1. Term Project Presentation
Data Integration for observing LAI and Soil Moisture Patterns in Walnut Creek, Ames, Iowa
Bushra Zaman
GIS in Water Resources
Term Project Presentation
11/27/2007

2. Motivation
The Paper on “Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery”, M.C. Anderson1, C.M.U. Neale2, F. Li3, J.M. Norman1, W.P. Kustas3, H. Jayanthi2, and J.Chavez2
The Regression Equations developed in the paper have been used in this project.

3. Various Sources of Information
Satellite Imagery
Aerial Imagery
Ground Measurements

4. Study Area SMEX 2002 - Walnut Creek Watershed, Ames, Iowa.
Spatial coverage °N °N & 93.2°W °W.
Temporal Coverage - Over a one month period between mid-June and mid-July.
In situ data was collected within the small-scale intensive Watershed domain.
This agricultural region consisted primarily of Corn and Soybeans in large homogeneous fields.

5. Pattern of the Study Area
Plus a Network of Roads !!

6. Objectives
Use the existing models with Airborne and Satellite Imagery to create Spatial LAI layers.
To match these layers to the Soil moisture ground measurements.
To interpolate precipitation data for various stations in the area within the GIS. To compare the interpolated precipitation to the soil moisture pattern at that location.

7. Analysis
Precipitation data obtained for 22 Stations within the study area. Four other records for that period were obtained through DAYMET and one through SCAN.
The Geotiff Image from the Landsat TM for 6th June was imported into ERDAS Imagine and changed to .img files which are finally being used in ARcGIS. The other dates were obtained in proper format. (Thanks to Dr. Neale!)
All the images and shapefiles were projected into the NAD83 Geographic Coordinate System.

8. Leaf Area Index
The Leaf Area Index or LAI is the ratio of total upper leaf surface of vegetation divided by the surface area of the land on which the vegetation grows.
The LAI is a dimensionless value [m2/m2], typically ranging from 0 for bare ground to 6 for a dense forest.

9. Results
A New Toolbox is Created and Models are Built for NDWI/LAI and NDVI.
Spatial LAI – Obtained through Regression model
Temporal Variation of Leaf Area Index
Interpolation of Precipitation through Kriging
Effect of Rain on Soil Moisture
Saturation of NDVI
Variation of Soil Moisture with LAI on Site WC03

10. LandSat Image for 8th July 2002 (RED, NIR and SWIR Bands)

11. Models for NDVI,NDWI and LAI using ArcGIS
Model for NDVI

12. Models for NDVI, NDWI & LAI using Imagine
For Cross Checking !!

13. Equations Used Regression Equation for LAI
Where, y = LAI, and a = 2.88; b=1.14; c=0.104; d = 4.1 (Ref:Anderson, M. C., Neal, C. M. U., Li, F., Norman, J. M., Kustas, W. P., Jayanthi, H., & Chavez, J. (2004). Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sensing of Environment. pii:S (04) )
Vegetation Indices NDWI = NIR-SWIR/NIR+SWIR NDVI = NIR – RED/NIR + RED

14. Spatial LAI S
0.89 S
2.86 C C S S
1.44
1.19
4.65
2.12 C C
1.64
4.92
LAI – 06/23/2002
LAI – 07/08/2002

15. Temporal Variation of Leaf Area Index
Corn Sites
Soybean Sites

16. Interpolated Precipitation (8th July 2002) Method Used - Kriging

17. Effect of Rain on Soil Moisture (8th July 2002)
Soybean Sites
Corn Sites

18. Effect of Rain on Soil Moisture (at 30cm depth)

19. Saturation of NDVI

20. Variation of Soil Moisture with LAI on Site WC03
07/08/02
06/23/02
07/01/02

21. References
[1] Anderson, M. C., Neal, C. M. U., Li, F., Norman, J. M., Kustas, W. P., Jayanthi, H., & Chavez, J. (2004). Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sensing of Environment. pii:S (04)
[2] Douglas Ramsey. Remote Sensing and GIS Laboratory, Utah State Univeristy, 2003. 
[3] Ray, S.S., Wadhwal,V.K., 2001,Estimation of crop evapotranspiration of irrigation command area using remote sensing and GIS, Agricultural Water Management,49:
[4] Anderson, M., SMEX02 Watershed Vegetation Sampling Data, Walnut Creek, Iowa. Boulder, CO: National Snow and Ice Data Center. Digital media.
[5] Crosson,W.L.,Limaye, A.S.,and Laymon C.A., 2005,Member, IEEE Parameter Sensitivity of Soil Moisture Retrievals From Airborne C- and X-Band Radiometer Measurements in SMEX02, IEEE Transactions On Geoscience And Remote Sensing, 43(12): ,
[6] Document URL: Napolitano R. et al.(2001). Data Integration for Leaf Area Index Prediction in Function of Land Cover Change. “Decision Support System for Sustainable ECOsystem MANagement in Atlantic Rain Forest Rural Areas (ECOMAN)”. Contract Nº ICA4-CT

22. Data Sources

23. Thank you !
Questions ?