9. GIS Data Collection

Overview

IntroductionPrimary data captureSecondary data captureData transferCapturing attribute dataManaging a data capture project

Data Collection

One of most expensive GIS activitiesMany diverse sourcesTwo broad types of collection

Data capture (direct collection)Data transfer

Two broad capture methodsPrimary (direct measurement)Secondary (indirect derivation)

Data Collection Techniques Raster Vector

Primary Digital remote sensing images

GPS measurements

Digital aerial photographs

Survey measurements

Secondary Scanned maps Topographic surveys

DEMs from maps

Toponymy data sets from atlases

Stages in Data Collection Projects

Planning

Preparation

Digitizing / TransferEditing / Improvement

Evaluation

Primary Data Capture

Capture specifically for GIS useRaster – remote sensing

e.g. SPOT and IKONOS satellites and aerial photographyPassive and active sensors

Resolution is key considerationSpatialSpectralTemporal

Spatial and temporal characteristics of commonly used Earth observation remote-sensing systems and their sensors

Typical Reflectance Signatures

Vector Primary Data Capture

SurveyingLocations of objects determined by angle and distance measurements from known locationsUses expensive field equipment and crewsMost accurate method for large scale, small areas

GPSCollection of satellites used to fix locations on Earth’s surfaceDifferential GPS used to improve accuracy

Total Station

Secondary Geographic Data Capture

Data collected for other purposes can be converted for use in GISRaster conversion

Scanning of maps, aerial photographs, documents, etcImportant scanning parameters are spatial resolution and bit depth

Vector Secondary Data Capture

Collection of vector objects from maps, photographs, plans, etc.Digitizing

Manual (table) Heads-up and vectorization

Photogrammetry – the science and technology of making measurements from photographs, etc.COGO – Coordinate Geometry

Scanner

Types of scanner

Vector Over Raster

Digitizer

Adjacent raster cells with the same attribute values are aggregated. Class boundaries are then created at the intersection between adjacent classes in the form of vector lines

Batch vectorization of a scanned map

(A) original raster file

(B) vectorized polygons

Typology of human errors in digitizing: (A) undershoots and overshoots; (B) invalid polygons; and (C) sliver polygons

Examples of spatial error in vector data

Radius Topology Feature Snapping

Error induced by data cleaning

Mismatches of adjacent spatial data sources that require rubber-sheeting

Edge matching

Rubber sheeting

Photogrammetry

Data Transfer

Buy vs. build is an important questionMany widely distributed sources of GIKey catalogs include

US NSDI Clearinghouse networkGeography Network

Access technologiesTranslationDirect read

Comparison of data access by translation and direct read

SummaryData collection is very expensive, time-consuming, tedious and error proneGood procedures required for large scale collection projectsMain techniques

Primary• Raster – e.g. remote sensing• Vector – e.g. field survey

Secondary• Raster – e.g. scanning• Vector – e.g. table digitizing