Use of remote sensing in
combination with statistical survey
methods in the production of
agricultural, land use and other
statistics
Current applications and future possibilities
Jeffrey Smith, Agriculture Division, Statistics Canada
Frédéric Bédard, Agriculture Division, Statistics Canada
Richard Dobbins, Agriculture Division, Statistics Canada
June 11, 2009
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June 2009
Outline
 Introduction
 Prince Edward Island Potato/Agricultural Land Area
Estimate and Classification System (PACS)
• Approach
• Results
• Discussion
 Other Possible Uses for this Type of Methodology
 Thoughts on Use in Developing Countries
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Introduction
A
PEI
A
Canada's agricultural land, 2006
Le territoire agricole du Canada, 2006
2006 agricultural ecumene
Écoumène agricole, 2006
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Non-agricultural area
Région non agricole
Major Lakes
Lacs principaux
B
Census division boundary
Limite de division de recensement
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B
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Introduction
 PEI Department of Agriculture asked for a study
on improving
• Estimates of potato area
• Estimates of total agricultural land
• Land cover/use classification for the whole province
 Why potatoes in particular?
• PEI total FCR1 in 2008:
• PEI crop FCR in 2008:
• PEI potato FCR in 2008:
1
$390.3 million
$242.0 million
$200.9 million
Farm Cash Receipts
 Project conducted in 2006, 2007, 2008
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PACS – Approach -
Overview
 Key Success Criteria
• Precision
• Objectivity
• Timeliness
 Statistical Component
• Entire Island delineated with small “cells”
• Stratified sample design
• Estimation and statistical quality assurance
 Phase A – preliminary estimates
• Ground truth data collection by roadside and aerial observation
• Area and precision estimates for potatoes and total agriculture land
 Phase B - land-cover/crop classification
• Province-wide land-cover/crop classification from analysis of
satellite images (map in GIS format)
• Improved area and precision estimate at province level for potatoes
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PACS - Approach –
Design Aspect
Sample unit (cell) size
Number of cells to cover province
Sample size (number of cells)
Total area in sample (km2)
Number of fields in sample cells
Portion of province in sample (%)
Number of strata
Stratification variable(s)
Allocation of sample to strata
Largest sampling weight
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Sample design
2006
2 km x 3 km
1,217
147
882
4,700
15.6
6
Year
2007
1 km x 1 km
6,546
360
360
5,230
6.4
5
Total area in
Average % of
potatoes, grain, area in potatoes
hay and pasture in
in 2000 and
2000
2006
equal
29.4
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proportional to
variance
206.5
2008
1 km x 2 km
3,387
202
404
4,273
7.1
5
Average % of
area in
agriculture
in 2006 and
2007
proportional to
variance
29.95
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PACS - Approach –
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Selected cells
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PACS – Approach –
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Ground collection
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PACS – Approach –
Satellite imagery
SPOT 5
LANDSAT 5
SPOT 4
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PACS - Approach –
Image acquisition
SUMMER 2008 IMAGES
SPRING 2008 IMAGES
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PACS - Approach -
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Regions
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PACS - Approach –
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Raw and classified
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PACS – Approach –
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Regression estimation
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PACS – Results –
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Classification map
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PACS - Results –
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Area estimates
Classification
Category
Potatoes
Grains
Hay/Pasture/Forage/Grass
Corn
Soybeans
Canola
Fallow
Other Crops
Forest
Urban/bare soil
2006
hectares
38,700
59,700
168,900
1,700
2,700
na
1,700
1,600
277,700
13,500
2007
hectares
40,200
67,000
156,400
2,200
4,300
na
800
4,000
276,700
14,600
2008
hectares
37,500
53,100
175,800
3,700
6,300
600
200
1,500
273,100
14,400
Total (CEAG)
566,200
566,200
566,200
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PACS - Results –
Accuracy matrix
% of areas in Class classified to:
Agriculture
Other
1
Class
Potatoes Grain H/P/F/G Corn Soybeans crops Fallow Canola Other2
Potatoes
87.0
2.9
7.4 0.3
1.9
0.1
0.0
0.0
0.3
Grain
0.4 88.0
10.0 0.1
0.5
0.1
0.0
0.0
0.9
1
H/P/F/G
2.0
3.8
93.5 0.1
0.2
0.0
0.0
0.0
0.4
Corn
0.8
7.8
8.3 82.3
0.6
0.0
0.0
0.0
0.1
Soybeans
6.6
1.4
8.3 0.7
82.6
0.3
0.0
0.0
0.2
Other crops
6.0
4.8
25.5 0.1
0.7 60.4
1.6
0.0
0.8
Fallow
4.2
0.3
21.4 0.0
0.0
0.0
74.1
0.0
0.0
Canola
1.9
4.4
0.8 0.3
8.4
0.1
0.0
84.2
0.0
1
2
Hay/Pasture/Forage/Grass
Other non-agriculture classes
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PACS - Results –
Potato area estimates
Estimates of PEI Potato Area (hectares, CV in % for PACS)
2006
2007
2008
Estimate
Seeded Harvested Seeded Harvested Seeded Harvested
PACS Prelima
38,350
35,666
33,144
PACSb
Census of
Agriculturec
22-008-Xd
(6.1%)
(9.1%)
(7.7%)
38,700
40,200
37,460
(1.6%)
(3.4%)
(1.9%)
39,512
39,499
38,770
38,851
38,851
37,435
36,018
a
Potato/Agricultural Land Area Estimate and Classification System study, released in August each year
Potato/Agricultural Land Area Estimate and Classification System study, released in September each year
c
Released May 16, 2007
d
Canadian Potato Production, figures from issue no. 2, released in November each year
b
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Discussion
 Potato area estimates very much improved in
precision and available earlier
 Classification accuracy reasonably good, but
somewhat hampered by cloud in some regions in
some years
 Evolving the design of the ground truth data phase
helped to improve the results
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Other Possible Uses
 Other geographical areas
 Measure or monitor environmental practices
• Crop rotation
• Buffer zones
• Shelterbelts
 Urban or settled area studies
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Other Possible Uses -
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Charlottetown
June 2009
Other Possible Uses -
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Summerside
June 2009
Other Possible Uses
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Other Possible Uses –
“Settlements”
Edmonton:
CMA,UA
and draft
settlement
boundaries
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Other Possible Uses –
“Settlements”
Edmonton:
UA and draft
settlement
boundaries
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Other Possible Uses –
“Settlements”
Edmonton Population Density Results
Population
Area
(km2)
Population Density
(people per km2)
CMA
937 845
9 418
100
UA
782 100
849
920
658 374 to
660 780
341 to 411
1 610 to 1 930
Settlement
(draft – range
depends on rules
applied)
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Thoughts on Use in Developing
Countries
 Does not rely on traditional survey-taking infrastructure
 No burden on farmers
 Collection of ground truth data is straightforward, fairly
fast and not expensive; uses road and air
 Satellite imagery is inexpensive and many options
available depending on particular requirement
 Interpretation expertise available
 Overall cost is not excessive
 Weather may affect quality, but new sensors should
solve this problem (e.g., RADARSAT-2)
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Questions / Discussion
Jeffrey Smith, Assistant Director
Agriculture Division, Statistics Canada
Jean Talon Building Floor 12 C-8
170 Tunney's Pasture Driveway, Ottawa ON K1A 0T6
Jeffrey.Smith@statcan.gc.ca
Tel. 613-951-6821
Fax 613-951-6454
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