Understanding GIS P.Quek [email protected] Training Workshop on Forest Biodiversity Conservation and...
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Transcript of Understanding GIS P.Quek [email protected] Training Workshop on Forest Biodiversity Conservation and...
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Understanding GIS
Training Workshop on Forest BiodiversityConservation and Management of Forest Genetic ResourcesKuala Lumpur, Malaysia 5 - 16 June 2006
Parts of this presentation were derived from A.Jarvis and P.Mathur ppt
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What is GIS?
A Geographic Information System is a set of computer programs that can organize, display, and analyze spatially distributed data•spatial dataspatial data in graphics form•and related, logically-attached, non-spatial, attribute dataattribute data
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GIS Image Handling
GIS handles images commonly in one of two forms:
Raster: A grid of rows and columns of cells.
These might represent photographic or scanned images.
Vector: A geometric shape, including points, lines, and polygons.
These might represent buildings, roads, and counties.
Both of these may have tables of attribute data associated with them, e.g. species, population, numbers, etc.
Such associated data can be used to colour a map to convey information in a visual manner.
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Information required to use GIS
• Spatial or Locality informationCoordinates of the locality Other information on the environment of the
area in maps, description of location
• Attribute or Taxonomic information Accepted scientific name Other information relating to taxonomic,
ecological, ethnobotanical, etc.
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• Ecogeographic survey for locating diversity
• Planning field exploration and germplasm collecting
• Design, management and monitoring of in situ reserves
• Site identification for germplasm introduction
• Site identification for germplasm evaluation
What can we use it for?
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Methodologies, software and data sourcesMethodologies:
– published by others– IPGRI collaborative
studies, linked to training
Software:• Commercial software
– ArcView– ArcInfo– IDRISI– MapInfo
• Specialized for PGR• FloraMap• DIVA• SID
Data:– Genebank and
herbarium• passport• characterization• evaluation
– Thematic• production• environmental• socio-economic
– Sources• national
programmes• CGIAR Centres
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Ecogeographic surveys locate areas which are:
• Likely to contain target material
– predicting species/ecotypes distributions
• Trait specific highly diverse – characterization/ evaluation traits
– point-centred methods
– grid methods
• Areas complementary to each other
• Under-conserved
– gap analysis
• Threatened areas
– mapping the risk of genetic erosion
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So why isn’t everybody using it?
•PGR programmes, particularly in developing countries, have significant resource constraints, and
•GIS hardware, software and data are perceived as being
– expensive
– difficult to obtain (very much easier now)
– complex to use
•and therefore not a priority compared to other things
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Application of GIS for PGR management
• What is required?– Geo-references and data– Associated data
• What we can get?– Generating maps– Generating climatic database
• Interpretation of results for:– Gap analysis– Diversity analysis
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Application of GIS for crop diversity
mapping and diversity assessment Possible outputs of GIS use in PGR
management:1. Update passport information for collecting sites
with respect to geo-reference information.
2. Map the crop diversity collected for individual countries and also on global basis.
3. Analyze crop diversity collected for different passport and characterization information.
4. Complementary diversity analysis for combination of traits.
5. Based on past collecting information, identify potential matching sites for cultivation of crop under biotic and abiotic stress conditions.
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Application of GIS for crop diversity mapping and diversity assessment
Classify collections based on climatic adaptation.
6. Provide climatic information (Monthly rainfall, minimum and maximum temperature) for individual collecting sites.
7. Providing climate maps for various climatic parameters and their combinations as well as for altitude of collecting sites.
8. Providing guidelines to further develop collecting strategies for new collections as well as for re-collecting of germplasm.
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Global Positioning Systems (GPS)
Acquiring locality data
Training Workshop on Forest BiodiversityConservation and Management of Forest Genetic ResourcesKuala Lumpur, Malaysia 5 - 16 June 2006
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Figure from http://franson.com/coordtrans/index.asp
Global Positioning System, usually called GPS, is the only fully-functional satellite navigation system
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Principles
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2D position (i.e. lat/long) - a minimum of 3 satellites must be in view, with good signals.
3D position (i.e. lat/long/altitude) - minimum of 4 satellites must be in view, with good signals
Bad geometryGood geometry
Taking a Position
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AccuracyDepends on :
• Geometry of satellites
• Local environmental conditions (clouds/vegetation/buildings)
• Quality of GPS receiver (a question of cost)
Accuracy varies from a matter of millimetres to around 50m in latitude/longitude, and 1m to 100m in altitude
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Which GPS Receiver to Use?
Trimble
Garmin 12 XL
• Both off the shelf “supermarket” brands
• Approximate cost $100-200
• Maximum accuracy - 5 -10m
• Both offer navigation facilities
• Direct connection to computer to download data
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Recommendation
Garmin 12 XL
Ease of use
Better antenna for use in forest canopies
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Taking a Position in Forest Canopies
Canopy interferes heavily with signal. Steps to take:
• Patience…..wait 5-10 minutes for good satellite coverage before taking an average position
• Try to take the position under a dry canopy
• Use the almanac function in cases of very poor coverage to time the collection of the geo-position with good satellite coverage
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Measurement of Altitude
GPS vs Altimeter
• GPS better under clear skied, low vegetated flat areas
• Altimeter preferable in forested areas/mountain regions
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What data to take and in what format
GPS Data :
Decimal degrees - i.e. 45.34256N, 76.54864W (North and East are +ve numbers, South and West are -ve numbers)
Five decimal points (indicates 10m accuracy at Equator)
The circumference of the earth at the equator 40,075 kilometers
Descriptive data:
ADM1 – first level administrative subdivisionADM2 – second level administrative subdivisionADM3 – third level administrative subdivisionADM4 – fourth level administrative subdivision
“At km 21 marker along Route 120 S of Morelia, on W side of Route 120.”
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Diameter (m) degrees minutes seconds
360 60 60
earth 1 degree 1 minute 1 second
40075000 111319.4 1855.324 30.92207
Decimal accuracy
0.9 100187.5
0.00009 10.01875
Conversion of 30o 31’ 32’’ E= 30 + 31/60 + 32/3600 =30 + .51667 +0.00889=30.52556
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Equator
Gre
enw
ich
+
+-
-
EastWest
0o
0o
Longitude : -180o till +180o
Latitude : -90o till +90o
North
South
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Bottom Line
• No GIS analysis is possible without geo-referenced accessions. The adoption of this technology relies upon careful data collection using GPS in the field
• Garmin XL12 is the recommended GPS
• Data taken in decimal degrees with 5 decimal points of precision
• As much descriptive information about locality noted as a backup source
• Post-collection checking of GPS data before sending off to PGR databases
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References
GPS Brands:
http://www.garmin.com
http://www.trimble.com
More info on GPS technology and systems :
http://www.colorado.Edu/geography/gcraft/notes/gps/gps_f.html
http://en.wikipedia.org/wiki/Global_Positioning_System
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http://www.gpstm.com
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GIS tools for PGR research
• FloraMapFloraMap (CIAT)– A computer tool for predicting the
distribution of plants and other organisms in the wild
• DIVADIVA (CIP, IPGRI, SGRP)– A GIS for the management and spatial
analysis of genetic resources data
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http://isa.ciat.cgiar.org FloraMap
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Introduction to FloraMap
• Introduction
• Minimum hardware and software requirements
• Installation
• Setting up the Map properties
• Checking the data quality
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New GIS tools for PGR research• FloraMapFloraMap
– developed by CIAT– software + climate data– on CD-ROM, $100 – you provide latitude, longitude,
(altitude)– can be used to
• check data quality• predict species distributions
– identify gaps in collections• identify climatic adaptation
groups within collections– compare climatic adaptation
of species• predict adaptation in other areas
– what it does not do• take soils etc. into account• give you a once and for all
answer
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• FloraMap is a system for producing the predicted distribution OR
• Areas of possible adaptation for a given species
However, • It is assumed that the climate at the point of
collection of a set of germplasm collections or herbarium specimens, is representative of the environmental range of the species
• The climate at these collection points is used as calibration set to compute a climate probability model
Introduction to FloraMap
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FloraMap file types:
• Accession point files– ACP.files – space delimited ASCII files with column
headings– DBF files – They may contain accession points data,
climate data, or information about polygons in the shape files
• SHP files: are shape files that delineate point, line or polygon data. They are also compatible with ArcView
• SHX files: are specialised index files that give meaning to the shape file
• TXT files: Are produced when a report file is saved. These are ASCII space-delimited data files
Introduction to FloraMap
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ESRI shapefile:• Consists of – Main file, and Index file, and a dBase
table.
• Main file is a direct access, variable-record-length file in which each record describe a shape with a list of its vertices.
• In the Index file, each record contains the offset of the corresponding main file record from the beginning of the main record.
• The dBase table contains features attributes with one record per feature. The one-to-one relationship between geometry and attributes is based on record number. Attributes records in the dBase file must be in the same order as records in the main file
Introduction to FloraMap
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Example:
Main file: Counties.shp
Index file: counties.shx
dBase table: counties.dbf
These three files above describe a map layer
MAP files: are FloraMap files that contains the information to associated DBF files, accession point files, and shapefiles in a map coverage.
A MAP file contains references to the several map layers combined together to represent a map.
FloraMap will construct a set of all the files necessary for the map and name them following the name you give to the MAP file.
Introduction to FloraMap
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Mapping Taro Collection
Mapping PNG taro collections using FloraMap
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Taro Diversity Prediction
Similar sites for taro diversity or introduction (based on PNG taro collections)
Prediction based on FloraMap
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Climatic matching probability distribution map of Sri Lanka
Cowpea collections
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Prediction of similar climatic grids across region
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Prediction of similar climatic grids across continents
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New GIS tools for PGR research•DIVADIVA
– developed by CIP with IPGRI, SGRP and FAO support
– software + data– on CD-ROM, downloadable from WWW– Cost - $ FREE– you provide latitude, longitude and
characterization data– can be used to
• check data quality• map diversity using grids of different
sizes• identify areas of complementary
diversity• map occurrence of single traits or
combinations of traits– what it does not do
• make predictions outside the data area
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Introduction to DIVA-GIS
Free GIS software
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With DIVA you can:• Map the location of sites where population of
plant and animal species were observed• Make grid maps of the distribution of biological
diversity• Identify hotspots and areas of complementary
levels of diversity• Extract climate data for localities points• Predict presence of species based on climate –
using BIOCLIM or DOMIN models for either:– Current climate (1960-90)– Predicted future climate (2040-60)
Introduction to DIVA-GIS
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Aimed at users who:– Cannot afford commercial GIS– Do not have time to learn how to use– Want a GIS tailor-made to analyse
biological distribution
Introduction to DIVA-GIS
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Installing DIVA-GIS
• Provided on CD• Can download from web (http:/www.diva-gis.org)• If download, unzip downloaded files• Click setup.exe to install DIVA• After installation following folders:
– Bin– Environ– Gazet– Tutor
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File types and Formats
• DIVA uses various types and formats
• Most important are:– Shape files– Grid files– Image files (For spatial database)– dBase IV (DBF) format for reading and writing
external (non spatial) database
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Shape files
• Describe the location of:– Point – collecting locations– Polylines – roads– Areas – polygons e.g. countries, soil
types• Consists of:
– SHP– SHX– DBF – But treated as one file
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• Shapefiles format developed by ESRI – leading GIS software company
• Initially developed for use in ArcView, but now really all GIS programme either directly use them, or import them
Shape files
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Gridfiles• Grid database – area is divided into equally sized
rectangles
• Consists of four separate files, but DIVA_GIS again treat them as if they were one file– GRI – File with grid database– GRD – Documentation file– BMP – bitmap (image) derived from the GRI file and
used for display– BMPW – “world-file”- ESRI, 1999 – the geo-reference the
BMP file
• Only GRI and GRD are essential – because the other two derived from them and does not contain data
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Image file
• Image files are special kind of grids that can be displayed but not used for analysis, as the data associated with the different colours in the file are not accessible
• An example of such file – air photo or satellite image
• DIVA-GIS supports three formats for images – TIFF, JPEG and SID
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Country Boundary
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Province boundary
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District boundary
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Gazet (localities) shape file
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Soil types of Sri Lanka
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Cowpea collections in Sri Lanka
Observation:
Most of the collections are from road side
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Cowpea collections from Sri Lanka
Mapping of:
•Roads
•Rivers
•Rail
•Cowpea collections
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Database Information
Climatic Information
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Diversity analysis for flowering days for cowpea collections
Highest diversity
Low diversity areas
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GIS Application for PGR management
Pearl millet collections from major climatic zones of India
• Most collections are from arid and semi-arid
• Few collections from sub-humid - dry as well as wet
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GIS Application for PGR management
Climate for pearl milleting collecting sites in India
0
5
10
15
20
25
30
35
40
45
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Months
Te
mp
era
ture
(0
C)
0
50
100
150
200
250
Ra
infa
ll (m
m)
Min. temp. Max. temp. Rainfall
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GIS Application for PGR management
Comparison of minimum temperature for pearl millet cropped area and collecting sites in India
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Months
Tem
per
atu
re (
0C
)
Min. temp.-coll Min.temp-crop
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http://www.spacemart.com/reports/African_Wetland_Managers_Armed_With_New_Technology.html
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http://www.vterrain.org/
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3D Models
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http://www.csi.cgiar.org
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http://edcwww.cr.usgs.gov/earthshots/slow/tableofcontents
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Conclusion• This is not the end of analysis• You may have several other out puts
using these GIS tools• Provided:
– You have better database on collecting sites
– Good and complete information of characterization
• This will help you in providing guidelines for:– Planning future collecting– Matching sites for introduction– Potential sites for area expansion under
forest plantation/conservation – Identification of suitable varieties for its
environmental conditionsTHANKS