Alquist-Priolo Earthquake Fault Zoning Act (1972) and the Seismic Hazards Mapping Act (1990) direct the State Geologist to delineate regulatory "Zones of Required Investigation" to reduce the threat to public health and safety and to minimize the loss of life and property posed by earthquake-triggered ground failures. Cities and counties affected by the zones must regulate certain development "projects" within them. These Acts also require sellers of real property (and their agents) within a mapped hazard zone to disclose at the time of sale that the property lies within such a zone.

NOTE: Fault Evaluation Reports are available for those areas covered by a Regulatory Map however there are reports available for areas outside the Regulatory map boundary. For a complete set of maps available for purchase on CD please contact the CGS Library.

Clickable map tool to locate and find information about United States Warehouse Act Licensed WarehousesThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web Page For complete information, please visit https://data.gov.

Produced collectively by tsunami modelers, geologic hazard mapping specialists, and emergency planning scientists from the University of Southern California (USC) Tsunami Research Center, CGS, and Cal OES. The Tsunami Inundation Maps for Emergency Planning cover all low-lying, populated areas along the State’s coastline. Coordinated by Cal OES, these inudation maps are developed for at risk areas to tsunamis in California and represent a combination of the maximum considered tsunamis for each area.

Since the 1960's, the California Geological Survey (CGS) has produced numerous maps that show landslide features and delineate potential slope-stability problem areas. Preparation of these maps has been episodic, often driven by landslide disasters and subsequent legislative mandates. Many CGS landslide maps and related products have been produced for local or state agencies in response to their specific needs. This index includes landslide maps produced over many years and for a variety of purposes. See the description of CGS landslide programs for details of some of the major programs and types of landslides and landslide maps. Landslide reports and maps for the California Geological Survey's Information Warehouse.

Mineral Land Classification studies are produced by the State Geologist as specified by the Surface Mining and Reclamation Act (SMARA, PRC 2710 et seq.) of 1975. To address mineral resource conservation, SMARA mandated a two-phase process called classification-designation. Classification is carried out by the State Geologist and designation is a function of the State Mining and Geology Board. The classification studies contained here evaluate the mineral resources and present this information in the form of Mineral Resource Zones. The objective of the classification-designation process is to ensure, through appropriate local lead agency policies and procedures, that mineral materials will be available when needed and do not become inaccessible as a result of inadequate information during the land-use decision-making process.

The topographic maps (TK) are generated from digital landscape and terrain models as well as the official property cadastre information system ALKIS and visualised according to the nationwide signature catalogue of the presentation editions ‘basemap.de P10’ grid. The TKs are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. They are available as analogue map prints (plots), as raster data and as web services. When using the data, the license conditions must be observed.

The digital topographic maps (DTK) are generated from digital landscape and terrain models as well as the official property cadastre information system ALKIS and visualised according to the nationwide signature catalogue of the presentation editions ‘basemap.de P10’ grid. The DTK are available nationwide and in the uniform geodetic reference system and map projection for the state of Brandenburg. They are available as raster data (coloured/grey) and as web services. When using the data, the license conditions must be observed.

A map showing Asian American historic properties for the Ethnic Heritage tour story map. This map focuses on the historic Chinatowns of Phoenix. This map is featured in the City of Phoenix Historic Preservation Office's Tour Phoenix's Asian American Heritage Story Map.Please visit our story maps at https://www.phoenix.gov/pdd/story-maps.

The International Association of Refrigerated Warehouses (IARW) came into existence in 1891 when a number of conventional warehousemen took on the demands of storing perishable food and soon realized the increased challenge and complexity of operating temperature controlled storage facilities. IARW's goals and activities have broadened considerably over the years. Today, in addition to collecting information and encouraging the exchange of ideas, the association aggressively promotes more efficient distribution services, aids members in adopting new technology, advises members of legislation and regulations affecting the food industry, assists members in complying with U.S. and international regulations, and participates in alliances with industry and international organizations having a common interest in the safe and efficient flow of food products around the world. All active members of IARW are also members and beneficiaries of the work of The World Food Logistics Organization.

The raster dataset consists of a 500 m score grid for the crop storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location.

The location score is achieved by processing sub-model outputs that characterize considered factors for crop warehouse location:

• Supply: Maize.

• Demand: Human population density, Major cities population (national and bordering countries).

• Infrastructure/accessibility: main transportation infrastructure.

• Socio-economic/poverty: Figueroa, Marsicovetere & Peñate (2020).

It consists of an arithmetic weighted sum of normalized grids (0 to 100):

("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (”Poverty” * 0.1) + (“Major Cities Accessibility” * 0.1) + (“Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1).

Data publication: 2022-11-24

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Justeen De Ocampo

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:

1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. https://data.apps.fao.org/catalog/iso/304c21fb-0f5a-44ad-9948-2af6a7144fb5
2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. https://data.apps.fao.org/map/catalog/srv/eng/catalog.search;jsessionid=4AA4D377D0F90E3328ACBDB5C21BFFC6?node=srv#/metadata/0c6be5d1-3a73-4516-953b-dbe2b511d6b3
3. OpenStreetMap.
4. Poverty – Study by Figueroa, W., Marsicovetere, P., & Peñate, M. (2020) based on the results of the XII National Population Census and VII Housing Census of 2018.

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Zipped raster TIF file for Crop Storage Location Score: Maize (Guatemala - ~ 500m)

Analysis of ‘CGS Information Warehouse: Landslide Maps and Reports’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/eb725418-9bb2-4e3f-9515-6967a20ba6b3 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Since the 1960's, the California Geological Survey (CGS) has produced numerous maps that show landslide features and delineate potential slope-stability problem areas. Preparation of these maps has been episodic, often driven by landslide disasters and subsequent legislative mandates. Many CGS landslide maps and related products have been produced for local or state agencies in response to their specific needs.

This index includes landslide maps produced over many years and for a variety of purposes. See the description of CGS landslide programs for details of some of the major programs and types of landslides and landslide maps.

Landslide reports and maps for the California Geological Survey's Information Warehouse.

--- Original source retains full ownership of the source dataset ---

The 3D Integrated Mobile Map market is experiencing robust growth, projected to reach a value of $49,770 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 8.0% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of mobile devices equipped with advanced mapping capabilities, coupled with the rising demand for precise location-based services across various sectors, is fueling market growth. Furthermore, the integration of 3D mapping technology with augmented reality (AR) and virtual reality (VR) applications is opening up new avenues for innovation and creating immersive user experiences. This is particularly evident in sectors like aviation (airlines, airports, and aircraft warehousing) where real-time, accurate 3D maps are crucial for improved navigation, safety, and operational efficiency. The growth is also facilitated by continuous advancements in sensor technologies, data processing capabilities, and the wider availability of high-quality 3D map data. Companies like Betria Interactive, Panasonic, and Rockwell Collins are actively contributing to market growth through their innovative product offerings and strategic partnerships. The market is segmented by type (IFE System, Mobile Terminal) and application (Airport, Airline, Aircraft Warehouse, Others), reflecting the diverse range of applications driving market expansion. Geographic expansion is also a strong contributor, with North America and Asia Pacific expected to be key regional markets. The market's sustained growth trajectory is expected to continue throughout the forecast period, driven by increasing investments in infrastructure development, particularly in smart cities and autonomous vehicles, which heavily rely on precise and detailed 3D mapping. Furthermore, the integration of 3D mobile maps with other technologies, such as the Internet of Things (IoT) and cloud computing, will unlock new opportunities for data analysis and predictive capabilities, further enhancing the market's value proposition. However, challenges such as data security concerns and the high initial investment costs associated with implementing 3D mapping technologies could potentially moderate market growth. Nevertheless, the long-term outlook for the 3D Integrated Mobile Map market remains positive, reflecting the significant potential for technological advancement and widespread adoption across various industries.

DATA.HRSA.GOV is the go-to source for data, dashboards, maps, reports, locators, APIs and downloadable data files on HRSA's public health programs, including: HRSA-funded Health Center grants, grantees, sites, and related primary care programs Health Professional Shortage Areas (HPSA) and Medically Underserved Areas/Populations (MUA/P) Ryan White HIV/AIDS services, grantees, and providers Maternal and Child Health grants (Title V, Home Visiting, Healthy Start) National Health Service Corps (NHSC), Nurse Corps, and other workforce loan repayment/scholarship programs Grants for workforce training programs in medicine, nursing, dentistry, and public health Grants for rural health programs Organ donation DATA.HRSA.GOV allows you to search by topic area, by geography, and by tool.

Raster dataset representing top location score (suitability index) areas for vegetables storage/warehousing, filtered by exclusive criteria: access to finance, distance to major roads, access to IT (mobile broadband connection) and electricity. As a component of the FAO's Hand-in-Hand Initiative approach, the Geographical Information Systems - Multi-criteria Evaluation is designed to identify optimal sites for value chain infrastructure. Access to finance and roads are defined using linear distance thresholds:

Access to finance and roads are defined using linear distance thresholds:

• Banks - 20km buffer radius.

• Major roads - 2km buffer radius.

Access to IT and electricity is characterized applying the mobile broadband coverage map and Atlas AI Electrification map.

The location score, or suitability index, is determined processing sub-model outputs that assess logistical and socioeconomic factors for crop warehouse locations, such as supply, demand, infrastructure/accessibility, and poverty. This score is derived from an arithmetic weighted sum of normalized grids, ranging from 0 to 100.

Data publication: 2024-06-05

Contact points:

Resource Contact: FAO-Data

Resource Contact: Dariia Nesterenko

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:

1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. https://data.apps.fao.org/catalog/iso/304c21fb-0f5a-44ad-9948-2af6a7144fb5
2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates crop distribution
   within disaggregated units. https://data.apps.fao.org/map/catalog/srv/eng/catalog.search;jsessionid=4AA4D377D0F90E3328ACBDB5C21BFFC6?node=srv#/metadata/0c6be5d1-3a73-4516-953b-dbe2b511d6b3
3. OpenStreetMap.
4. Altas AI - Asset Wealth Index 2022. https://docs.atlasai.co/economic%20well-being/asset_wealth/
5. Altas AI - Electrification. https://docs.atlasai.co/infrastructure/electrification/
6. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. https://data.apps.fao.org/catalog/dataset/mobile-broadband-coverage-global-1km

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Zipped raster TIF file for Crop Storage Final Location: Maize (Eswatini - ~ 500 m)

880 Global import shipment records of Warehouse Shelving with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Raster dataset representing top location score (suitability index) areas for vegetables storage/warehousing, filtered by exclusive criteria: access to finance, distance to major roads, access to IT (mobile broadband connection) and electricity. As a component of the FAO's Hand-in-Hand Initiative, the Geographical Information Systems - Multi-criteria evaluation is designed to identify optimal sites for value chain infrastructure.

Access to finance and roads are defined using linear distance thresholds:

• Banks - 20km buffer radius.

• Major roads - 2km buffer radius.

Access to IT and electricity is characterized applying the mobile broadband coverage map and Atlas AI Electrification map.

The location score, or suitability index, is determined processing sub-model outputs that assess logistical and socioeconomic factors for crop warehouse locations, such as supply, demand, infrastructure/accessibility, and poverty. This score is derived from an arithmetic weighted sum of normalized grids, ranging from 0 to 100.

Data publication: 2024-02-16

Contact points:

Resource Contact: FAO-Data

Resource Contact: Dariia Nesterenko

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:

1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. https://data.apps.fao.org/catalog/iso/304c21fb-0f5a-44ad-9948-2af6a7144fb5
2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates crop distribution
   within disaggregated units. https://data.apps.fao.org/map/catalog/srv/eng/catalog.search;jsessionid=4AA4D377D0F90E3328ACBDB5C21BFFC6?node=srv#/metadata/0c6be5d1-3a73-4516-953b-dbe2b511d6b3
3. OpenStreetMap.
4. Altas AI - Asset Wealth Index 2022. https://docs.atlasai.co/economic%20well-being/asset_wealth/
5. Altas AI - Electrification. https://docs.atlasai.co/infrastructure/electrification/
6. Mobile Broadband Coverage produced based on: Coverage Data © Collins Bartholomew and GSMA 2021. https://data.apps.fao.org/catalog/dataset/mobile-broadband-coverage-global-1km

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Zipped raster TIF file for Crop Storage Final Location: Vegetables (Eswatini - ~ 500 m)

The dataset

The dataset is produced within the SafeLog project and it is used for benchmarking of multi-agent path planning algorithms. Specifically, the dataset consists of a set of 21 maps with increasing density and a set of 500 random assignments, each for a group of 100 agents for planning on each of the maps.

All of the maps, in the form of a graph G = {V, E}, are built on the same set of 400 vertices V. The sets of edges Ej, where j ∈ (0; 20), in the maps then form a set ranging from a spanning tree to a mostly 4-connected graph. These maps were created by generating a complete square graph with the size of 20*20 vertices. The graph was then simplified to a spanning tree, and, finally, approximately 50 random edges from the complete graph were added 20 times, to create the set of 21 maps of density ranging from 800 to 1500 edges in the graph.

Content and format

The following files are included in the dataset

test_nodes.txt - 400 nodes of a 20*20 square map in the form "id x y"
testAssignment.txt - 50499 random pairs of nodes ids from test_nodes.txt
test_edgesX.txt - pairs of adjacent nodes ids from test_nodes.txt forming edges
- X = 0 - tree
- X = 20 - full graph
- created starting at a full graph and repeatedly erasing edges until a tree remains

To illustrate the maps in the dataset, we provide three images (1008.png, 1190.png, and 1350.png) showing maps with 1008 (1190, 1350) edges.

Citation

If you use the dataset, please cite:

[1] Hvězda, J., Rybecký, T., Kulich, M., and Přeučil, L. (2018). Context-Aware Route Planning for Automated Warehouses. Proceedings of 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

@inproceedings{Hvezda18itsc,
author = {Hvězda, Jakub and Rybecký, Tomáš and Kulich, Miroslav and Přeučil, Libor},
title = {Context-Aware Route Planning for Automated Warehouses},
booktitle = {Proceedings of 2018 21st International Conference on Intelligent Transportation Systems (ITSC)},
publisher = {IEEE Intelligent Transportation Systems Society},
address = {Maui},
year = {2018},
doi = {10.1109/ITSC.2018.8569712},
}

[2] Hvězda, J., Kulich, M., and Přeučil, L. (2019). On Randomized Searching for Multi-robot Coordination. In: Gusikhin O., Madani K. (eds) Informatics in Control, Automation and Robotics. ICINCO 2018. Lecture Notes in Electrical Engineering, vol 613. Springer, Cham.

@inbook{Hvezda19springer,
author = {Hvězda, Jakub and Kulich, Miroslav and Přeučil, Libor},
title = {On Randomized Searching for Multi-robot Coordination},
booktitle = {Informatics in Control, Automation and Robotics},
publisher = {Springer},
address = {Cham, CH},
year = {2019},
series = {Lecture Notes in Electrical Engineering},
language = {English},
url = {https://link.springer.com/chapter/10.1007/978-3-030-31993-9_18},
doi = {10.1007/978-3-030-31993-9},
}

[3] Hvězda, J., Kulich, M., and Přeučil, L. (2018). Improved Discrete RRT for Coordinated Multi-robot Planning. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - (Volume 2).

@inproceedings{Hvezda18icinco,
author = {Hvězda, Jakub and Kulich, Miroslav and Přeučil, Libor},
title = {Improved Discrete RRT for Coordinated Multi-robot Planning},
booktitle = {Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - (Volume 2)},
publisher = {SciTePress},
address = {Madeira, PT},
year = {2018},
language = {English},
url = {http://www.scitepress.org/PublicationsDetail.aspx?ID=ppwUqsGaX18=\&t=1},
doi = {10.5220/0006865901710179},
access = {full}
}

Application for the consultation of the Map of Potential CO2 Geological Warehouses in Spain. It shows the main geological and petrophysical characteristics of structures that house potential geological CO2 warehouses.

Grain elevators in Iowa. This data is part of Iowa’s multimodal freight network. These facilities are important for the safe and efficient movement of freight that is demanded by Iowa’s large and diverse economy.