Title: Crop Biomass Estimation with NRT MODIS Data and Early Results of a Total Crop Area Algorithm
1- Crop Biomass Estimation with NRT MODIS Data and
Early Results of a Total Crop Area Algorithm - Integrated remote sensing technologies for
improved farm management - Dr Andrew P. Rodger
- arodger_at_agric.wa.gov.au
- Curtin University of Technology
- Department of Agriculture Western Australia
2What are we Attempting to Measure and Where?
- What?
- Total crop area on a state, shire, and farm level
- Soil end-members from MODIS data collected over
the Western Australian wheat-belt. - Farm level fractional crop coverage
- Potential crop yield at the farm level
- Where?
- Western Australian wheat belt in general (May
2005-Present) - Merredin Research Station (DAWA) (May
2005-Present) - Glenvar Farm at Wongan Hills, WA. (May 2005-
Present) - Additional farms at Wongan Hills as the season
progresses
3Merredin and Glenvar
4Automatic Soil End-Member (AUTOSEM)
softwareSelection Using MODIS Imagery
- Uses the first 5 MODIS bands (459-1250nm)
- Uses a time series of MODIS reflectance imagery
- Each MODIS reflectance spectrum is compared to a
known soils spectral library (ASTER) and the sum
of the differences from each of the 5 bands
recorded - For a given pixel the MODIS spectra with the
smallest sum difference is assumed to be probable
soil - The error of fit of the MODIS spectra to the
ASTER library (at present) spectra is then
compared to a predefined tolerance level - All spectra having an error of fit greater than
the tolerance level are classed as non-soil
5AUTOSEM _at_ Merredin Initial Results
6MODIS Wavelength versus Zeiss Spectrometry
AUTOSEM Reflectance
- Good agreement between MODIS-derived soil spectra
and those measured at Merredin - Comparable variation in the first 4 MODIS bands.
7Preliminary Results (1)
Fractional Analysis Model Using a Zeiss
Vegetation End-Member and the AUTOSEM Sharpees
Farm Using the AUTOSEM in combination with a
Zeiss-derived vegetation end-member yields the
following time series of fractional vegetation
cover. These results do not distinguish between
crop species, remnant vegetation or natural
vegetation.
8Preliminary Results (2)
While the overall trend is what we expect, the
confidence in the vegetation end-member is not
high since we have yet to gather a representative
sample of crop end-members.
9Preliminary Results (3)
Potential STIN yield prediction for Wongan Hills
as of the 22/7/05 is 2.305 (T/ha). The potential
mass of the crop Mc can be estimated at any point
in time as McVF6.252.305, where VFvegetation
fraction and the factor 6.25 is the size of a
MODIS 250m pixel in hectares. The assumption is
that the peak tonnage corresponds to the end of
year yield. This is no different than the
assumption of mid-season NDVI being the best
indicator of yield.
10Total Crop Area from Temporal MODIS NDVI
11The Team
The Partners
- Project Leader
- Professor Graciela Metternicht,
- Dept. of Spatial Sciences, Curtin Univ.
Technology - Research Team
- Dr Andrew Rodger Dr Tom Schut, Research
Associates, Curtin Univ. Dept Agriculture WA - Mr Greg Beeston, Dept. Agriculture Western
Australia - Dr Stephen Gherardi, Dept. Agriculture Western
Australia - Dr Miles Dracup, Dept. Agriculture Western
Australia - Mr Damien Shepherd, Dept. Agriculture Western
Australia - Dr Richard Smith, Dept of Land Information
Western Australia - Dr Dave Henry and Dr Asoka Edirisinghe, CSIRO