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Integrating Remote Sensing and Statistical Methods for Agricultural Statistics Enhancement

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27 diapositives · 429 Views · Aug 23, 2014

This paper explores the combination of remote sensing technology and statistical survey methods in the production of agricultural statistics, specifically in land use and crop area estimates. The case study in Prince Edward Island demonstrates improved accuracy in potato area estimates using a dual-phase approach, involving ground truth data collection and satellite imagery analysis. The findings highlight significant advancements in precision and timeliness of agricultural statistics, offering insights for both developed and developing countries in agricultural data collection and analysis.

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  1. 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 Wye City Group

  2. 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 Outline Wye City Group

  3. Introduction PEI Wye City Group

  4. 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 Introduction Wye City Group

  5. 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 PACS – Approach - Overview Wye City Group

  6. PACS - Approach – Sample design Wye City Group

  7. PACS - Approach – Selected cells Wye City Group

  8. PACS – Approach – Ground collection Wye City Group

  9. PACS – Approach – Satellite imagery SPOT 5 LANDSAT 5 SPOT 4 Wye City Group

  10. PACS - Approach – Image acquisition SUMMER 2008 IMAGES SPRING 2008 IMAGES Wye City Group

  11. PACS - Approach - Regions Wye City Group

  12. PACS - Approach – Raw and classified Wye City Group

  13. PACS – Approach – Regression estimation Wye City Group

  14. PACS – Results – Classification map Wye City Group

  15. PACS - Results – Area estimates Wye City Group

  16. PACS - Results – Accuracy matrix Wye City Group

  17. PACS - Results – Potato area estimates Wye City Group

  18. 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 Discussion Wye City Group

  19. Other geographical areas Measure or monitor environmental practices Crop rotation Buffer zones Shelterbelts Urban or settled area studies Other Possible Uses Wye City Group

  20. Other Possible Uses - Charlottetown Wye City Group

  21. Other Possible Uses - Summerside Wye City Group

  22. Other Possible Uses Wye City Group

  23. Other Possible Uses – “Settlements” Edmonton: CMA,UA and draft settlement boundaries Wye City Group

  24. Other Possible Uses – “Settlements” Edmonton: UA and draft settlement boundaries Wye City Group

  25. Other Possible Uses – “Settlements” Edmonton Population Density Results Wye City Group

  26. 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) Wye City Group

  27. 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 Wye City Group