators of Association (LISA) (i.e Local Moran's I and | 155 | Local Indicators of Association (LISA) (i.e Local Moran's I and | ||
| 156 | Getis-ord Gi*). Three different GIS software applications were used: | 156 | Getis-ord Gi*). Three different GIS software applications were used: | ||
| 157 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | 157 | ArcGis, Quantum GIS with R (opensource) and GeoDa (opensource). | ||
| 158 | Results showed the importance of using multidistance spatial cluster | 158 | Results showed the importance of using multidistance spatial cluster | ||
| 159 | analysis to define the best scale for hotspot detection with | 159 | analysis to define the best scale for hotspot detection with | ||
| 160 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | 160 | Malo\u00b4s equation and Kernel density analysis. Here we also suggest | ||
| 161 | the advantages of Local Indicators of Association (LISA) for detecting | 161 | the advantages of Local Indicators of Association (LISA) for detecting | ||
| 162 | clusters with the contribution of each individual observation (Local | 162 | clusters with the contribution of each individual observation (Local | ||
| 163 | Morans I and Getis-ord Gi*)." | 163 | Morans I and Getis-ord Gi*)." | ||
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