GIS Data Acquisition and Data Formats

Presentation Agenda

• Discuss different ways of acquiring GIS data.

• Discuss examples of issues that might arise when acquiring GIS data.

• Demonstrate practically the use of main Ontario’s and Canada’s online

GIS data portals and tools for format conversion.

Tomislav Sapic

GIS Technologist

Lakehead University

Faculty of Natural Resources Management

GIS Data Acquisition and Data Formats

• GIS data created or captured by the user.

o Primary data capture

o Secondary data capture

•Already created GIS data obtained.

o Official data

o Data obtained from individuals in the government or

private organizations

Source Issues

Primary

Data

Capture

GPS collected

data

• Understand the accuracy of collected data:

- possible errors present in the system (multipath,

ionosphere geomagnetic disturbance, etc.).

- the real accuracy, not the accuracy suggested by the unit.

Data captured

from aerial and

satellite images.

• Is the image in a perspective projection or has it been

orthorectified?

• Learn about the basics of the imagery in question (what

satellite, the spatial, spectral, radiometric, temporal

resolutions) in order to understand the pixel values and

know how to best display them for data capturing.

GIS data created or captured by the user

Primary Data Capture

o GPS Collected Data

• Use available methods of increasing positional accuracy:

Differential GPS

Post-

processing

Real-time

1) WAAS

2) Public DGPS (not available in remote areas).

3) Real-time Kinematic, carrier phase based, GPS

(very accurate but expensive, requiring special

receivers).

Base Stations Canadian Spatial

Reference System

(CSRS)

https://www.nrcan.gc.

ca/maps-tools-

publications/tools/geo

detic-reference-

systems-tools/tools-

applications/10925

Source Issues

Secondary

Data

Capture

Hard copy

maps

• Hard copy maps can be distorted due to drying and shrinking.

• Georeference the map in the same projection in which the map

is.

• Be cognizant of the map scale. A note (metadata!) should be

made about it because GIS data don’t have inherent scale – data

collected at small scales can be used at large scales, carrying over

the small scale coarseness and digitizing errors.

• Maps are cartographic products, which means that they have

been made by using cartographic rules for representation – many

features are abstract representations of their real-world sources.

• Soft copy maps also have a degree of distortion in them if

created through scanning.

o Large-format feed scanners are the best choice when

combining the price, accuracy and quickness.

o Drum scanners are very accurate but also very expensive

and too slow.

o Flat-bed scanners – too small and inaccurate.

Soft copy

maps,

scanned

maps.

GIS data created or captured by the user

(From Devillers and Jeansoulin (2006))

Error vector field of a map scanned by a continuous feed scanner.

Secondary Data Capture

o Hard and Soft Copy Maps

• If georefencing in ArcGIS, set the data frame map projection to the map projection

of the map.

• If no map projection is stated on the map try to contact the person who created or

published the map. If that’s futile, as the last resort, try to figure it out. Here are some

hints that can help with it:

In Canada, two of the most used map projections are UTM and (Canada) Lambert

Conformal Conic:

If it’s a topographic or a topographic-based map, showing small areas (up

to a few hundred kilometers across), the projection is likely UTM.

If the area is large, such as an entire province or larger, the map projection

is likely Lambert Conformal Conic. If it is in UTM, distortions at the east,

west ends start to appear.

If the features are stretched east-west, e.g. squares look like horizontal

rectangles and circles like horizontal elipsoides, the ‘map projection’ is

likely the Geographic Coordinate System (GCS) – this coordinate system is

very unlikely, though, to be used in creating a map.

OBM tiles and a circle in UTM, Zone 15 OBM tiles and a circle in the Geograph. Coord. Sys. (GCS)

OBM tiles and a circle in Canada Lambert

Conformal Conic Eastern Ontario OBM tiles in UTM, Zone 15

• When georeferencing a map you will need to choose the transformation method and with and understand

the root mean square (RMS) error.

Common Transformation Methods Used for Georeferencing Images

Must have ≥ 3 control points. Must have ≥ 6 control points. Must have ≥ 10 control points.

Used for mostly flat areas. Used for hilly areas (relief

displacement!) and distorted

images.

Used for rugged terrain (relief

displacement!) and mountaines,

distorted images.

Notes: - more than required minimum of control points are advised to be used to lower the overall error.

- the higher the order of transformation is the greater can be image distortions in the areas far from the control points.

Important: Cartographic maps are planimetrically correct, and unless distorted due to their

manipulation, do not require greater than the affine transformation method.

• The transformation (the model, e.g. the Affine transformation) produces output locations

for control points. The transformed output locations most likely won’t match the true output

control point location and will result in an error. The overall average error, can be

calculated by taking a root mean square (RMS) of all errors.

Root Mean Square Error (RMSE)

•RMSE measures the displacement between the actual and estimated locations of the control

points (Chang 2008).

•RMSE should be achieved to the level that the project accuracy requires (e.g., as many meters of

error) or the user feels comfortable with. With Landsat images, RMSE should usually be brought

down to 1 pixel.

•RMSE is similar to standard deviation and errors have a distribution similar to normal

distribution.

~68% errors ≤ 1RMSE

~95% errors ≤ 2RMSE

Already created GIS data obtained

Source Issues

Official sources,government and non-government organizations

Topographic databases (OBM, NTDB), DEMs,thematic GIS datasets, imagery.

• Datasets might be delivered as .e00 files – transfer file format for coverages (an older ESRI file format).

• Most likely there are abundant metadata that accompany the database – make sure to find them and read parts relevant to your GIS work.

CanVec +(NTDB > CanVec > CanVec+): http://ftp.geogratis.gc.ca/pub/nrcan_rncan/vector/canvec/doc/info.html (Documentation files for the CanVec product)

Ontario datasets on Ontario GeoHub: https://geohub.lio.gov.on.ca/ , metadata example https://geohub.lio.gov.on.ca/datasets/forest-processing-facility

LiDAR Data If the map projection is not defined, use available

tools to define the projection. If it is defined, try to

double-check the map projection through the

metadata or the data provider.

Already created GIS data obtained

Source Issues

Data from

individuals

governments

or private

entities,

without or

with partially

proper

metadata

Mostly local

datasets.

• There are often mistakes in data themselves

and problems with improper formatting.

• Absence of the negative (-) sign for longitude

dec.degree coordinates in the western

hemisphere (e.g., Canada) provided in a

spreadsheet.

• Obtain as much as possible metadata about

the datasets from the sender.

• Extra caution should be exercised, the data

properly reviewed, their quality checked.

GIS Datasets Available Through Lakehead Library

• OBM datasets.

• Datasets available Ontario Geospatial Data Exchange Data (OGDE Data), for

example:

o Forest Resource Inventory (FRI) vector GIS files for each of forest management

units (FMU) in Ontario.

o 20 cm panchromatic, 40 cm multispectral, and stereo aerial imagery used to

photointerpret FRI.

o Triangulated digital surface models (DSM) for the flown FMUs.

• Census of Canada geography files and table databases.

The obtaining and use of the OGDE data will require signing a licence agreement stating

that the data will be used for research or education purposes only.

Ontario Base Map

(OBM) GIS

Database

•Entire province is divided into square tiles, 5x5 km in the south and

10x10km in the north.

• Datasets are created based on a scale 1:10000 in the south and

1:20000 in the north.

• Each tile contains a multitude of datasets, such as roads, rivers,

lakes, dams, towers, parks, contours, DTM, and many more.

• Each tile is named by adding scale + UTM zone + UTM easting of

the south-west corner + UTM northing of the south-west corner.

• Usually the name is shortened by leaving out the scale and

sometimes the UTM zone, and by truncating the UTM coordinates.

• Often OBM layers are referred to as ‘basic layers.’

163205320

Zone 16

SW corner x = 320000

SW corner y = 5320000

UTM Zone 15UTM Zone 16

• Many GIS datasets can be downloaded from the Web; some more prominent GIS data portals can be found at http://flash.lakeheadu.ca/~forspatial/ - Web GIS Resources .

Examples:Ontario Scholars GeoPortal: http://geo1.scholarsportal.info/Ontario datasets on Ontario GeoHub: https://geohub.lio.gov.on.ca/CanVec + (Canada basic vector layers) : http://maps.canada.ca/czs/index-en.html

Some Common Issues and Challenges with

Acquired GIS Data

OBM tile files are often received as

.e00 files.

e00 files are interchange files for older

ESRI file formats, ArcINFO files,

including the vector file type called

coverage. E00 files need to be imported

in ArcGIS by following a specific

procedure:

http://resources.arcgis.com/en/help/mai

n/10.2/index.html#//0012000000460000

00

ESRI Coverages

• Vector data models that are formatted as composite files.

• Can’t be edited in ArcGIS.

• Used to be ESRI’s flagship data format but are being replaced with

geodatabases.

Coverages can be exported to

shapefiles or geodatabase

feature classes through

ArcCatalog or ArcMap

(Export Data of a coverage

layer).

Garmin .gpx Files

• If dealing directly with Garmin .gpx files, the easiest way to bring them into GIS is to use

the free software DNR Garmin.

1) File > Load From

2) File Format

.gpx

3) Feature type (e.g. waypoint).

4) File > Save to > e.g. shapefile

References:

Chang, K. 2008. Introduction to Geographic Information Systems. McGraw-Hill, New York.

Devillers, R. and R. Jeansoulin. 2006. Fundamentals of Spatial Data Quality. ISTE Ltd.

ESRI. 2010. ArcGIS ArcMap Help File.

Longley, P. A., M. F. Goodchild, D. J. Maguire, and D. W. Rhind. 2011. Geographic Information Systems & Science. John Wiley & Sons, Inc.

McMaster, R. B. and K. S. Shea. 1992. Generalization in Digital Cartography. Washington, DC: Association of American Geographers.

Lekkerkerk, H. J. 2007. The GPS Handbook for Professional Users. CMedia Productions. Netherlands.