AI 용어집
인공지능 완전 사전
Raster Data
Geospatial data structure organized as a grid of pixels where each cell contains a numerical value representing specific spatial information such as elevation, temperature, or land cover. This format is particularly suited for representing continuous phenomena and satellite imagery.
Vector Data
Geospatial representation using discrete geometric features (points, lines, polygons) defined by precise mathematical coordinates rather than a pixel grid. This format excels at representing objects with sharp boundaries such as roads, buildings, or administrative parcels.
Spatial Overlay
Analysis geometrically combining multiple vector layers to create new features based on their spatial intersections, transferring attributes from the original layers. This fundamental technique enables multi-criteria analysis and complex spatial modeling.
Pixel Matrix
Two-dimensional structure organizing raster image pixels into rows and columns, where each position corresponds to specific spatial coordinates in the reference system. This matrix structure facilitates mathematical processing and image analysis operations.
Spatial Topology
Set of explicit spatial relationships between vector features (adjacency, connectivity, containment) preserved independently of exact geometric coordinates. Topology ensures spatial data consistency and enables advanced analyses such as network routing or administrative management.
Geographic Coordinate System
Mathematical reference frame defining how geographic coordinates (latitude, longitude, altitude) correspond to positions on Earth's surface, including geodetic datum and Earth shape model. This system is fundamental for ensuring the accuracy and integration of spatial data.
Neighborhood Analysis
Raster processing evaluating each pixel based on surrounding pixel values according to a moving window (kernel) to detect patterns, edges, or textures. This approach is essential for image filtering, classification, and spatial feature extraction.
Tessellation
Partitioning of geographic space into contiguous non-overlapping polygons creating a regular or irregular mesh for spatial analysis and modeling. Methods include square grids, hexagons, triangulated irregular networks (TIN), or Voronoi diagrams according to analytical needs.
Spectral Band
Individual raster layer representing reflectance or emission values at a specific wavelength of the electromagnetic spectrum, fundamental in remote sensing. Multispectral band combinations enable thematic analysis and land use classification.
Raster Mosaic
Seamless assembly of multiple adjacent raster images to form a continuous spatial coverage, managing overlaps and illumination differences. This technique allows creating extensive image databases from individual satellite scenes or aerial photographs.
Image Pyramid
Hierarchical structure of multiple resolutions of the same raster, creating increasingly degraded versions to accelerate display and navigation at different scales. This optimization significantly reduces loading times when visualizing vast raster datasets.