Geospatial data about St. Clair County, Alabama Parcels. Export to CAD, GIS, PDF, CSV and access via API.

Definition/Description

Flood hazard areas identified on the Flood Insurance Rate Map are identified as a Special Flood Hazard Area (SFHA). SFHA are defined as the area that will be inundated by the flood event having a 1-percent chance of being equaled or exceeded in any given year. The 1-percent annual chance flood is also referred to as the base flood or 100-year flood. SFHAs are labeled as Zone A, Zone AO, Zone AH, Zones A1-A30, Zone AE, Zone A99, Zone AR, Zone AR/AE, Zone AR/AO, Zone AR/A1-A30, Zone AR/A, Zone V, Zone VE, and Zones V1-V30. Moderate flood hazard areas, labeled Zone B or Zone X (shaded) are also shown on the FIRM, and are the areas between the limits of the base flood and the 0.2-percent-annual-chance (or 500-year) flood. The areas of minimal flood hazard, which are the areas outside the SFHA and higher than the elevation of the 0.2-percent-annual-chance flood, are labeled Zone C or Zone X (unshaded).Visit our website

2017 TIGER/Line® Shapefiles: Roads

Geospatial data about St. Clair County, Alabama Lakes & Ponds. Export to CAD, GIS, PDF, CSV and access via API.

Geospatial data about St. Clair County, Alabama Buildings. Export to CAD, GIS, PDF, CSV and access via API.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.

Linear Water Features includes single-line drainage water features and artificial path features that run through double-line drainage features such as rivers and streams, and serve as a linear representation of these features. The artificial path features may correspond to those in the USGS National Hydrographic Dataset (NHD). However, in many cases the features do not match NHD equivalent feature and will not carry the NHD metadata codes. These features have a MAF/TIGER Feature Classification Code (MTFCC) beginning with an "H" to indicate the super class of Hydrographic Features.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Area Hydrography Shapefile contains the geometry and attributes of both perennial and intermittent area hydrography features, including ponds, lakes, oceans, swamps (up to the U.S. nautical three-mile limit), glaciers, and the area covered by large rivers, streams, and/or canals that are represented as double-line drainage. Single-line drainage water features can be found in the Linear Hydrography Shapefile (LINEARWATER.shp). Linear water features includes single-line drainage water features and artificial path features, where they exist, that run through double-line drainage features such as rivers, streams, and/or canals, and serve as a linear representation of these features.

Soil SurveyThis map shows the Soil Survey Geographic (SSURGO) by the United States Department of Agriculture's Natural Resources Conservation Service. It also shows data that was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) dataset published in 1994. SSURGO digitizing duplicates the original soil survey maps. This level of mapping is designed for use by landowners, townships, and county natural resource planning and management. The user should be knowledgeable of soils data and their characteristics. The smallest scale map shows the Global Soil Regions map by the United States Department of Agriculture’s Natural Resources Conservation Service.Length of Growing PeriodLength of growing period is defined as the period during the year when average temperatures are greater than or equal to 5oC (Tmean >=5o C) and precipitation plus moisture stored in the soil exceed half the potential evapotranspiration (P>0.5PET). A normal growing period is defined as one when there is an excess of precipitation over pet (i.e. a humid period). Such a period meets the full evapotransiration demands of crops and replenishes the moisture definite of the soil profile. An intermediate growing period is defined as one in which precipitation does not normally exceed PET but does for part of the year. No growing period is when temperatures are not conducive to crop growth or P never exceeds PET (FAO 1978). Determining LGP is a difficult process that requires extensive calculations based on precipitation, evapotranspiration and soil moisture holding capacity. It also requires an understanding of the moisture requirements of specific crops since the growing period for many extends beyond the rainy season. Coarse resolution LGP data is available as part of IIASA/FAO’s initial GAEZ project (IIASA/FAO 2001). Geology UnitsThe geologic units in this layer depict formations at or near the surface. The emphasis is on pre-Quaternary geology, so Quaternary surficial deposits are shown only where they completely conceal the underlying units in significant areas. The extensive glacial deposits of the continental interior and Canadian shield are not shown, but Quaternary surficial deposits are shown in the intermontane basins in the Cordillera, in parts of the Atlantic and Gulf coastal plains, and in the Orinoco basin.Geology correlates closely with soil, elevation, vegetation, and ecosystems. It also used as a precedent for where there might be deposits of valuable resources. This dataset is not fine enough in scale for use for large scale analytical purposes, but can be used as context for visual analysis in conjunction with other data that may show correlations and trends.