Spatial data for GIS

This document discusses using remote sensing and GIS for land use/land cover mapping. It describes analyzing agricultural versus urban land to ensure development doesn't degrade farmland. Land cover refers to ground surface characteristics like vegetation or bare soil, while land use refers to how land is used, such as agriculture or recreation. The document outlines classification systems and criteria for remote sensing-based land use/land cover mapping. It also discusses digital classification techniques, global and national land use datasets, and applications of remote sensing for natural resource management and change detection analysis.

This document discusses remote sensing platforms and sensors. It describes the different types of orbits used by remote sensing satellites, including low Earth orbit, sun synchronous orbit, and geostationary orbit. It also outlines the various platforms that can be used, such as ground-based, airborne, and space-borne. Finally, it examines the characteristics of remote sensing sensors, including spatial, spectral, radiometric, and temporal resolution.

This document discusses GIS data analysis techniques including raster to vector conversion and spatial analysis through vector overlay. It provides information on various data types and models in GIS. Key analysis techniques covered are raster and vector data overlays, terrain mapping and analysis, and spatial interpolation methods. Specific vector and raster overlay methods like point-in-polygon, line-in-polygon and polygon-on-polygon are described. Spatial data editing techniques involving digitization errors and topological/non-topological editing are also summarized.

Raster data is represented by a grid of cells, where each cell contains numeric or qualitative values. Raster data comes from sources like images, maps, and satellite imagery. Common analyses of raster data include buffering, reclassification, hillshades, interpolation, and surface calculation. Buffering assigns "in" and "out" values to cells based on their distance from a feature. Reclassification reassigns cell values. Hillshades create shaded relief maps from elevation data. Interpolation estimates values between known data points. Surface calculation performs cell-by-cell mathematical functions on rasters.

This document provides an overview of geographical information systems (GIS), including definitions of GIS, its basic principles and components, data types used in GIS (vector and raster), advantages and applications of GIS. Specifically, it defines GIS as a computer system for capturing, storing, analyzing and displaying spatially referenced data. It describes the key principles of data capture, management, analysis and visualization. It outlines the typical hardware, software and data components of a GIS, and differentiates between vector and raster data types. Finally, it discusses advantages like accurate representation and analysis, and applications across different domains.

The document discusses vector data models in GIS. Vector data models represent geographic features using points, lines, and polygons. The key vector data models are the spaghetti model, which encodes features as strings of coordinates, and the TIN (triangulated irregular network) model, which creates a network of triangles connecting points. Vector models allow for discrete boundaries but complex algorithms, while raster models divide space into a grid but are simpler.

Triangulated Irregular Network (TIN) is a digital representation of a surface as non-overlapping triangles computed from irregularly spaced 3D points, where each point has x, y, and z coordinates. TINs are useful for representing continuous surfaces in GIS as they can accurately model terrain with significant slopes and variations while using fewer triangles in flat areas. TINs allow for easy derivation and analysis of surface properties like slope, aspect, area, and volume from mass point data, contours, and breaklines.

An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.

This document provides an introduction to Geographic Information Systems (GIS). It defines GIS as a system designed to store, manipulate, analyze and display spatially referenced data. The key components of a GIS are hardware, software and data. Common GIS software includes desktop programs like ArcGIS and open-source options like QGIS. GIS can incorporate different types of spatial data like raster, vector and remote sensing data along with associated attribute tables. Example applications discussed are in hydrology, including watershed analysis and flood modeling.

Key encoding, digitizing, scanning, coordinate geometry, and direct file transfer are the main techniques for inputting data into a geographic information system (GIS). Key encoding involves directly entering spatial and attribute data using a keyboard. Digitizing can be done heads down using a digitizing tablet or heads up using a mouse on a digital map. Scanning uses electronic detectors to automatically input data faster but may require data cleaning. Coordinate geometry enters survey measurements to calculate feature coordinates. Direct file transfer imports available GIS data sets after adjustments.

This document discusses GIS topology, which establishes rules for how geographic features share geometry and spatial relationships. Topology ensures data quality, enhances analysis, and manages coincident geometry. It has three components: connectivity between nodes and arcs, area definition using polygon boundaries, and contiguity to determine adjacent features. Topological rules prevent errors like overlaps, gaps, dangles and ensure proper containment of points and boundaries.

The document discusses land suitability classification according to the FAO, which involves assessing land for specified uses and comparing benefits with needed inputs for sustained use without degradation. The classification system includes four categories - orders, classes, subclasses, and units - which respectively reflect the kind of suitability, degree of suitability, limitations or improvements required, and minor management differences. Land is then rated as either suitable, unsuitable, or permanently unsuitable according to this classification system.