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En el instante 23 de junio de 2026, 16:00:00 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 GPS-based real-time application to warn drivers of high risk of animal-vehicle collision.
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| 2 | "access_rights": | 2 | "access_rights": | ||
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| 4 | "alternate_identifier": "ISBN: 978-91-637-7327-3", | 4 | "alternate_identifier": "ISBN: 978-91-637-7327-3", | ||
| 5 | "author": "Colino-Rabanal, V.J.", | 5 | "author": "Colino-Rabanal, V.J.", | ||
| 6 | "author_name": "Colino-Rabanal, V.J.", | 6 | "author_name": "Colino-Rabanal, V.J.", | ||
| 7 | "classification_variables": { | 7 | "classification_variables": { | ||
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| 10 | "conforms_to": [ | 10 | "conforms_to": [ | ||
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| 25 | "contact_name": "Organismo publicador del Cat\u00e1logo", | 25 | "contact_name": "Organismo publicador del Cat\u00e1logo", | ||
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| 30 | "contact_url": "https://organismo.example.org/", | 30 | "contact_url": "https://organismo.example.org/", | ||
| 31 | "created": "2025-05-23", | 31 | "created": "2025-05-23", | ||
| 32 | "creator": [ | 32 | "creator": [ | ||
| 33 | { | 33 | { | ||
| 34 | "name": "Colino-Rabanal, V.J." | 34 | "name": "Colino-Rabanal, V.J." | ||
| 35 | } | 35 | } | ||
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| 37 | "creator_user_id": "d24a314a-79ce-48c0-abd9-54cb42706da4", | 37 | "creator_user_id": "d24a314a-79ce-48c0-abd9-54cb42706da4", | ||
| 38 | "dataset_scope": "non_spatial_dataset", | 38 | "dataset_scope": "non_spatial_dataset", | ||
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| 44 | "groups": [], | 44 | "groups": [], | ||
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| 48 | "inspire_id": "", | 48 | "inspire_id": "", | ||
| 49 | "isopen": true, | 49 | "isopen": true, | ||
| 50 | "language": | 50 | "language": | ||
| 51 | "http://publications.europa.eu/resource/authority/language/SPA", | 51 | "http://publications.europa.eu/resource/authority/language/SPA", | ||
| 52 | "license_id": "cc-by", | 52 | "license_id": "cc-by", | ||
| 53 | "license_title": "Creative Commons Attribution", | 53 | "license_title": "Creative Commons Attribution", | ||
| 54 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | 54 | "license_url": "http://www.opendefinition.org/licenses/cc-by", | ||
| 55 | "lineage_process_steps": [], | 55 | "lineage_process_steps": [], | ||
| 56 | "lineage_source": [ | 56 | "lineage_source": [ | ||
| 57 | "2014 IENE International Conference. Programme and abstracts", | 57 | "2014 IENE International Conference. Programme and abstracts", | ||
| 58 | "pag. 42" | 58 | "pag. 42" | ||
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| 60 | "maintainer": "", | 60 | "maintainer": "", | ||
| 61 | "maintainer_name": "", | 61 | "maintainer_name": "", | ||
| 62 | "metadata_created": "2026-06-23T14:49:56.328992", | 62 | "metadata_created": "2026-06-23T14:49:56.328992", | ||
| n | 63 | "metadata_modified": "2026-06-23T14:49:56.328998", | n | 63 | "metadata_modified": "2026-06-23T16:00:00.358519", |
| 64 | "metadata_profile": [ | 64 | "metadata_profile": [ | ||
| 65 | "https://www.w3.org/TR/vocab-dcat-3/" | 65 | "https://www.w3.org/TR/vocab-dcat-3/" | ||
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| 67 | "miteco_data_population": { | 67 | "miteco_data_population": { | ||
| 68 | "es": "" | 68 | "es": "" | ||
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| 70 | "miteco_data_territory": { | 70 | "miteco_data_territory": { | ||
| 71 | "es": "" | 71 | "es": "" | ||
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| 73 | "miteco_dataset_type": | 73 | "miteco_dataset_type": | ||
| 74 | //publications.europa.eu/resource/authority/dataset-type/STATISTICAL", | 74 | //publications.europa.eu/resource/authority/dataset-type/STATISTICAL", | ||
| 75 | "miteco_geo_level": "1", | 75 | "miteco_geo_level": "1", | ||
| 76 | "modified": "2026-06-23", | 76 | "modified": "2026-06-23", | ||
| 77 | "name": "c2e5ffcf-4005-5839-af34-864fd1dd77d4", | 77 | "name": "c2e5ffcf-4005-5839-af34-864fd1dd77d4", | ||
| 78 | "notes": "A wide range of mitigation measures have been proposed and | 78 | "notes": "A wide range of mitigation measures have been proposed and | ||
| 79 | tested to reduce the number of animal-vehicle collision (AVC). These | 79 | tested to reduce the number of animal-vehicle collision (AVC). These | ||
| 80 | mitigation measures work at different spatial scales, from regional | 80 | mitigation measures work at different spatial scales, from regional | ||
| 81 | planning to transversal structures and other mechanisms that work at | 81 | planning to transversal structures and other mechanisms that work at | ||
| 82 | road segment scale. They have different objectives, aimed to modify | 82 | road segment scale. They have different objectives, aimed to modify | ||
| 83 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | 83 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | ||
| 84 | they also show different costs and effectiveness. The mitigation | 84 | they also show different costs and effectiveness. The mitigation | ||
| 85 | measures focused on the driver as the main responsible for avoiding | 85 | measures focused on the driver as the main responsible for avoiding | ||
| 86 | AVC are commonly installed throughout the world. For example, traffic | 86 | AVC are commonly installed throughout the world. For example, traffic | ||
| 87 | warning signs are the most widely applied measure. The warning expects | 87 | warning signs are the most widely applied measure. The warning expects | ||
| 88 | to get driver\u00b4s attention and to manage a reduction of the | 88 | to get driver\u00b4s attention and to manage a reduction of the | ||
| 89 | vehicle speed, considering that speed is one of the most remarkable | 89 | vehicle speed, considering that speed is one of the most remarkable | ||
| 90 | explanatory variables involved in AVC occurrence and in the | 90 | explanatory variables involved in AVC occurrence and in the | ||
| 91 | seriousness of them. Nevertheless, road signs have shown limited | 91 | seriousness of them. Nevertheless, road signs have shown limited | ||
| 92 | long-term effectiveness because, after a certain period of time, the | 92 | long-term effectiveness because, after a certain period of time, the | ||
| 93 | driver\u00b4s response to the warning decreases. This fact can be | 93 | driver\u00b4s response to the warning decreases. This fact can be | ||
| 94 | explained partly because of the absence of temporal correspondence | 94 | explained partly because of the absence of temporal correspondence | ||
| 95 | between the warning and the real risk. Effectiveness may increase | 95 | between the warning and the real risk. Effectiveness may increase | ||
| 96 | focusing the warning only in those moments and locations of high risk | 96 | focusing the warning only in those moments and locations of high risk | ||
| 97 | of AVC. Thus, one of the main characteristics that we can exploit to | 97 | of AVC. Thus, one of the main characteristics that we can exploit to | ||
| 98 | deal with the AVC problematic is that they are not randomly | 98 | deal with the AVC problematic is that they are not randomly | ||
| 99 | distributed either the space or time. There are important temporal | 99 | distributed either the space or time. There are important temporal | ||
| 100 | changes across the seasons, within the day or within other facts as | 100 | changes across the seasons, within the day or within other facts as | ||
| 101 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | 101 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | ||
| 102 | and habitats. Hence, it is possible to model the spatio-temporal | 102 | and habitats. Hence, it is possible to model the spatio-temporal | ||
| 103 | probability of AVC occurrence with a road network. We have obtained | 103 | probability of AVC occurrence with a road network. We have obtained | ||
| 104 | the model for AVC in Castile and Leon region (NW Spain). The resultant | 104 | the model for AVC in Castile and Leon region (NW Spain). The resultant | ||
| 105 | spatio-temporal model can be implemented in an app for smartphones or | 105 | spatio-temporal model can be implemented in an app for smartphones or | ||
| 106 | incorporated easily to a GPS vehicle navigation system, coupling it | 106 | incorporated easily to a GPS vehicle navigation system, coupling it | ||
| 107 | with the positioning system, the calendar and the clock of the device. | 107 | with the positioning system, the calendar and the clock of the device. | ||
| 108 | The result is an application that shows at real-time the probability | 108 | The result is an application that shows at real-time the probability | ||
| 109 | of AVC considering the vehicle positioning. Al alarm alerts the driver | 109 | of AVC considering the vehicle positioning. Al alarm alerts the driver | ||
| 110 | only when the risk of AVC is high, this is, when the driver passes | 110 | only when the risk of AVC is high, this is, when the driver passes | ||
| 111 | through a road segment with high probability of AVC occurrence just in | 111 | through a road segment with high probability of AVC occurrence just in | ||
| 112 | a period of time (month, hour, moon phase, etc.) given to AVC.", | 112 | a period of time (month, hour, moon phase, etc.) given to AVC.", | ||
| 113 | "notes_translated": { | 113 | "notes_translated": { | ||
| 114 | "en": "A wide range of mitigation measures have been proposed and | 114 | "en": "A wide range of mitigation measures have been proposed and | ||
| 115 | tested to reduce the number of animal-vehicle collision (AVC). These | 115 | tested to reduce the number of animal-vehicle collision (AVC). These | ||
| 116 | mitigation measures work at different spatial scales, from regional | 116 | mitigation measures work at different spatial scales, from regional | ||
| 117 | planning to transversal structures and other mechanisms that work at | 117 | planning to transversal structures and other mechanisms that work at | ||
| 118 | road segment scale. They have different objectives, aimed to modify | 118 | road segment scale. They have different objectives, aimed to modify | ||
| 119 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | 119 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | ||
| 120 | they also show different costs and effectiveness. The mitigation | 120 | they also show different costs and effectiveness. The mitigation | ||
| 121 | measures focused on the driver as the main responsible for avoiding | 121 | measures focused on the driver as the main responsible for avoiding | ||
| 122 | AVC are commonly installed throughout the world. For example, traffic | 122 | AVC are commonly installed throughout the world. For example, traffic | ||
| 123 | warning signs are the most widely applied measure. The warning expects | 123 | warning signs are the most widely applied measure. The warning expects | ||
| 124 | to get driver\u00b4s attention and to manage a reduction of the | 124 | to get driver\u00b4s attention and to manage a reduction of the | ||
| 125 | vehicle speed, considering that speed is one of the most remarkable | 125 | vehicle speed, considering that speed is one of the most remarkable | ||
| 126 | explanatory variables involved in AVC occurrence and in the | 126 | explanatory variables involved in AVC occurrence and in the | ||
| 127 | seriousness of them. Nevertheless, road signs have shown limited | 127 | seriousness of them. Nevertheless, road signs have shown limited | ||
| 128 | long-term effectiveness because, after a certain period of time, the | 128 | long-term effectiveness because, after a certain period of time, the | ||
| 129 | driver\u00b4s response to the warning decreases. This fact can be | 129 | driver\u00b4s response to the warning decreases. This fact can be | ||
| 130 | explained partly because of the absence of temporal correspondence | 130 | explained partly because of the absence of temporal correspondence | ||
| 131 | between the warning and the real risk. Effectiveness may increase | 131 | between the warning and the real risk. Effectiveness may increase | ||
| 132 | focusing the warning only in those moments and locations of high risk | 132 | focusing the warning only in those moments and locations of high risk | ||
| 133 | of AVC. Thus, one of the main characteristics that we can exploit to | 133 | of AVC. Thus, one of the main characteristics that we can exploit to | ||
| 134 | deal with the AVC problematic is that they are not randomly | 134 | deal with the AVC problematic is that they are not randomly | ||
| 135 | distributed either the space or time. There are important temporal | 135 | distributed either the space or time. There are important temporal | ||
| 136 | changes across the seasons, within the day or within other facts as | 136 | changes across the seasons, within the day or within other facts as | ||
| 137 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | 137 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | ||
| 138 | and habitats. Hence, it is possible to model the spatio-temporal | 138 | and habitats. Hence, it is possible to model the spatio-temporal | ||
| 139 | probability of AVC occurrence with a road network. We have obtained | 139 | probability of AVC occurrence with a road network. We have obtained | ||
| 140 | the model for AVC in Castile and Leon region (NW Spain). The resultant | 140 | the model for AVC in Castile and Leon region (NW Spain). The resultant | ||
| 141 | spatio-temporal model can be implemented in an app for smartphones or | 141 | spatio-temporal model can be implemented in an app for smartphones or | ||
| 142 | incorporated easily to a GPS vehicle navigation system, coupling it | 142 | incorporated easily to a GPS vehicle navigation system, coupling it | ||
| 143 | with the positioning system, the calendar and the clock of the device. | 143 | with the positioning system, the calendar and the clock of the device. | ||
| 144 | The result is an application that shows at real-time the probability | 144 | The result is an application that shows at real-time the probability | ||
| 145 | of AVC considering the vehicle positioning. Al alarm alerts the driver | 145 | of AVC considering the vehicle positioning. Al alarm alerts the driver | ||
| 146 | only when the risk of AVC is high, this is, when the driver passes | 146 | only when the risk of AVC is high, this is, when the driver passes | ||
| 147 | through a road segment with high probability of AVC occurrence just in | 147 | through a road segment with high probability of AVC occurrence just in | ||
| 148 | a period of time (month, hour, moon phase, etc.) given to AVC.", | 148 | a period of time (month, hour, moon phase, etc.) given to AVC.", | ||
| 149 | "es": "A wide range of mitigation measures have been proposed and | 149 | "es": "A wide range of mitigation measures have been proposed and | ||
| 150 | tested to reduce the number of animal-vehicle collision (AVC). These | 150 | tested to reduce the number of animal-vehicle collision (AVC). These | ||
| 151 | mitigation measures work at different spatial scales, from regional | 151 | mitigation measures work at different spatial scales, from regional | ||
| 152 | planning to transversal structures and other mechanisms that work at | 152 | planning to transversal structures and other mechanisms that work at | ||
| 153 | road segment scale. They have different objectives, aimed to modify | 153 | road segment scale. They have different objectives, aimed to modify | ||
| 154 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | 154 | driver\u00b4s behavior, modify animal behavior, or both. Moreover, | ||
| 155 | they also show different costs and effectiveness. The mitigation | 155 | they also show different costs and effectiveness. The mitigation | ||
| 156 | measures focused on the driver as the main responsible for avoiding | 156 | measures focused on the driver as the main responsible for avoiding | ||
| 157 | AVC are commonly installed throughout the world. For example, traffic | 157 | AVC are commonly installed throughout the world. For example, traffic | ||
| 158 | warning signs are the most widely applied measure. The warning expects | 158 | warning signs are the most widely applied measure. The warning expects | ||
| 159 | to get driver\u00b4s attention and to manage a reduction of the | 159 | to get driver\u00b4s attention and to manage a reduction of the | ||
| 160 | vehicle speed, considering that speed is one of the most remarkable | 160 | vehicle speed, considering that speed is one of the most remarkable | ||
| 161 | explanatory variables involved in AVC occurrence and in the | 161 | explanatory variables involved in AVC occurrence and in the | ||
| 162 | seriousness of them. Nevertheless, road signs have shown limited | 162 | seriousness of them. Nevertheless, road signs have shown limited | ||
| 163 | long-term effectiveness because, after a certain period of time, the | 163 | long-term effectiveness because, after a certain period of time, the | ||
| 164 | driver\u00b4s response to the warning decreases. This fact can be | 164 | driver\u00b4s response to the warning decreases. This fact can be | ||
| 165 | explained partly because of the absence of temporal correspondence | 165 | explained partly because of the absence of temporal correspondence | ||
| 166 | between the warning and the real risk. Effectiveness may increase | 166 | between the warning and the real risk. Effectiveness may increase | ||
| 167 | focusing the warning only in those moments and locations of high risk | 167 | focusing the warning only in those moments and locations of high risk | ||
| 168 | of AVC. Thus, one of the main characteristics that we can exploit to | 168 | of AVC. Thus, one of the main characteristics that we can exploit to | ||
| 169 | deal with the AVC problematic is that they are not randomly | 169 | deal with the AVC problematic is that they are not randomly | ||
| 170 | distributed either the space or time. There are important temporal | 170 | distributed either the space or time. There are important temporal | ||
| 171 | changes across the seasons, within the day or within other facts as | 171 | changes across the seasons, within the day or within other facts as | ||
| 172 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | 172 | moon phases. Moreover, AVC commonly concentrate in certain landscapes | ||
| 173 | and habitats. Hence, it is possible to model the spatio-temporal | 173 | and habitats. Hence, it is possible to model the spatio-temporal | ||
| 174 | probability of AVC occurrence with a road network. We have obtained | 174 | probability of AVC occurrence with a road network. We have obtained | ||
| 175 | the model for AVC in Castile and Leon region (NW Spain). The resultant | 175 | the model for AVC in Castile and Leon region (NW Spain). The resultant | ||
| 176 | spatio-temporal model can be implemented in an app for smartphones or | 176 | spatio-temporal model can be implemented in an app for smartphones or | ||
| 177 | incorporated easily to a GPS vehicle navigation system, coupling it | 177 | incorporated easily to a GPS vehicle navigation system, coupling it | ||
| 178 | with the positioning system, the calendar and the clock of the device. | 178 | with the positioning system, the calendar and the clock of the device. | ||
| 179 | The result is an application that shows at real-time the probability | 179 | The result is an application that shows at real-time the probability | ||
| 180 | of AVC considering the vehicle positioning. Al alarm alerts the driver | 180 | of AVC considering the vehicle positioning. Al alarm alerts the driver | ||
| 181 | only when the risk of AVC is high, this is, when the driver passes | 181 | only when the risk of AVC is high, this is, when the driver passes | ||
| 182 | through a road segment with high probability of AVC occurrence just in | 182 | through a road segment with high probability of AVC occurrence just in | ||
| 183 | a period of time (month, hour, moon phase, etc.) given to AVC." | 183 | a period of time (month, hour, moon phase, etc.) given to AVC." | ||
| 184 | }, | 184 | }, | ||
| 185 | "num_resources": 1, | 185 | "num_resources": 1, | ||
| 186 | "num_tags": 2, | 186 | "num_tags": 2, | ||
| 187 | "organization": { | 187 | "organization": { | ||
| 188 | "approval_status": "approved", | 188 | "approval_status": "approved", | ||
| 189 | "created": "2026-06-23T14:36:08.942021", | 189 | "created": "2026-06-23T14:36:08.942021", | ||
| 190 | "description": "", | 190 | "description": "", | ||
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| 192 | "image_url": "", | 192 | "image_url": "", | ||
| 193 | "is_organization": true, | 193 | "is_organization": true, | ||
| 194 | "name": "iepnb", | 194 | "name": "iepnb", | ||
| 195 | "state": "active", | 195 | "state": "active", | ||
| 196 | "title": "", | 196 | "title": "", | ||
| 197 | "type": "organization" | 197 | "type": "organization" | ||
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| 199 | "owner_org": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | 199 | "owner_org": "bca483f7-26e2-4ed8-99e8-65f5b3c7a26e", | ||
| 200 | "private": false, | 200 | "private": false, | ||
| 201 | "provenance": { | 201 | "provenance": { | ||
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| 203 | "es": "" | 203 | "es": "" | ||
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| 205 | "publisher": [ | 205 | "publisher": [ | ||
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| 207 | "email": "buzon-bdatos@miteco.es", | 207 | "email": "buzon-bdatos@miteco.es", | ||
| 208 | "name": "\u00c1rea de Banco de Datos de la Naturaleza. | 208 | "name": "\u00c1rea de Banco de Datos de la Naturaleza. | ||
| 209 | Direcci\u00f3n General Biodiversidad, Bosques y Desertificaci\u00f3n. | 209 | Direcci\u00f3n General Biodiversidad, Bosques y Desertificaci\u00f3n. | ||
| 210 | Ministerio para la Transici\u00f3n Ecol\u00f3gica y el Reto | 210 | Ministerio para la Transici\u00f3n Ecol\u00f3gica y el Reto | ||
| 211 | Demogr\u00e1fico", | 211 | Demogr\u00e1fico", | ||
| 212 | "type": "http://purl.org/adms/publishertype/NationalAuthority", | 212 | "type": "http://purl.org/adms/publishertype/NationalAuthority", | ||
| 213 | "uri": "https://iepnb.es/catalogo/organization/iepnb", | 213 | "uri": "https://iepnb.es/catalogo/organization/iepnb", | ||
| 214 | "url": "https://www.miteco.gob.es/" | 214 | "url": "https://www.miteco.gob.es/" | ||
| 215 | } | 215 | } | ||
| 216 | ], | 216 | ], | ||
| 217 | "publisher_email": "buzon-bdatos@miteco.es", | 217 | "publisher_email": "buzon-bdatos@miteco.es", | ||
| 218 | "publisher_name": "\u00c1rea de Banco de Datos de la Naturaleza. | 218 | "publisher_name": "\u00c1rea de Banco de Datos de la Naturaleza. | ||
| 219 | Direcci\u00f3n General Biodiversidad, Bosques y Desertificaci\u00f3n. | 219 | Direcci\u00f3n General Biodiversidad, Bosques y Desertificaci\u00f3n. | ||
| 220 | Ministerio para la Transici\u00f3n Ecol\u00f3gica y el Reto | 220 | Ministerio para la Transici\u00f3n Ecol\u00f3gica y el Reto | ||
| 221 | Demogr\u00e1fico", | 221 | Demogr\u00e1fico", | ||
| 222 | "publisher_type": | 222 | "publisher_type": | ||
| 223 | "http://purl.org/adms/publishertype/NationalAuthority", | 223 | "http://purl.org/adms/publishertype/NationalAuthority", | ||
| 224 | "publisher_uri": "https://iepnb.es/catalogo/organization/iepnb", | 224 | "publisher_uri": "https://iepnb.es/catalogo/organization/iepnb", | ||
| 225 | "publisher_url": "https://www.miteco.gob.es/", | 225 | "publisher_url": "https://www.miteco.gob.es/", | ||
| 226 | "purpose": { | 226 | "purpose": { | ||
| 227 | "en": "", | 227 | "en": "", | ||
| 228 | "es": "" | 228 | "es": "" | ||
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