The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. GIS Database 2002-2005: Project Size = 1,898 acres Fort Larned National Historic Site (including the Rut Site) = 705 acres 16 Map Classes 11 Vegetated 5 Non-vegetated Minimum Mapping Unit = ½ hectare is the program standard but this was modified at FOLS to ¼ acre. Total Size = 229 Polygons Average Polygon Size = 8.3 acres Overall Thematic Accuracy = 92% To produce the digital map, a combination of 1:8,500-scale (0.75 meter pixels) color infrared digital ortho-imagery acquired on October 26, 2005 by the Kansas Applied Remote Sensing Program and 1:12,000-scale true color ortho-rectified imagery acquired in 2005 by the U.S. Department of Agriculture - Farm Service Agency’s Aerial Photography Field Office, and all of the GPS referenced ground data were used to interpret the complex patterns of vegetation and land-use. In the end, 16 map units (11 vegetated and 5 land-use) were developed and directly cross-walked or matched to corresponding plant associations and land-use classes. All of the interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases using ArcGIS© software. Draft maps were printed, field tested, reviewed and revised. One hundred and six accuracy assessment (AA) data points were collected in 2006 by KNSHI and used to determine the map’s accuracy. After final revisions, the accuracy assessment revealed an overall thematic accuracy of 92%.

In today’s information age, thematic maps increasingly appear in all kinds of media and publications and many users control the map design process themselves. Due to wider prevalence of data, teaching the principles of thematic cartography is gaining interest. Students need to understand the power of thematic maps to reveal geographic patterns and relations, and should learn how to create convincing maps. In this paper, student maps featuring socio-economic themes for Northern South Africa show how attention can be drawn to information hidden in data. Seven students each prepared a black-and-white traditional thematic map and a coloured infographics-style map, which were later enhanced by a well-trained cartographer. Through these maps, we demonstrate that the power of thematic maps depends on the chosen cartographic representation and that diversity of visualization options matters when telling a story with a map. Discussion of the maps illustrates the relevance and challenge of thematic maps for society, the need to develop map literacy, and the possibility to accommodate new visualization trends, like narrative data visualization, in thematic cartography teaching. The emphasis should be on using multivariate data and allowing infographics characteristics, thus fostering creativity and preparing students for a role in interdisciplinary data journalism teams.

This map draws attention to your thematic content by providing a neutral background with minimal colors, labels, and features. Only key information is represented to provide geographic context, allowing your data to come to the foreground. This light gray map supports any strong colors, creating a visually compelling map graphic which helps your reader see the patterns intended. This map was developed by Esri using HERE data, DeLorme basemap layers, OpenStreetMap contributors, Esri basemap data, and select data from the GIS user community. Worldwide coverage is provided from Level 0 (1:591M scale) through Level 13 (1:72k scale). In North America (Canada, Mexico, United States), Europe, India, South America and Central America, Africa, most of the Middle east, and Australia & New Zealand coverage is provided from Level 14 (1:36k scale) through Level 16 (1:9k scale). For more information on this map, including the terms of use, visit us online.

Abstract: The objective of this work was to develop and provide a free web application able to generate thematic maps. The initiative aims to incorporate the functionalities of the “Software para Definição de Unidades de Manejo” (SDUM) desktop application, which has proven to be suitable for working with thematic maps and management zones, but that was only available for desktop computers. The developed web application was tested with real data from two agricultural fields located in the state of Paraná, Brazil. Thematic maps of soil and plant characteristics relevant to precision agriculture were created through the following interpolation methods: inverse distance, moving average, and nearest neighbor. The obtained results show that the usage of this web tool allows identifying areas with the same behavior toward soil variables, making it possible for the user to have a better and more accurate vision of the area to be worked on and to identify possible causes of variation in productivity. Because it is installed in a server with on-demand features, the software has a satisfactory performance from a functional point of view and can be accessed from any web environment.

Thematic maps about social inequalities can engage audiences, add context to policy debates, and change attitudes toward the issues. The field of communication has long compared the relative persuasiveness of this kind of abstract data versus concrete examples about individuals. While studies have compared the effectiveness of presenting both types of information alongside each other, the line between them is sometimes blurred in data visualization, which can incorporate individuals’ stories in innovative ways. One context in which incorporating examples within thematic maps may help is when discussing the social determinants of health because the complex relationship between individual and community is central to how the determinants influence health, and communication on this can be challenging. In this study, we randomly presented the UK public (N = 389) with maps incorporating varying levels of “exemplification” for three different social determinants: public transport, air pollution, and youth service provision. We tested how this affected engagement, credibility, and perceptions about the issues. Between-group analysis found few significant differences and therefore limited persuasive power. However, within-subject analysis indicated that the maps with individual-centered stories may be more persuasive but only among those less confident in their ability to interpret data visualizations. Maps of social inequalities that incorporate stories about individuals may be more engaging and persuasive to audiences less confident with statistics.In data visualization experiments, researchers should consider analyzing both differences between treatment groups and differences within subjects in their responses to different stimuli. Maps of social inequalities that incorporate stories about individuals may be more engaging and persuasive to audiences less confident with statistics. In data visualization experiments, researchers should consider analyzing both differences between treatment groups and differences within subjects in their responses to different stimuli.

This dataset is obtained from MapBiomas.

Landsat mosaics are used to generate classifications that produce thematic maps of land cover and land use for each year. Within the framework proposed by MapBiomas Amazonía, these maps will be updated whenever improvements are made to the classification algorithm. This classification method is dynamic, with the aim of improving the classification of each typology.

Here you can access annual land cover and land use maps of the Amazon, organized by country, map scale (1:250,000), and year.

Important: When creating a single mosaic or calculating statistics on the maps, you must consider that:

To calculate area, the use of an appropriate metric projection is required.
All data is in GeoTIFF format and uses LZW compression. To obtain class reference codes, visit:
LEGEND CODES – COLLECTION 6.0 Annual maps are combined into a single file with multiple bands, where each band represents one year from the historical series (the first band corresponds to the first year of the series). The international boundaries used by MapBiomas Amazonía are those used by RAISG and may differ from files from other sources.

A map with various base layers to be used as a template for creating thematic maps for the Napa County CWPP online maps. Most layers are from Napa County's online gis data catalog but some layers were derived from public data sources such as Wikipedia and others.

The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000. The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000. The feature class MO_tradizioni_costumi_lin_1 represents the linear elements of local traditions and customs, acquired from the map of local traditions and customs, acquired on a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.

This map is suitable only for the ArcGIS Online Map Viewer. Because of viewer-specific effects, it will not render as designed in Map Viewer Classic or ArcGIS Pro.This map uses a combination of blend modes and effects with imagery, hillshade, and reference layers, to create a muted landcover-tinted natural appearance. It is appropriate for reference mapping, physical/environmental geography themes, or thematic maps where a muted representation of the natural environment provides helpful context.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and nonsoil areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. Note: All Minnesota SSURGO data sets are now in Version 2 format. This format is compatible with NRCS's Soil Data Viewer, a free extension for ArcView 3.x that allows users to more easily create soil-based thematic maps. - For more information about Soil Data Viewer, see http://www.itc.nrcs.usda.gov/soildataviewer/ Also note: This metadata record was created by the Minnesota Land Management Information Center to serve as a generic record for all SSURGO data sets within Minnesota. See the individual county metadata records created by NRCS for county-specific information; these records are included in the data set download files.

Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independently of ArcMap, but output is then limited to a tabular report. The soil survey attribute database associated with the spatial soil map is a complicated database with more than 50 tables. Soil Data Viewer provides users access to soil interpretations and soil properties while shielding them from the complexity of the soil database. Each soil map unit, typically a set of polygons, may contain multiple soil components that have different use and management. Soil Data Viewer makes it easy to compute a single value for a map unit and display results, relieving the user from the burden of querying the database, processing the data and linking to the spatial map. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Resources in this dataset:Resource Title: Soil Data Viewer. File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/home/?cid=nrcs142p2_053620 Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independent of ArcMap, but output is then limited to a tabular report. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Links to download and install Download Soil Data Viewer 6.2 for use with ArcGIS 10.x and Windows XP, Windows 7, Windows 8.x, or Windows 10. Earlier versions are also available.

GISCO (Geographic Information System of the COmmission) is responsible for meeting the European Commission's geographical information needs at three levels: the European Union, its member countries, and its regions.

In addition to creating statistical and other thematic maps, GISCO manages a database of geographical information, and provides related services to the Commission. Its database contains core geographical data covering the whole of Europe, such as administrative boundaries, and thematic geospatial information, such as population grid data. Some data are available for download by the general public and may be used for non-commercial purposes. For further details and information about any forthcoming new or updated datasets, see http://ec.europa.eu/eurostat/web/gisco/geodata.

This metadata refers to the whole content of GISCO reference database extracted in June 2020, which contains both public datasets (also available for the general public through http://ec.europa.eu/eurostat/web/gisco/geodata) and datasets to be used only internally by the EEA (typically, but not only, GISCO datasets at 1:100k). The document GISCO-ConditionsOfUse.pdf provided with the dataset gives information on the copyrighted data sources, the mandatory acknowledgement clauses and re-dissemination rights. The license conditions for EuroGeographic datasets in GISCO are provided in a standalone document "LicenseConditions_EuroGeographics.pdf".

The database is provided in GPKG files, with datasets at scales from 1:60M to 1:100K, with reference years spanning until 2021 (e.g. NUTS 2021). Attribute files are provided in CSV. The database manual, a file with the content of the database, a glossary, and a document with the naming conventions are also provided with the database.

The main updates with respect to the previous version of the full database in the SDI (from Jul. 2018) are the addition of the following datasets: - Administrative boundaries at country level, 2020 (CNTR_2020) - Administrative boundaries at commune level, 2016 (COMM_2016) - Coastline boundaries, 2016 (COAS_2016) - Exclusive Economic Zones, 2016 (EEZ_2016)

- Farm Accountancy Data Network based on NUTS 2016, 2018 (FADN_2018)

             Local Administrative Units, 2018 (LAU_2018)

• Nomenclature of Territorial Units for Statistics, 2021 (NUTS_2021)
• Political regions (NB.: defined by the Committee of the Regions), 2018 (POLREG_2018)
• Pan-European Settlements, 2016 (STLL_2016) and 2018 (STLL_2018)
• Transport Networks (NB.: railway lines, railway stations, roads, road junctions, levelcrossings, ferry routs and custom points), 2019 (TRAN_2019)
• Urban Audit Areas, 2018 (URAU_2018) and 2020 (URAU_2020)

NOTE: This metadata file is only for internal EEA purposes and in no case replaces the official metadata provided by Eurostat. For specific GISCO datasets included in this version there are individual EEA metadata files in the SDI: NUTS_2021 and CNTR_2020. For other GISCO datasets in the SDI, it is recommended to use the version included in this dataset. The original metadata files from Eurostat for the different GISCO datasets are available via ECAS login through the Eurostat metadata portal on https://webgate.ec.europa.eu/inspire-sdi/srv/eng/catalog.search#/home. For the public products metadata can also be downloaded from https://ec.europa.eu/eurostat/web/gisco/geodata. For more information about the full database or any of its datasets, please contact the SDI Team (sdi@eea.europa.eu).

Geospatial Data Pack for Visualization 🗺️

Learn Geographic Mapping with Altair, Vega-Lite and Vega using Curated Datasets

Complete geographic and geophysical data collection for mapping and visualization. This consolidation includes 18 complementary datasets used by 31+ Vega, Vega-Lite, and Altair examples 📊. Perfect for learning geographic visualization techniques including projections, choropleths, point maps, vector fields, and interactive displays.

Source data lives on GitHub and can also be accessed via CDN. The vega-datasets project serves as a common repository for example datasets used across these visualization libraries and related projects.

Why Use This Dataset? 🤔

• Comprehensive Geospatial Types: Explore a variety of core geospatial data models:
  • Vector Data: Includes points (like airports.csv), lines (like londonTubeLines.json), and polygons (like us-10m.json).
  • Raster-like Data: Work with gridded datasets (like windvectors.csv, annual-precip.json).
• Diverse Formats: Gain experience with standard and efficient geospatial formats like GeoJSON (see Table 1, 2, 4), compressed TopoJSON (see Table 1), and plain CSV/TSV (see Table 2, 3, 4) for point data and attribute tables ready for joining.
• Multi-Scale Coverage: Practice visualization across different geographic scales, from global and national (Table 1, 4) down to the city level (Table 1).
• Rich Thematic Mapping: Includes multiple datasets (Table 3) specifically designed for joining attributes to geographic boundaries (like states or counties from Table 1) to create insightful choropleth maps.
• Ready-to-Use & Example-Driven: Cleaned datasets tightly integrated with 31+ official examples (see Appendix) from Altair, Vega-Lite, and Vega, allowing you to immediately practice techniques like projections, point maps, network maps, and interactive displays.
• Python Friendly: Works seamlessly with essential Python libraries like Altair (which can directly read TopoJSON/GeoJSON), Pandas, and GeoPandas, fitting perfectly into the Kaggle notebook environment.

Table of Contents

• Why Use This Dataset?
• Dataset Inventory
• Usage Guide
• Appendix: Geospatial Examples by Technique
• Licenses
• Sources
• Learning Resources

Dataset Inventory 🗂️

This pack includes 18 datasets covering base maps, reference points, statistical data for choropleths, and geophysical data.

1. BASE MAP BOUNDARIES (Topological Data)

2. GEOGRAPHIC REFERENCE POINTS (Point Data) 📍

The Millennium Coral Reef Mapping Project provides thematic maps of coral reefs worldwide at geomorphological scale. Maps were created by photo-interpretation of Landsat 7 and Landsat 8 satellite images. Maps are provided as standard Shapefiles usable in GIS software. The geomorphological classification scheme is hierarchical and includes 5 levels. The GIS products include for each polygon a number of attributes. The 5 level geomorphological attributes are provided (numerical codes or text). The Level 1 corresponds to the differentiation between oceanic and continental reefs. Then from Levels 2 to 5, the higher the level, the more detailed the thematic classification is. Other binary attributes specify for each polygon if it belongs to terrestrial area (LAND attribute), and sedimentary or hard-bottom reef areas (REEF attribute). Examples and more details on the attributes are provided in the references cited. The products distributed here were created by IRD, in their last version. Shapefiles for 102 atolls of France (in the Pacific and Indian Oceans) as mapped by the Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). The data set provides one zip file per region of interest. Global coral reef mapping project at geomorphological scale using LANDSAT satellite data (L7 and L8). Funded by National Aeronautics and Space Administration, NASA grants NAG5-10908 (University of South Florida, PIs: Franck Muller-Karger and Serge Andréfouët) and CARBON-0000-0257 (NASA, PI: Julie Robinson) from 2001 to 2007. Funded by IRD since 2003 (in kind, PI: Serge Andréfouët).

The feature class MO_geomorphological_later_7 represents the point geomorphological elements acquired from the geomorphological map at a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.

When creating choropleth maps, mapmakers often bin (i.e. group, classify) quantitative data values into groups to help show that certain areas fall within a similar range of values. For instance, a mapmaker may divide counties into groups of high, middle, and low life expectancy (measured in years). It is well known that different binning methods (e.g. natural breaks, quantiles) yield different groupings, meaning the same data can be presented differently depending on how it is divided into bins. To help guide a wide variety of users, we present a new, open-source, web-based, geospatial visualization tool, Exploropleth, that lets users interact with a catalog of established data binning methods, and subsequently compare, customize, and export custom maps. This tool advances the state of the art by providing multiple binning methods in one view and supporting administrative unit reclassification on-the-fly. We interviewed 16 cartographers and geographic information systems (GIS) experts from 13 government organizations, non-government organizations (NGOs), and federal agencies who identified opportunities to integrate Exploropleth into their existing mapmaking workflow, and found that the tool has the potential to educate students as well as mapmakers with varying levels of experience. Exploropleth is open-source and publicly available at https://exploropleth.github.io.

The feature class MO_geolithologica_lin_8 represents the linear geolithological elements acquired from the geolithological map at a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.

The feature class MO_geolithologica_poly_4 represents the geolithological elements of type area — acquired from the geolithological map at a scale of 1:25 000. The maps PTPAAV (Territorial Environmental Country Plan of Area Vasta) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.

Land cover information is critical to scientific, economic, and public policy-making. There is a high demand for accurate and timely land cover information that affects the accuracy of all subsequent applications. The availability of Google Earth Engine (GEE), which derives temporal aggregation methods from time-series images (i.e., the use of metrics such as mean or median), has also enabled optimization of computation time, such as managing large amounts of data to obtain more accurate results. Our objective was to obtain a land cover map for the northwest of the province of Córdoba, Argentina. The study was carried out in rural communities that belong to the departments of Cruz del Eje and Ischilín, northwest of Córdoba, and have different degrees of intervention in the land cover. Sentinel 2 Level 2A images were acquired for the study area. Images available from January 1, 2018, to December 31, 2020, were sampled. To create a thematic map, the median value was calculated for the sample of images from the selected time interval. Finally, the Normalized Difference Vegetation Index (NDVI) was calculated and added to the total bands of the median image. Training polygons were placed there considering the visual features in the median image. The Random Forest algorithm was used as the classification method. To verify the quality of the classified map, a list of 97,753 verification pixels was obtained. In addition, a confusion matrix was created to collect the conflicts that arise between categories, and the precision and kappa coefficient was calculated to define the quality of the map obtained. Image acquisition, preprocessing, and analysis were performed on the Google Earth Engine platform. Thematic maps with eight classes were obtained, with a total area of 719880 ha. The confusion matrix showed an overall precision of 99.26% and a corrected kappa index of 0.99, the classes were correctly classified by the algorithm.

The feature class MO_transformabilita_lin_6 represents the transformability — linear elements acquired from the transformability map for the Municipality of Venafro on a scale of 1:25 000.The maps PTPAAV (Territorial Environmental Country Plan of Vasta Area) are a series of thematic maps drawn up since 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by several groups of technicians, a coordination group which established by circulars the standards to be used for the drafting of plans ranging from the thickness of the graph tip to the type of retino and the nuances to be used, and 8 design groups one for each area, which have created the maps trying to standardise spatial information as much as possible. The paperwork of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic cards related to some areas, the missing ones and in the case of scans not found suitable for georeference, have been scanned. The mapping basis used by the working groups for the creation of PTPAAV maps was the IGM on a scale of 1:25,000.