GIS - Vocab 2

Geocoding

A GIS operation for converting street addresses into spatial data that can be displayed as features on a map, usually by referencing address information from a street segment data layer.

US Census Tract

A census tract, census area, or census district is a geographic region defined for the purpose of taking a census. In the United States, Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however, the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census. Census tracts occasionally are split due to population growth or merged as a result of substantial population decline.

Georeferenced scanned map image

A paper map that has been scanned to a digital graphics file and then been aligned to a known coordinate system so it can be viewed, queried, and analyzed with other geographic data. An example of georeferenced scanned maps are the USGS Digital Raster Graphics scans of USGS topographic quadrangle maps: http://topomaps.usgs.gov/drg/

US Census TIGER file

Acronym for Topologically Integrated Geographic Encoding and Referencing. A digital spatial database of geographic features, covering the entire United States and its territories, that provides a topological description of the geographic structure of these areas. The files are a public product created from the U.S. Census Bureau Topologically Integrated Geographic Encoding and Referencing (TIGER) database. TIGER/Line files define the locations and spatial relationships of streets, rivers, railroads, and other features to each other and to the numerous geographic entities for which the Census Bureau tabulates data from its censuses and sample surveys.

Snapping tolerance

In an ArcGIS editing session, the distance within which the pointer or a feature will snap to another location. If the location being snapped to (vertex, boundary, midpoint, or connection) is within that distance, the pointer will automatically snap. Snapping tolerance can be measured using either map units or pixels.

GIS metadata

Information that describes the content, quality, condition, origin, and other characteristics of data or other pieces of information. ---- for spatial data may describe and document its subject matter; how, when, where, and by whom the data was collected; availability and distribution information; its projection, scale, resolution, and accuracy; and its reliability with regard to some standard.

Random spatial sampling

Locations obtained by choosing x-coordinates and y-coordinates at random within the spatial area being sampled

Population forecasting or population projections

Population projections are estimates of the population for future dates. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The US Census Bureau frequently calculates future population forecasts which are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. See: http://www.census.gov/population/projections/data/national/2012.html

Spatial or geostatistical interpolation

The estimation of surface values at unsampled points based on known surface values of surrounding points. Interpolation can be used to estimate elevation, rainfall, temperature, chemical dispersion, or other spatially-based phenomena. Interpolation is commonly a raster operation, but it can also be done in a vector environment using a TIN surface model. There are several well-known interpolation techniques, including Inverse Distance Weighted (IDW), spline and kriging.

Digital Elevation Model (DEM)

The representation of continuous elevation values over a topographic surface by a regular array of z-values. --- are typically used to represent terrain relief

Land Use/Land Cover (LULC) GIS data

digital spatial thematic data - typically in either vector polygon or raster format - that maps the types of basic physical land cover (such as forest, open water, agriculture, shrub cover, urban or built cover, etc.) as is thus known as land cover data, or that maps how the land is being used by humans (e.g. for development, conservation, public land, industrial, mixed uses, etc.) and is thus known as land use data. Many national and international scientific research agencies produce high-quality GIS maps of national or global Land Cover/Land Use (LULC), such as 1, The USGS Land Cover Institute (LCI) http://landcover.usgs.gov/ 2, The NASA Land-Cover and Land-Use Change (LCLUC) Program: http://lcluc.umd.edu/ 3, United Nations Food and Agriculture Organization (FAO) GeoNetwork database of GIS LULC global datasets: http://www.fao.org/geonetwork/srv/en/main.search?title=africover%20landcover

Systematic spatial sampling

spatial sampling based on a specific systematic pattern, such as points or transects regularly spaced, across the area being sampled. The location of the first point or transect is selected randomly.

Satellite or airphoto spatial resolution

the pixel size of a digital airphoto or satellite sensor image, corresponding to a specific size of surface area (e.g. in m2) being measured on the Earth's surface; for example, Landsat 7 satellite imagery (produced by the US government) has 30 meter pixel spatial resolution, while commercially available WorldView-3 satellite imagery (http://worldview3.digitalglobe.com ) has 0.31m (12 inches) spatial pixel resolution.

Stratified spatial sampling

when subpopulations in geographic sub-areas within an overall geographic population area vary, spatial Stratification is the process of dividing members of the geographic area to be sampled into homogeneous spatial subgroups before sampling. Then simple random spatial sampling or systematic spatial sampling is applied within each stratum. This often improves the representativeness of the sample by reducing sampling error. It can produce a weighted mean that has less variability than the arithmetic mean of a simple random sample of the population.