Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Forecasting Wheat Yield and
Production for Punjab Province,
Pakistan from Satellite Image
Time Series
Jan Dempewolf, Inbal...
Pakistan: Strengthening Provincial Capacity
(USDA funded, collaboration between USDA, FAO, SUPARCO, CRS Pakistan, & UMD)

...
GLAM-Pakistan Agricultural Monitoring System
Food Crop Production in Pakistan
Winter Season (Rabi) % of Total
Vegetables
5%

Other
5%

Fruits
9%

Potatoe
11%

Wheat
70...
Total wheat dry matter and NDVI in Maryland, USA
(Tucker et al., 1981)

Tucker, C. J., B. N. Holben, J.
H. Elgin Jr, and J...
Wheat yield and AVHRR-NDVI integrated over the
growing season in Montana, USA (Labus et al., 2002)

Labus, M. P., G. A. Ni...
Reported wheat yield and predicted yield from
MODIS-NDVI in Shandong, China (Ren et al., 2008)

Ren, J., Z. Chen, Q. Zhou,...
MODIS-NDVI and Wheat Yield in Kansas, USA
(Becker-Reshef et al., 2010)
Daily Normalized Difference Vegetation Index (NDVI
...
Wheat Mask and Area from 250 m MODIS
Multi-Temporal Landsat
1. Early growing season
2. Height of growing season
3. After h...
Visual Interpretation of Wheat Areas
Early Season
(8. Feb. 2012)
Landsat-7 ETM
scene for
Punjab
Band
combination 45-3 (gre...
Visual Interpretation of Wheat Areas
Near Peak
(24. Feb. 2012)
Landsat-7 ETM
scene for
Punjab
Band
combination
4-5-3 (gree...
Visual Interpretation of Wheat Areas
Harvest
(4. Apr. 2012)
Landsat-7 ETM
scene for
Punjab
Band
combination 45-3 (green
ve...
Select Wheat Training Areas
Training
(12. Apr. 2012)
Landsat-7 ETM
scene for
Punjab
Band
combination
4-5-3 (green
vegetati...
Classify for Wheat Areas
Classification
(12. Apr. 2012)
Landsat-7 ETM
scene for
Punjab
Band
combination
4-5-3 (green
veget...
Wheat Mask
Classification
(Rabi 2012)
Landsat-7
ETM scene
for Punjab
Band
combination
4-5-3 (green
vegetation
appears red)
Landsat Training Scenes for Wheat Area
Pakistan

Landsat
training
scenes

Sindh

WRS2
Path/Row
Grid
Wheat Mask and Area from 250 m MODIS
Multi-Temporal Landsat
1. Early growing season
2. Height of growing season
3. After h...
Wheat Mask and Area from 250 m MODIS
Multi-Temporal Landsat
1. Early growing season
2. Height of growing season
3. After h...
Wheat Mask and Area from 250 m MODIS
Multi-Temporal Landsat
1. Early growing season
2. Height of growing season
3. After h...
Wheat Mask and Area from 250 m MODIS
Multi-Temporal Landsat
1. Early growing season
2. Height of growing season
3. After h...
Percent Wheat
for Punjab
Province Rabi
Season
2010/11

Derived from
MODIS 250 m
8-day
composite
surface
reflectance
time s...
Wheat Yield and Production Forecast
Percent wheat
per pixel

MODIS 8-day
composites

Select 20%
highest density
wheat pixe...
Timing of Forecast and Number of Training Years for
Punjab Province, Pakistan, 2010/11 Rabi Season

R2, RMSE at the distri...
Performance of Vegetation Indices for Forecasting
Wheat Yield for the 2010/11 and 2011/12 Rabi Seasons
NDVI

VCI

WDRVI

S...
Forecast Wheat Production per District for
Punjab Province, Pakistan, Seasons 2008/09 to 2011/12
2008/09

2010/11

2009/10...
Remote Sensing Applications for
Smallholder Farming Systems in Tanzania
(Proposed Project)
Explore feasible pathways to us...
Primary Use-Case Challenges
1.

2.

3.

4.

5.

Whether, how, and with which datasets can we
produce national-scale cropla...
Remote Sensing Systems
MODIS

Satellite Time
Series Pipeline
and Archive

Landsat
RapidEye/
PlanetLabs
UAV
Field Data
Test...
Thank You!
Upcoming SlideShare
Loading in …5
×

Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Satellite Image Time Series

2,280 views

Published on

Remote sensing –Beyond images
Mexico 14-15 December 2013

The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

Published in: Education, Technology
  • Be the first to comment

Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Satellite Image Time Series

  1. 1. Forecasting Wheat Yield and Production for Punjab Province, Pakistan from Satellite Image Time Series Jan Dempewolf, Inbal Becker-Reshef, Bernard Adusei, Matt Hansen, Peter Potapov, Brian Barker, Chris Justice Department of Geographical Sciences University of Maryland, United States Beyond Diagnostics: Insights and Recommendations from Remote Sensing Workshop at CIMMYT 2013 in Texcoco, Mexico 14-15 December 2013
  2. 2. Pakistan: Strengthening Provincial Capacity (USDA funded, collaboration between USDA, FAO, SUPARCO, CRS Pakistan, & UMD) Training Workshops
  3. 3. GLAM-Pakistan Agricultural Monitoring System
  4. 4. Food Crop Production in Pakistan Winter Season (Rabi) % of Total Vegetables 5% Other 5% Fruits 9% Potatoe 11% Wheat 70% Data source: Crop Reporting Service of the Government of Punjab, Pakistan, www.agripunjab.gov.pk
  5. 5. Total wheat dry matter and NDVI in Maryland, USA (Tucker et al., 1981) Tucker, C. J., B. N. Holben, J. H. Elgin Jr, and J. E. McMurtrey III. “Remote Sensing of Total Dry-matter Accumulation in Winter Wheat.” Remote Sensing of Environment 11 (1981): 171–189.
  6. 6. Wheat yield and AVHRR-NDVI integrated over the growing season in Montana, USA (Labus et al., 2002) Labus, M. P., G. A. Nielsen, R. L. Lawrence, R. Engel, and D. S. Long. “Wheat Yield Estimates Using Multitemporal NDVI Satellite Imagery.” International Journal of Remote Sensing 23, no. 20 (January 2002): 4169–4180.
  7. 7. Reported wheat yield and predicted yield from MODIS-NDVI in Shandong, China (Ren et al., 2008) Ren, J., Z. Chen, Q. Zhou, and H. Tang. “Regional Yield Estimation for Winter Wheat with MODIS-NDVI Data in Shandong, China.” International Journal of Applied Earth Observation and Geoinformation 10, no. 4 (December 2008): 403–413.
  8. 8. MODIS-NDVI and Wheat Yield in Kansas, USA (Becker-Reshef et al., 2010) Daily Normalized Difference Vegetation Index (NDVI from MODIS) 2000-2008, Harper County Blue numbers are Yield (MT/Ha) Winter Wheat emergence NDVI peak 2.35 Winter Wheat seasonal NDVI peak 2.69 3.36 2.54 2.49 2.49 2.21 1.61 1.4 8 Year Strong correlation between NDVI Peak and yield Becker-Reshef, I., E. Vermote, M. Lindeman, and C. Justice. “A Generalized Regression-based Model for Forecasting Winter Wheat Yields in Kansas and Ukraine Using MODIS Data.” Remote Sensing of Environment 114, no. 6 (2010): 1312–1323.
  9. 9. Wheat Mask and Area from 250 m MODIS Multi-Temporal Landsat 1. Early growing season 2. Height of growing season 3. After harvest Classify Landsat • • Select training data visually Bagged decision trees
  10. 10. Visual Interpretation of Wheat Areas Early Season (8. Feb. 2012) Landsat-7 ETM scene for Punjab Band combination 45-3 (green vegetation appears red)
  11. 11. Visual Interpretation of Wheat Areas Near Peak (24. Feb. 2012) Landsat-7 ETM scene for Punjab Band combination 4-5-3 (green vegetation appears red)
  12. 12. Visual Interpretation of Wheat Areas Harvest (4. Apr. 2012) Landsat-7 ETM scene for Punjab Band combination 45-3 (green vegetation appears red)
  13. 13. Select Wheat Training Areas Training (12. Apr. 2012) Landsat-7 ETM scene for Punjab Band combination 4-5-3 (green vegetation appears red)
  14. 14. Classify for Wheat Areas Classification (12. Apr. 2012) Landsat-7 ETM scene for Punjab Band combination 4-5-3 (green vegetation appears red)
  15. 15. Wheat Mask Classification (Rabi 2012) Landsat-7 ETM scene for Punjab Band combination 4-5-3 (green vegetation appears red)
  16. 16. Landsat Training Scenes for Wheat Area Pakistan Landsat training scenes Sindh WRS2 Path/Row Grid
  17. 17. Wheat Mask and Area from 250 m MODIS Multi-Temporal Landsat 1. Early growing season 2. Height of growing season 3. After harvest Classify Landsat • • Select training data visually Bagged decision trees Aggregate to 250 m resolution
  18. 18. Wheat Mask and Area from 250 m MODIS Multi-Temporal Landsat 1. Early growing season 2. Height of growing season 3. After harvest Classify Landsat • • Select training data visually Bagged decision trees Aggregate to 250 m resolution MODIS 250 m surface reflectance 8day composites time series bands 1, 2, 5, 7 (red, nir, swir, therm) 1. 1. Dec. – 26th Feb. 2. QA Filter (clouds, etc.) 3. Calculate NDVI
  19. 19. Wheat Mask and Area from 250 m MODIS Multi-Temporal Landsat 1. Early growing season 2. Height of growing season 3. After harvest MODIS 250 m surface reflectance 8day composites time series bands 1, 2, 5, 7 (red, nir, swir, therm) 1. 1. Dec. – 26th Feb. 2. QA Filter (clouds, etc.) 3. Calculate NDVI Classify Landsat • • Select training data visually Bagged decision trees Aggregate to 250 m resolution Convert to 588 metrics per season • • • 0th, 10th, 25th, 50th, 75th, 90th, 100th percentiles Means of sequential percentiles and their differences Band values ranked by other bands
  20. 20. Wheat Mask and Area from 250 m MODIS Multi-Temporal Landsat 1. Early growing season 2. Height of growing season 3. After harvest MODIS 250 m surface reflectance 8day composites time series bands 1, 2, 5, 7 (red, nir, swir, therm) 1. 1. Dec. – 26th Feb. 2. QA Filter (clouds, etc.) 3. Calculate NDVI Classify Landsat • • Select training data visually Bagged decision trees Aggregate to 250 m resolution Classify MODIS time series • Bagged decision trees Convert to 228 metrics per season • • • 0th, 10th, 25th, 50th, 75th, 90th, 100th percentiles Means of sequential percentiles and their differences Band values ranked by other bands Percent wheat per 250 m pixel for Punjab Province
  21. 21. Percent Wheat for Punjab Province Rabi Season 2010/11 Derived from MODIS 250 m 8-day composite surface reflectance time series
  22. 22. Wheat Yield and Production Forecast Percent wheat per pixel MODIS 8-day composites Select 20% highest density wheat pixels Calculate spatial average of NDVI, weighted by percent wheat Regression estimator of pixel counts against reported area Multiply area forecast with yield forecast to obtain production forecast Historic reported yield Regression-based wheat model yield against 95th NDVI percentile
  23. 23. Timing of Forecast and Number of Training Years for Punjab Province, Pakistan, 2010/11 Rabi Season R2, RMSE at the district level and deviation (D) at the province level of forecast versus reported yield for the 2010/11 Rabi season. Left: Changes through the cropping season. Right: Number of training years.
  24. 24. Performance of Vegetation Indices for Forecasting Wheat Yield for the 2010/11 and 2011/12 Rabi Seasons NDVI VCI WDRVI SANDVI
  25. 25. Forecast Wheat Production per District for Punjab Province, Pakistan, Seasons 2008/09 to 2011/12 2008/09 2010/11 2009/10 2011/12
  26. 26. Remote Sensing Applications for Smallholder Farming Systems in Tanzania (Proposed Project) Explore feasible pathways to use remote sensing tools for smallholder agriculture:      Improve crop condition monitoring by the National Food Security Office (NFSO). Produce current cropland extent core dataset. Support agricultural extension through Sokoine University. Monitor crop condition of smallholder agricultural areas. Assess distribution of smallholder cropping systems and crop types.
  27. 27. Primary Use-Case Challenges 1. 2. 3. 4. 5. Whether, how, and with which datasets can we produce national-scale cropland layers for smallholder agriculture? How can smallholder agricultural fields be sampled and monitored through remote sensing? How can agricultural areas be monitored at the national scale in near-realtime? How can we inform decision makers? What are the pathways to reach smallholder farmers?
  28. 28. Remote Sensing Systems MODIS Satellite Time Series Pipeline and Archive Landsat RapidEye/ PlanetLabs UAV Field Data Test Sites ( ) Time Series (one season) Groundtruth landcover and land-cover dynamics Rela ve NDVI / Crop Condi on at MODIS and Landsat resolu on Prototype of Agricultural Areas Base Map (Cropland Mask) Methodologies for classifying • Cropland • Maize produc on systems
  29. 29. Thank You!

×