Iowa Geographic Names

This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names. The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.

National Flood Hazard Layer (HESS)

National Flood Hazard Layer (NFHL) for development of the Parcel Inventory dataset for the Housing Element Site Selection (HESS) Pre-Screening Tool. This NFHL data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. In addition to the identification of Special Flood Hazard Areas, the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the National Flood Insurance Program. The FIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The FIRM Database serves to archive the information collected during the Flood Risk Project. ** This flood zone data should not be used for flood insurance purposes, but rather hazard mapping. FIRM data retrieved directly from the FEMA should be used for insurance programs. Source data, by county, was downloaded from https://msc.fema.gov/portal/advanceSearch.

OLAS Population-based Water Stress and Risk Dataset for Latin America and the Caribbean

LAC is the most water-rich region in the world by most metrics; however, water resource distribution throughout the region does not correspond demand. To understand water risk throughout the region, this dataset provides population and land area estimates for factors related to water risk, allowing users to explore vulnerability throughout the region to multiple dimensions of water risk. This dataset contains estimates of populations living in areas of water stress and risk in 27 countries in Latin America and the Caribbean (LAC) at the municipal level. The dataset contains categories of 18 factors related to water risk and 39 indices of water risk and population estimates within each with aggregations possible at the basin, state, country, and regional level. The population data used to generate this dataset were obtained from the WorldPop project 2020 UN-adjusted population projections, while estimates of water stress and risk come from WRI’s Aqueduct 3.0 Water Risk Framework. Municipal administrative boundaries are from the Database of Global Administrative Areas (GADM). For more information on the methodology users are invited to read IADB Technical Note IDB-TN-2411: “Scarcity in the Land of Plenty”, and WRIs “Aqueduct 3.0: Updated Decision-relevant Global Water Risk Indicators”. | https://www.wri.org/data/aqueduct-global-maps-30-data | | https://www.worldpop.org/ | | https://gadm.org/ |

NOAA - Percentage of the continental U.S. population served by flood inundation mapping services

For more than two decades, the emergency management community has articulated a need for real-time, street-level flood inundation maps depicting the areal extent, depth, and infrastructure impacted by flood waters, to inform critical decisions that save lives and property before, during, and, after a flood event. NOAA will collect and integrate high-resolution bathymetric and topographic data to advance flood and inundation mapping capabilities, particularly for previously underserved communities inland and along the coast. NOAA tracks the progress of making real-time flood inundation mapping services available for 100% of the U.S. population, using Oak Ridge National Laboratory LandScan 2019 data and the latest Census data to assess how many residents lie within the areas served by FIM.

OLAS/SCL WASH Household Survey Dataset

The OLAS/SCL Household Survey Data Set contains 47 water and sanitation related indicators generated from microdata from national household surveys throughout the region. The data set contains information from 2003-2022 for 22 countries throughout Latin America and the Caribbean. Indicators are provided in terms of household percentage and total households that fall into each category, and can be broken down by various socioeconomic dimensions, including area (urban or rural community), income quintile, migratory status, ethnicity, and disability status. This dataset is the result of a collaboration between INE/WSA and SCL, and is a subset of the larger IDB SCL Indicators dataset.

Oil and Gas Annual Production: Beginning 2001

This dataset contains annual production information of oil and gas wells in New York State from 2001 to present.

OLAS/SCL WASH Household Survey Dataset - Regional Estimates

This dataset provides regional estimates for the indicators in the OLAS/SCL WASH Household Survey Dataset: https://mydata.iadb.org/Water-and-Sanitation/OLAS-SCL-WASH-Household-Survey-Dataset/bjat-gfsm For information on how the dataset was generated, please refer to the methodology document.

Flood Hazard Areas (DFIRM Statewide)

South Sudan Unity State Baseline Report: WASH

To get a better understanding and assess the severity of the nutrition and mortality situation in Mayendit County, implementing partners conducted a Nutrition and Mortality SMART survey from the 10th to 23rd of December, 2015. The overall survey objective was to determine the nutrition status among children aged 6 to 59 months and to estimate crude and under-five retrospective mortality rates in Mayendit County, Unity State. Data collected included morbidity data (two-week recall), immunization and supplementation coverage, and a qualitative component on Food Security and Livelihoods (FSL).

SWGIHubCorShp

Maryland's green infrastructure is a network of undeveloped lands that provide the bulk of the state's natural support system. These data map hub and corridor elements within the green infrastructure. The Green Infrastructure Assessment was developed to provide decision support for Maryland's Department of Natural Resources land conservation programs. Ecosystem services, such as cleaning the air, filtering water, storing and cycling nutrients, conserving soils, regulating climate, and maintaining hydrologic function, are all provided by the existing expanses of forests, wetlands, and other natural lands. These ecologically valuable lands also provide marketable goods and services, like forest products, fish and wildlife, and recreation. The Green Infrastructure serves as vital habitat for wild species and contributes in many ways to the health and quality of life for Maryland residents. To identify and prioritize Maryland's green infrastructure, we developed a tool called the Green Infrastructure Assessment (GIA). The GIA was based on principles of landscape ecology and conservation biology, and provides a consistent approach to evaluating land conservation and restoration efforts in Maryland. It specifically attempts to recognize: a variety of natural resource values (as opposed to a single species of wildlife, for example), how a given place fits into a larger system, the ecological importance of natural open space in rural and developed areas, the importance of coordinating local, state and even interstate planning, and the need for a regional or landscape-level view for wildlife conservation. The GIA identified two types of important resource lands - "hubs" and "corridors." Hubs typically large contiguous areas, separated by major roads and/or human land uses, that contain one or more of the following: Large blocks of contiguous interior forest (containing at least 250 acres, plus a transition zone of 300 feet) Large wetland complexes, with at least 250 acres of unmodified wetlands; Important animal and plant habitats of at least 100 acres, including rare, threatened, and endangered species locations, unique ecological communities, and migratory bird habitats; relatively pristine stream and river segments (which, when considered with adjacent forests and wetlands, are at least 100 acres) that support trout, mussels, and other sensitive aquatic organisms; and existing protected natural resource lands which contain one or more of the above (for example, state parks and forests, National Wildlife Refuges, locally owned reservoir properties, major stream valley parks, and Nature Conservancy preserves). In the GIA model, the above features were identified from Geographic Information Systems (GIS) spatial data that covered the entire state. Developed areas and major roads were excluded, areas less than 100 contiguous acres were dropped, adjacent forest and wetland were added to the remaining hubs, and the edges were smoothed. The average size of all hubs in the state is approximately 2200 acres. Corridors are linear features connecting hubs together to help animals and plant propagules to move between hubs. Corridors were identified using many sets of data, including land cover, roads, streams, slope, flood plains, aquatic resource data, and fish blockages. Generally speaking, corridors connect hubs of similar type (hubs containing forests are connected to one another; while those consisting primarily of wetlands are connected to others containing wetlands). Corridors generally follow the best ecological or "most natural" routes between hubs. Typically these are streams with wide riparian buffers and healthy fish communities. Other good wildlife corridors include ridge lines or forested valleys. Developed areas, major roads, and other unsuitable features were avoided.