june 2009 wye city group 1 use of remote sensing in combination with statistical survey methods in...
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June 2009Wye City Group1
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 CanadaFrédéric Bédard, Agriculture Division, Statistics Canada
Richard Dobbins, Agriculture Division, Statistics Canada
June 11, 2009
June 2009Wye City Group2
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
June 2009Wye City Group3
Introduction
Le territoire agricole du Canada, 2006Canada's agricultural land, 2006
A
B
A
B
Non-agricultural areaRégion non agricole Limite de division de recensement
Census division boundary2006 agricultural ecumeneÉcoumène agricole, 2006
Major LakesLacs principaux
PEI
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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: $390.3 million • PEI crop FCR in 2008: $242.0 million• PEI potato FCR in 2008: $200.9 million
1 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 – Sample design
Year Design Aspect 2006 2007 2008
Sample unit (cell) size 2 km x 3 km 1 km x 1 km 1 km x 2 km Number of cells to cover province 1,217 6,546 3,387 Sample size (number of cells) 147 360 202 Total area in sample (km2) 882 360 404 Number of fields in sample cells 4,700 5,230 4,273 Portion of province in sample (%) 15.6 6.4 7.1 Number of strata 6 5 5 Stratification variable(s)
Total area in potatoes, grain,
hay and pasture in 2000
Average % of area in potatoes
in 2000 and 2006
Average % of area in
agriculture in 2006 and
2007 Allocation of sample to strata
equal proportional to
variance proportional to
variance Largest sampling weight 29.4 206.5 29.95
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PACS - Approach – Selected cells
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PACS – Approach – Ground collection
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PACS – Approach – Satellite imagery
SPOT 4
SPOT 5
LANDSAT 5
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PACS - Approach – Image acquisition
SPRING 2008 IMAGES
SUMMER 2008 IMAGES
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PACS - Approach - Regions
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PACS - Approach – Raw and classified
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PACS – Approach – Regression estimation
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PACS – Results – Classification map
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PACS - Results – Area estimates
2006 2007 2008 Classification Category hectares hectares hectares
Potatoes 38,700 40,200 37,500 Grains 59,700 67,000 53,100
Hay/Pasture/Forage/Grass 168,900 156,400 175,800 Corn 1,700 2,200 3,700
Soybeans 2,700 4,300 6,300 Canola na na 600 Fallow 1,700 800 200
Other Crops 1,600 4,000 1,500 Forest 277,700 276,700 273,100
Urban/bare soil 13,500 14,600 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 Class Potatoes Grain H/P/F/G1 Corn Soybeans
Other 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
H/P/F/G1 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 Hay/Pasture/Forage/Grass 2 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 (6.1%) 35,666
(9.1%) 33,144 (7.7%)
PACSb 38,700 (1.6%)
40,200 (3.4%)
37,460 (1.9%)
Census of Agriculturec
39,512
22-008-Xd 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 b 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
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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 - Charlottetown
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Other Possible Uses - Summerside
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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”
Population Area
(km2)
Population Density (people per km2)
CMA 937 845 9 418 100
UA 782 100 849 920
Settlement (draft – range depends on rules applied)
658 374 to
660 780
341 to 411 1 610 to 1 930
Edmonton Population Density Results
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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 DirectorAgriculture Division, Statistics Canada
Jean Talon Building Floor 12 C-8 170 Tunney's Pasture Driveway, Ottawa ON K1A 0T6
[email protected] Tel. 613-951-6821 Fax 613-951-6454