Countywide layer which divides the County of Los Angeles into 11 unique areas for planning purposes of the unincorporated areas. This layer is referred to as 'DRP Planning Areas.'The General Plan provides goals and policies to achieve countywide planning objectives for the unincorporated areas, and serves as the foundation for all community-based plans, such as area plans, community plans, and coastal land use plans. Area plans focus on land use and policy issues that are specific to the Planning Area. Community plans cover smaller geographic areas within the Planning Area, and address neighborhood and/or community-level policy issues. Coastal land use plans are components of local coastal programs, and regulate land use and establish policies to guide development in the coastal zone. Please refer to the Planning Areas Framework chapter in the General Plan here.UPDATED: 6/20/24 - following the adoption of the East San Gabriel Valley Area Plan, the boundary between this planning area and the West San Gabriel Valley was modified to include three new unincorporated communities (North Whittier, Pellissier Village, and South El Monte).NEED MORE FUNCTIONALITY? If you are looking for more layers or advanced tools and functionality, then try our suite of GIS Web Mapping Applications.

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability.”This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in the study area or near it, at the time of the analysis of the issues. The data on the issues represent a photograph (figential and not exhaustive) of the property and of the people exposed to hazards at the time of the development of the risk prevention plan. This data is not updated after approval of the RPP. In practice they are no longer used: the issues are recalculated as necessary with up-to-date data sources.

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability.”This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in the study area or near it, at the time of the analysis of the issues. The data on the issues represent a photograph (figential and not exhaustive) of the property and of the people exposed to hazards at the time of the development of the risk prevention plan. This data is not updated after approval of the RPP. In practice they are no longer used: the issues are recalculated as necessary with up-to-date data sources.

The Trust for Public Land's Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city’s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connecting, Cooling, Absorbing, and Protecting.Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure3 = Medium Priority for Green Infrastructure0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.

As part of THEIA (the French Data and Services center for continental surfaces) CIRAD's TETIS research unit is developing an automated mapping method based on the Moringa chain that minimizes interactions with users by automating most image analysis and processing. The methodology uses jointly a Very High Spatial Resolution image (Spot6/7 or Pleiades) and one or more time series of High Spatial Resolution optical images such as Sentinel-2 and Landsat-8 for a classification combining segmentation and object classification (use of the Random Forest algorithm) driven by a learning database constituted from in situ collection and photo-interpretation. The land use maps are produced as part of the GABIR project (Gestion Agricole des Biomasses à l'échelle de l'Ile de la Réunion) and are all distributed on CIRAD's spatial data catalogue in Réunion: http://aware.cirad.fr/ This Dataverse entry concerns the maps produced, for the year 2017, using a mosaic of Pleiades images to calculate segmentation (extraction of homogeneous objects from the image). We use a field database with a nested nomenclature with 3 levels of accuracy allowing us to produce a classification by level. The most detailed level distinguishing crop types has an overall accuracy of 86% and a Kappa index of 0.85. Level 2, distinguishing crop groups, has an overall accuracy of 92% and a Kappa index of 0.90. Level 1, distinguishing major land use groups, has an overall accuracy of 97% and a Kappa index of 0.94. A detailed sheet presenting the validation method and results is available for download. Dans le cadre du Centre d’Expertise Scientifique Occupation des Sols de THEIA, l’UMR TETIS du CIRAD développe une méthode de cartographie automatisée fondée sur la chaine Moringa qui minimise les interactions avec les utilisateurs par l’automatisation de la plupart des processus d’analyse et de traitement des images. La méthodologie utilise conjointement une image à Très Haute Résolution Spatiale (Spot6/7 ou Pléiades) et une ou plusieurs séries temporelles d’images optiques à Haute Résolution Spatiale type Sentinel-2 et Landsat-8 pour une classification combinant segmentation et classification objet (utilisation de l’algorithme Random Forest) entrainée par une base de données d’apprentissage constituée à partir de collecte in situ et de photo-interprétation. Les cartes d'occupation du sol sont réalisées dans le cadre du projet GABIR (Gestion Agricole des Biomasses à l’échelle de l'Ile de la Réunion) et sont toutes diffusées sur le catalogue de données spatiales du Cirad à la Réunion : http://aware.cirad.fr/ Cette fiche du Dataverse concerne les cartes produites, pour l'année 2017, en utilisant une mosaïque d'images Pléiades pour calculer la segmentation (extraction d'objets homogènes à partir de l'image). Nous utilisons une base de données terrain ayant une nomenclature emboitée avec 3 niveaux de précision nous permettant de produire une classification par niveau. Le niveau le plus détaillé distinguant les types de cultures présente une précision globale de 86% et un indice de Kappa est de 0,85. Le niveau 2, distinguant les groupes de cultures présente une précision globale de 92% et un indice de Kappa est de 0,90. Le niveau 1, distinguant les grands groupes d'occupation du sol présente une précision globale de 97% et un indice de Kappa est de 0,94. Une fiche détaillée présentant la méthode et les résultats de validation est téléchargeable.

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability”. This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in or near the study area, at the time of the analysis of the issues. The data on issues represent a (figible and non-exhaustive) photograph of assets and individuals exposed to hazards at the time of the development of the risk prevention plan. This data is not updated after approval of the RPP. In practice they are no longer used: the issues are recalculated as necessary with up-to-date data sources.

Layer description: In Luxembourg, there are a number of (inner-)urban green spaces that transport their cool air into the built environment at night. These so-called park winds, i.e. thermally induced balancing currents from an enclosed green space, occur on larger green spaces that are embedded in a significantly warmer environment. The winds emanating from the respective green spaces flow in almost all directions and extensively ventilate the surrounding built-up area. Most of these green spaces are also located on hills, so that the resulting surface winds are further intensified by the relief. Explanation: The present geodata are taken from the regional climate analysis of Luxembourg (GEO-NET & LIST 2021) which was published with the report « KLIMAÖKOLOGISCHE SITUATION IN LUXEMBURG“ - Modellbasierte regionale Klimaanalyse / (La situation au Luxembourg en matière d’écologie climatique) » by the Administration for Environment. Source: -> https://environnement.public.lu/fr/klima-an-energie/changement-climatique/klimaanalyse.html -> https://data.public.lu/fr/datasets/klimaokologische-situation-in-luxemburg-la-situation-au-luxembourg-en-matiere-decologie-climatique/ Abstracts: The Luxembourg regional climate, which is formed during a low-exchange radiative weather pattern in summer, was investigated using high-resolution computer-based modelling. In total, the model area is described with 8,272,693 grid cells, with information on terrain height, land use, structural height and degree of sealing stored for each grid cell. The urban climate model FITNAH-3D according to Groß (1992) forms the basic framework for the modelling. The input data and model results are based on a horizontal spatial resolution of 25 m x 25 m. The model results are presented in maps. The model results are presented in cartographic representations of the nocturnal temperature field, the nocturnal cold air flow field (4 a.m. in each case) and the thermal load during the day (2 p.m.) and concretised in the form of a climate analysis map. The main product of the work process is a planning recommendation map with an associated catalogue of measures. On the one hand, the map makes visible the graduated need for action to improve thermal comfort in summer in all living/working and recreational areas (“load area”) of the population in Luxembourg. On the other hand, the planning recommendation map also assigns a value to all green and open spaces in the country ("compensation area") with regard to the climate-ecological functions they provide. Notes: - The geodata are only to be used in the context of the specific considerations of the above-mentioned report (e.g.: basic data as of 2018, specific meteorological framework conditions). - The composition of the layers is based on the corresponding maps from the above-mentioned report. Even though these layers can be combined with any other layers from other thematic areas in the geoportal, it should be noted that these representations can easily lead to misinterpretations. - Detailed explanations of this layer and the modelling methodology can be found in the sources mentioned above. - The assessments of the planning recommendation map are based on the climate-ecological functions without taking into account the concerns of other sectoral plans, i.e. the planning recommendation maps represent weighting material obtained from a climate perspective.

Dates: Tuesday, August 7, 2018 to Thursday, August 16, 2018Optical satellite remote sensing depends on cloudless, well-illuminated areas to produce quality data. This is especially problematic for collecting data during nighttime or when there is cloud cover. Radar is an ideal sensor because of its ability to “see” the surface through clouds or regardless of day or night conditions. In addition, the radar signal can penetrate through the vegetation canopy and provide information about conditions underneath, such as whether there is flooding. Also, techniques such as interferometry can track surface deformation on the order of centimeters, such as displacement caused by earthquakes.This webinar series builds on ARSET's previous webinar: Introduction to Synthetic Aperture Radar. The training will focus on different techniques such as time-series, polarimetry, and interferometry for mapping and monitoring disasters, water and land cover applications such as deforestation, crops, flooding, and earthquakes.La teledetección satelital óptica depende de áreas sin nubes y bien iluminadas para producir datos de calidad. Esto es especialmente problemático para la recolección de datos durante la noche o cuando hay cobertura nubosa. El radar es un sensor ideal debido a su habilidad de “ver” la superficie a través de las nubes o independientemente si es de día o de noche. Además, la señal de radar puede penetrar a través del dosel de vegetación y proporcionar información sobre las condiciones en la superficie, como por ejemplo si el área esta inundada. Las técnicas como la interferometría pueden detectar deformación en la superficie en escala de centímetros, como por ejemplo el desplazamiento causado por terremotos.Esta serie en línea tiene como base la capacitación ARSET: Introducción al Radar de Apertura Sintética. Esta capacitación se enfocará en diferentes técnicas tales como series temporales, polarimetría e interferometría para el mapeo y monitoreo de aplicaciones relacionadas a desastres y cobertura terrestre como la deforestación, los cultivos, las inundaciones y los terremotos.SOURCE: https://arset.gsfc.nasa.gov/disasters/webinars/advanced-SAR-18List of Relevant Tools & Data Portals/Lista de Herramientas Relevantes y Portales de DatosLearning Objectives: By the end of this training, attendees will be able to:use SAR data to map deforestation, floods, crop growth, and surface deformation as a result of an earthquakeObjetivos de Aprendizaje:Al concluir esta capacitación, los(las) participantes podrán:utilizar datos SAR para mapear la deforestación, inundaciónes, cultivos y desplazamiento en la superficie como resultado de un terremotoCourse Format: Four, two-hour webinarsFormato del CursoCuatro sesiones de dos horas cada unaPrerequisites: Complete Introduction to Synthetic Aperture Radar, or have equivalent knowledgeAttendees that do not complete the prerequisite may not be adequately prepared for this trainingPrerrequisitosCompletar la capacitación Introducción al Radar de Apertura Sintética o tener el conocimiento equivalenteAquellos participantes que no cumplan con los prerrequisitos podrán estar insuficientemente preparados para esta capacitación.Audience: Remote sensing users from local, regional, state, federal, and international organizations interested in using SAR for terrestrial applications such as inundation mapping, land cover land use change studies, and surface deformation for volcanic and earthquake activity.ParticipantesUsuarios de la teledetección de organizaciones locales, regionales, estatales, federales e internacionales interesados en utilizar SAR para aplicaciones terrestres como el mapeo de inundaciones, estudios de cambios en la cobertura terrestre y el uso del suelo y deformación superficial para actividad volcánica y terremotos.Session OneThis session will cover synthetic aperture radar (SAR) applications for mapping land cover and land cover change, including deforestation. We will address the challenges encountered when mapping these types of applications, and how to best address them. View the Recording »Presentation Slides »Primera Sesión: 7 de agostoEsta sesión cubrirá aplicaciones de radar de apertura sintética (SAR por sus siglas en inglés) para el mapeo de la cobertura terrestre y sus cambios, incluyendo la deforestacion. Abordaremos los retos que enfrentamos al mapear este tipo de aplicaciones y la mejor manera de superarlos.Ver grabación »Diapositivas de la Presentación » Session TwoThis session will cover using SAR for mapping flooded areas and flood dynamics in natural and urban environments. View the Recording »Presentation Slides »Segunda Sesión: 9 de agostoEsta sesión cubrirá el uso de SAR para el mapeo de áreas inundadas y la dinámica de inundaciones en ambientes naturales y urbanos.Ver grabación »Diapositivas de la Presentación »Session ThreeThis session will cover using cover using SAR for mapping crop growth.View the Recording »Presentation Slides »Tercera Sesión: 14 de agostoEsta sesión cubrirá el uso de SAR para el mapeo de el crecimiento de cultivos.Ver grabación »Diapositivas de la Presentación » Session FourThis session will cover using interferometric SAR to map surface deformation related to earthquakes.View the Recording »Presentation Slides »Sesión Cuatro: Agosto 16Esta sesión cubrirá el uso de SAR interferométrico para mapear deformación en la superficie terrestre relacionada con terremotos. Ver grabación »Diapositivas de la Presentación » Application Area: DisastersAvailable Languages: EnglishSpanishInstruments/Missions: UAVSARSentinelNISARKeywords: FloodingLand-Cover and Land-Use Change (LCLUC)Satellite ImageryTools

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability”. This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in or near the study area, at the time of the analysis of the issues. The data on issues represent a (figible and non-exhaustive) photograph of assets and individuals exposed to hazards at the time of the development of the risk prevention plan. This data is not updated after approval of the RPP. In practice they are no longer used: the issues are recalculated as necessary with up-to-date data sources.

This is SCAG 2019 Regional Land Use dataset developed for the final 2024 Connect SoCal, the 2024-2050 Regional Transportation Plan/Sustainable Communities Strategy (RTP/SCS), including general plan land use, specific plan land use, zoning code, and existing land use at parcel-level (approximately five million parcels) for 197 local jurisdictions in the SCAG region. The regional land use dataset is developed (1) to aid in SCAG’s regional transportation planning, scenario planning and growth forecasting, (2) facilitate policy discussion on various planning issues, and (3) enhance information database to better serve SCAG member jurisdictions, research institutes, universities, developers, general public, etc. It is the most frequently and widely utilized SCAG geospatial data. From late 2019 to early 2020, SCAG staff obtained the 2019 parcel boundary GIS file and tax roll property information from county assessor’s offices. After months of data standardization and clean-up process, SCAG staff released the 2019 parcel boundary GIS files along with the 2019 Annual Land Use dataset in February 2021. In December 2021, SCAG staff successfully developed the preliminary dataset of the 2019 regional land use data and released the draft SCAG Data/Map Book in May 2022. The preliminary land use data was reviewed by local jurisdictions during the Local Data Exchange (LDX) process for Connect SoCal 2024. As a part of the final 2019 regional land use data development process, SCAG staff made every effort to review the local jurisdictions’ inputs and comments and incorporated any updates to the regional land use datasets. The products of this project has been used as one of the key elements for Connect SoCal 2024 plan development, growth forecasting, scenario planning, and SCAG’s policy discussion on various planning issues, as well as Connect SoCal key growth strategy analysis.Note: This dataset is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Users should consult with each local jurisdiction directly to obtain the official land use information.2019 SCAG Land Use Codes: LegendLand Use Description Single Family Residential1110 Single Family Residential 1111 High Density Single Family Residential (9 or more DUs/ac) 1112 Medium Density Single Family Residential (3-8 DUs/ac) 1113 Low Density Single Family Residential (2 or less DUs/ac)Multi-Family Residential1120 Multi-Family Residential 1121 Mixed Multi-Family Residential1122 Duplexes, Triplexes and 2- or 3-Unit Condominiums and Townhouses1123 Low-Rise Apartments, Condominiums, and Townhouses1124 Medium-Rise Apartments and Condominiums1125 High-Rise Apartments and CondominiumsMobile Homes and Trailer Parks1130 Mobile Homes and Trailer Parks1131 Trailer Parks and Mobile Home Courts, High-Density1132 Mobile Home Courts and Subdivisions, Low-DensityMixed Residential1140 Mixed Residential1100 ResidentialRural Residential 1150 Rural ResidentialGeneral Office1210 General Office Use 1211 Low- and Medium-Rise Major Office Use 1212 High-Rise Major Office Use 1213 SkyscrapersCommercial and Services1200 Commercial and Services1220 Retail Stores and Commercial Services 1221 Regional Shopping Center 1222 Retail Centers (Non-Strip With Contiguous Interconnected Off-Street Parking) 1223 Retail Strip Development1230 Other Commercial 1231 Commercial Storage 1232 Commercial Recreation 1233 Hotels and MotelsFacilities1240 Public Facilities1241 Government Offices1242 Police and Sheriff Stations1243 Fire Stations1244 Major Medical Health Care Facilities1245 Religious Facilities1246 Other Public Facilities1247 Public Parking Facilities1250 Special Use Facilities1251 Correctional Facilities1252 Special Care Facilities1253 Other Special Use FacilitiesEducation1260 Educational Institutions1261 Pre-Schools/Day Care Centers1262 Elementary Schools1263 Junior or Intermediate High Schools1264 Senior High Schools1265 Colleges and Universities1266 Trade Schools and Professional Training FacilitiesMilitary Installations1270 Military Installations1271 Base (Built-up Area)1272 Vacant Area1273 Air Field1274 Former Base (Built-up Area)1275 Former Base Vacant Area1276 Former Base Air FieldIndustrial1300 Industrial 1310 Light Industrial1311 Manufacturing, Assembly, and Industrial Services1312 Motion Picture and Television Studio Lots1313 Packing Houses and Grain Elevators1314 Research and Development1320 Heavy Industrial1321 Manufacturing1322 Petroleum Refining and Processing1323 Open Storage1324 Major Metal Processing1325 Chemical Processing1330 Extraction1331 Mineral Extraction - Other Than Oil and Gas1332 Mineral Extraction - Oil and Gas1340 Wholesaling and WarehousingTransportation, Communications, and Utilities1400 Transportation, Communications, and Utilities 1410 Transportation1411 Airports1412 Railroads1413 Freeways and Major Roads1414 Park-and-Ride Lots1415 Bus Terminals and Yards1416 Truck Terminals1417 Harbor Facilities1418 Navigation Aids1420 Communication Facilities1430 Utility Facilities1431 Electrical Power Facilities1432 Solid Waste Disposal Facilities1433 Liquid Waste Disposal Facilities1434 Water Storage Facilities1435 Natural Gas and Petroleum Facilities1436 Water Transfer Facilities 1437 Improved Flood Waterways and Structures1438 Mixed Utilities1440 Maintenance Yards1441 Bus Yards1442 Rail Yards1450 Mixed Transportation1460 Mixed Transportation and UtilityMixed Commercial and Industrial1500 Mixed Commercial and IndustrialMixed Residential and Commercial1600 Mixed Residential and Commercial 1610 Residential-Oriented Residential/Commercial Mixed Use 1620 Commercial-Oriented Residential/Commercial Mixed UseOpen Space and Recreation1800 Open Space and Recreation 1810 Golf Courses 1820 Local Parks and Recreation 1830 Regional Parks and Recreation 1840 Cemeteries 1850 Wildlife Preserves and Sanctuaries 1860 Specimen Gardens and Arboreta 1870 Beach Parks 1880 Other Open Space and Recreation 1890 Off-Street TrailsAgriculture2000 Agriculture2100 Cropland and Improved Pasture Land2110 Irrigated Cropland and Improved Pasture Land2120 Non-Irrigated Cropland and Improved Pasture Land2200 Orchards and Vineyards2300 Nurseries2400 Dairy, Intensive Livestock, and Associated Facilities2500 Poultry Operations2600 Other Agriculture2700 Horse RanchesVacant3000 Vacant3100 Vacant Undifferentiated3200 Abandoned Orchards and Vineyards3300 Vacant With Limited Improvements3400 Beaches (Vacant)1900 Urban VacantWater4000 Water4100 Water, Undifferentiated4200 Harbor Water Facilities4300 Marina Water Facilities4400 Water Within a Military Installation4500 Area of Inundation (High Water)Specific Plan7777 Specific PlanUnder Construction1700 Under ConstructionUndevelopable or Protected Land8888 Undevelopable or Protected LandUnknown9999 Unknown

Exports du découpage administratif français au niveau communal (contours des communes) issu d'OpenStreetMap produit dans sa grande majorité à partir du cadastre. Ces données sont issues du crowdsourcing effectué par les contributeurs au projet OpenStreetMap et sont sous licence ODbL qui impose un partage à l'identique et la mention obligatoire d'attribution doit être "© les contributeurs d'OpenStreetMap sous licence ODbL" conformément à http://osm.org/copyright Un export automatique quotidien au format shapefile est disponible, ainsi qu'un second export avec des géométries allégées et vérifiées topologiquement (pas de chevauchement). Descriptif du contenu des fichiers "communes" Origine Les données proviennent de la base de données cartographiques OpenStreetMap. Celles-ci ont été constituées à partir du cadastre mis à disposition par la DGFiP sur cadastre.gouv.fr. En complément sur Mayotte où le cadastre n'est pas disponible sur cadastre.gouv.fr, ce sont les limites du GEOFLA de l'IGN qui ont été utilisées ainsi que le tracé des côtes à partir des images aériennes de Bing. Plus d'infos: http://prev.openstreetmap.fr/36680-communes Format Ces fichiers sont proposés au format shapefile, en projection WGS84 avec plusieurs niveaux de détails: simplification à 5m simplification à 50m simplification à 100m La topologie est conservée lors du processus de simplification (cf: http://prev.openstreetmap.fr/blogs/cquest/limites-administratives-simplifiees) Contenu Ces fichiers contiennent l'ensemble des communes françaises, y compris les DOM, Mayotte et Saint-Pierre-et-Miquelon. Pour Paris, Lyon, Marseille, ce sont les limites d'arrondissements qui sont fournies à la place des limites de communes. Pour chaque commune ou arrondissement, les attributs suivants sont ajoutés: insee: code INSEE à 5 caractères de la commune nom: nom de la commune (tel que figurant dans OpenStreetMap, si possible conforme aux règles de toponymie) wikipedia: entrée wikipédia (code langue suivi du nom de l'article) surf_ha : surface en hectares de la commune Pour les communes de Bois-Guillaume et Bihorel, les données du GEOFLA ont été corrigées manuellement suite à l'annulation de la fusion le 1er Janvier 2014. Historique 19-12-2013 : première génération du fichier, basé sur le découpage communal OSM au 19-12-2013 20-12-2013 : correction de 2 erreurs (un cimetière militaire était exclu du territoire par erreur, la géométrie de la commune de Landerneau manquait) 06-03-2014 : troisième génération du fichier, basé sur le découpage communal OSM au 06-03-2014 29-06-2014 : remplacement des limites de Paris, Lyon, Marseille par les limites de leurs arrondissements municipaux. 30-06-2014 : ajout de la version "enrichie" 10-10-2014 : ajout d'un export CSV de la version "enrichie" 01-01-2015 : quatrième version du fichier, prenant en compte les fusions de communes au 1/1/2015 ainsi que les communes ayant changé de nom le 3/12/2014. Pour les communes fusionnées et à titre temporaire (attente de publication du COG 2015) le code INSEE conservé est celui de la commune où le chef-lieu est fixé par le JORF. 19-01-2016 : cinquième version du fichier, prenant en compte les fusions de communes au 19/1/2016 ainsi que les changements intervenus en 2015 (nouveaux noms, etc). Voir ce jeu de données pour plus de détail sur les fusions et communes nouvelles. Les arrondissements municipaux (Paris, Lyon, Marseille) sont disponibles dans un fichier séparé avec les communes déléguées issues de la création des communes nouvelles. 11-01-2017 : version prenant en compte les 181 fusions de communes au 1/1/2017 ainsi que les changements intervenus en 2016 (nouveaux noms, fusions, etc). Voir ce jeu de données pour plus de détail sur les fusions et communes nouvelles. 01-01-2018 : version comprenant les 33 fusions de communes au 1/1/2018 et la fusion au 1/7/2017, ainsi que les changements de noms intervenus en 2017. St-Pierre et Miquelon sont dans le fichier des communes des Collectivités d'Outre-Mer. 26-02-2018 : version au 1/1/2018 complétée par 3 communes nouvelles (Aubessagne, Blancs-Coteaux, Geiswiller-Zœbersdorf) soit au total 36 fusions. 01-01-2019 : version au 1/1/2019 comprenant 232 communes nouvelles répertoriées sur wikipédia au 01/01/2019 11-02-2019 : intégration des communes nouvelles répertoriées par l'INSEE 07-03-2019 : correction du code INSEE de La Léchère (73187) 01-01-2021 : Fusion des communes au 1/1/2021 Versions précédentes disponibles sur: http://osm13.openstreetmap.fr/~cquest/openfla/export/ Pour toute question concernant ces exports, vous pouvez contacter exports@openstreetmap.fr Voir aussi : Liste des adjacences des communes françaises Contours des EPCI 2014 et Contours des EPCI 2013 Contours des arrondissements français Contours des départements français et Cartes SVG des départements Contours de régions françaises Contours des futures régions

The objective of the regulatory zoning phase is to define homogeneous areas in terms of prohibitions, prescriptions, recommendations or land use, both for new projects and for existing assets. The principles of this zoning are based in particular on a confrontation between the different levels of hazards previously identified and the assessment of existing and future issues characterising the surface. The identification of these homogeneous areas results in the development of a mapping of the regulatory zoning of the PPRN GT... Directly related to this zoning, a regulation must be established. Its purpose is to set out, in a clear and operational manner, the regulatory measures that apply to each of the Regulatory Areas. The scale of use of the regulatory zoning is that of 1/10 000 and exploitation on a smaller cadastral scale (1/5000 or 1/2000) is not recommended. The accuracy of the initial data therefore presents uncertainty about its contours in the order of 10 metres. Genealogy: The boundaries of a restricted area are shown on the graphical documents of the RPP. Regulatory limits are generally set on natural phenomena, which do not follow cadastral or administrative boundaries. A PPR determines the boundaries of the different restricted areas based on the calculated right-of-way of the site’s hazardous phenomena. Some PPRs may sometimes contain regulations associated with linear or point configurations (cavitates, runoff axis...). The linear and point graphic primitives are to be used in these cases respectively.

La carte de la France métropolitaine (hors Corse) des stocks de carbone dans les sols a été préparée par l’INRA dans le cadre d’un exercice mondial piloté par le Partenariat Mondial sur les Sols hébergé par l’Organisation des Nations-Unies pour l’alimentation et l’agriculture, la FAO. La carte ainsi produite, en suivant les spécifications décidées par cette instance, a été intégrée à la carte mondiale des stocks de carbone. Elle exploite une précédente production réalisée dans le cadre du programme Global Soil Map (Mulder et al. 2016) et résulte d’un travail de cartographie numérique par modélisation réalisé à partir des données ponctuelles issues des deux programmes nationaux IGCS et RMQS du GIS Sol. La carte transmise à la FAO estime sur une grille de 1km de résolution les stocks de carbone sur 30 cm. Elle fournit des indications précieuses quant à la distribution spatiale et la variabilité des stocks de carbone dans les sols français, avec toutefois des zones où les estimations présentent de forts niveaux d’incertitude, notamment en région montagneuse. Conformément aux spécifications du programme Global Soil Map (Arrouays et al., 2014), ces incertitudes sont symbolisées par des cartes du stock de carbone prenant en compte la borne inférieure et supérieure de l'intervalle de confiance. Ces cartes comprenant les intervalles de confiance, ainsi que la carte des stocks de carbone intégrée à la FAO sont disponibles en visualisation et en téléchargement ci-dessous. IMPORTANT : en cas d’utilisation de ce jeu de données, il est fortement recommandé de prendre en compte les incertitudes fournies (cartes d’intervalles de confiance). Ce travail confirme les précédentes publications nationales puisque les stocks les plus faibles sont observés en Languedoc-Roussillon (région fortement viticole et caractérisée par un climat chaud et des sols peu épais) et dans quelques zones de culture très intensive (Beauce Chartraine, Nord). Les stocks de carbone faibles à moyens (40-50 t/ha) sont caractéristiques des sols des grandes plaines de culture intensive de France ainsi que des sols limoneux comme par exemple le grand Bassin parisien, une partie du Bassin aquitain, le Toulousain et le sillon rhodanien. Les stocks de carbone moyennement élevés (50-70 t/ha) sont caractéristiques des grandes régions forestières ou fourragères de France (Bretagne, Est, Massif central, Normandie) et les stocks de carbone les plus élevés correspondent à des situations climatiques (sols situés en altitude), minéralogiques (sols volcaniques du Massif central) ou hydriques extrêmes (marais de l’Ouest, delta du Rhône).

The Risk Prevention Plans (PPR) were established by the Act of 2 February 1995 on strengthening the protection of the environment. They are the key instrument of the State in the field of risk prevention. Their objective is to monitor development in areas exposed to a major risk. The PPRs are approved by the Prefect and carried out by the Direction des Départementale des Territoires et de la Mer des Bouches-du-Rhône. These plans regulate land use or land use through building prohibitions or requirements on existing or future buildings (constructive provisions, vulnerability reduction work, restrictions on agricultural use or practices, etc.). These plans may be under development (prescribed), implemented in advance or approved. The RPP file contains a presentation note, a regulatory zoning plan and a regulation. Other graphic documents that are useful for understanding the approach (e.g. hazards, issues, etc.) can be attached. Each PPR is identified by a polygon that corresponds to the set of affected municipalities within the scope of the prescription when it is in the prescribed state; and the envelope of restricted areas when it is in the approved state. This geographical table allows to map existing PPRNs on the department. Each PPRN document in the N_DOCUMENT_PPRN geographical table is linked with its GASPAR code in the format “ddd[PREF|DDT|DDTM|DREAL]aaaannnn” (AAAA and NNNN correspond to the reference year and the order number of the associated PPR procedure in GASPAR): 1. its administrative procedure for drawing up (or revising) managed in the GASPAR application, on the one hand, 2. its set of numeric spatial data as described in the metadata sheet N_PPRN_AAAANNNN (#0001495).

A series of geographic data produced for the High Flood Risk Land Flood Directive (TRI) of CAHORS and mapped for reporting purposes for the European Flood Directive.

European Directive 2007/60/EC of 23 October 2007 on the assessment and management of flood risks (OJ L 288, 06-11-2007, p. 27) influences the flood prevention strategy in Europe. It requires the production of flood risk management plans aimed at reducing the negative consequences of flooding on human health, the environment, cultural heritage and economic activity.

The objectives and implementation requirements are set out in the Law of 12 July 2010 on the National Commitment for the Environment (LENE) and the Decree of 2 March 2011. In this context, the primary objective of flood and flood risk mapping for IRRs is to contribute, by homogenising and objectivating knowledge of flood exposure, to the development of flood risk management plans (WRMs). This data set is used to produce flood surface maps and flood risk maps that represent flood hazards and issues at an appropriate scale, respectively. Their objective is to provide quantitative evidence to further assess the vulnerability of a territory for the three levels of probability of flooding (high, medium, low).

For more information:
http://www.occitanie.developpement-durable.gouv.fr/la-mise-en-oeuvre-de-la-directive-inondation-r7292.html