2802 REMOTE SENSING INDICATORS FOR CROP GROWTH MONITORING AT DIFFERENT SCALES.ppt
- 1. REMOTE SENSING INDICATORS FOR CROP GROWTH MONITORING AT DIFFERENT SCALES Zongnan Li 1, 2 and Zhongxin Chen 1, 2* 1 Key Laboratory of Resources Remote Sensing and Digital Agriculture, MOA, Beijing 100081 2 Institute of Agricultural Resources and Regional Planning, CAAS, Beijing 100081 IGARSS 2011, Vancouver, 24-29 July, 2011
- 2. Outline Ⅰ . INTRODUCTION Ⅱ . DATA AND PROCESS Ⅲ . RESULT &DISCUSSION Ⅳ . CONCLUSION
- 3. Ⅰ . INTRODUCTION Crop growth is critical agricultural information. It can be used in the scientific management of crop and agricultural practice. It is also important in yield estimation and prediction There are several methods for crop growth monitoring, including in-situ field agronomic method, crop growth diagnostic model, and remote sensing method Remote sensing indicators are widely useed in vegetation monitoring Vegetation indices (VIs)are still the important indicators for regional crop growth monitoring
- 4. Problem with VIs’ application Some VIs are sensitive to the soil background and non-vegetation fraction The scale effect —— different spatial resolutions —— spatial heterogeneity of land surface
- 5. Research Objectives Through testing the relationship between VIs and crop growth parameters, to investigate if there is/are optimal crop growth monitoring indicators at canopy scale and regional scale for different crop phenological stages if there are any trends for the relationship between VIs and crop growth parameters at different spatial scales
- 6. field experiment canopy spectra crop parameters crop yield HJ-1 Imagery LAI in-situ Geom. Correction Atmos. Correction VIs VIs Correlation analysis Relationsip between VIs and crop growth VIs at different scales scaling up Correlation analysis LAI regional Relationsip between VIs and LAI at different scales
- 7. Ⅱ . DATA AND PROCESS research region
- 8. Field experiment plots in Langfang (116°36′E, 39°36′N). Regional study in Hebei province
- 9. Ⅱ . DATA AND PROCESS Field experiment and observation 5 levels for N fertilizer treatments; 4 times repeat N application treatments: N1- 0; N2- 15kg/ha; N3- 45 kg/ha; N4- 105 kg/ha; N5- 225kg/ha
- 10. Ⅱ . DATA AND PROCESS Field experiment and observation canopy spectra, LAI, foliar chlorophyll, plant hight, coverage and biomass were measured at 5 phenological stages on 3/30, 4/14, 4/24, 5/5 and 5/17, 2009. Canopy spectra Canopy LAI Chlorophyll SPAD
- 11. Ⅱ . DATA AND PROCESS Field experiment and observation early elongation stage jointing stage heading stage milk stage
- 12. LAI evolution for various N applications
- 13. HJ-1A CCD Image 3/25/2009 HJ-1A CCD Image 4/21/2009 Specification Bands (μm) Blue:0.43-0.52 Green:0.52-0.60 Red:0.63-0.69 infrared: 0.76-0.90 Swath 360×360km Resolution 30m
- 14. Ⅱ . DATA AND PROCESS Caculation of VIs & Correlation analysis
- 15. Ⅱ . DATA AND PROCESS Processing of HJ-1 multi-spectral images
- 16. Ⅱ . DATA AND PROCESS LAI Inversion (Beer’s law) where K NDVI =0.29 NDVI ∞ =0.97 NDVI s =0.11
- 17. LAI in study region March 25 (elongation) April 21 (heading)
- 18. High crop cover Low crop cover Canopy
- 19. Ⅲ . RESULT &DISCUSSION Remote sensing indicators for crop growth at canopy scale (sample sizes =20) Date and Crop Stages 2009-3-30 2009-4-14 2009-5-5 2009-5-17 early elongation stage jointing stage heading stage milk stage NDVI 0.5173 * 0.8462 ** 0.8778 ** 0.9068 ** PVI 0.5484 * 0.6612 ** 0.7033 ** 0.8165 ** SAVI(L=0.1) 0.5060 * 0.8447 ** 0.8146 ** 0.8993 ** SAVI(L=0.2) 0.5494 * 0.8507 ** 0.7815 ** 0.8857 ** SAVI(L=0.3) 0.5680 * 0.8229 ** 0.7544 ** 0.8857 ** SAVI(L=0.5) 0.5504 * 0.8191 ** 0.7416 ** 0.8737 ** MSAVI 0.5504 * 0.8191 ** 0.7484 ** 0.8677 ** EVI 0.5504 * 0.8236 ** 0.7379 ** 0.8361 **
- 20. Ⅲ . RESULT &DISCUSSION Remote sensing indicators for crop growth at regional scales Low crop cover/the sample sizes n=30. good but no obvious trend Date 2009-3-25 early elongation stage 2009-4-21 heading stage Resolution 240m 480m 960m 240m 480m 960m PVI 0.9288 0.9362 0.9440 0.9592 0.9357 0.9536 SAVI(L=0.1) 0.9431 0.9504 0.9723 0.9697 0.9643 0.9665 SAVI(L=0.3) 0.9514 0.9486 0.9746 0.9689 0.9654 0.9686 SAVI(L=0.5) 0.9472 0.9474 0.9722 0.9689 0.9638 0.9700 MSAVI 0.9440 0.9446 0.9714 0.9685 0.9621 0.9674 EVI 0.9262 0.9582 0.9472 0.9400 0.9361 0.9499
- 21. Ⅲ . RESULT &DISCUSSION Remote sensing indicators for crop growth at regional scales High crop cover/the sample sizes n=30. Date 2009-3-25 early elongation stage 2009-4-21 heading stage Resolution 240m 480m 960m 240m 480m 960m PVI 0.9261 0.9450 0.9799 0.5750 0.6512 0.7261 SAVI(L=0.1) 0.9536 0.9816 0.9943 0.9437 0.9512 0.9519 SAVI(L=0.3) 0.9456 0.9726 0.9898 0.8247 0.8349 0.8936 SAVI(L=0.5) 0.9394 0.9671 0.9888 0.7209 0.8006 0.8284 MSAVI 0.9408 0.9651 0.9877 0.7784 0.8260 0.8770 EVI 0.9125 0.9463 0.9639 0.7932 0.8072 0.8598
- 22. Ⅳ . CONCLUSION At canopy scale, SAVI with different L values are suitable for winter wheat growth monitoring. At regional scale, soil –adjusted vegetation indices have limitations in dense crop coverage. For dense crop coverage, the relationship between VIs improve with the increased pixel size, But this trend is not obvious for low crop coverage.
- 23. Acknowledgements The research was supported by the MOA 948 program project with contract no. 2010-S2 and 2009-Z31, and international corporation project from MOST(Ministry of Science and Technology of China ) with contract no. 2010DFB10030.
- 24. Thanks for your attention !