Digital Soil Mapping: Jake Campolo Applications for...EXPLORATORY SOIL MAP 1980 SCALE 1.000000 KENYA...
Transcript of Digital Soil Mapping: Jake Campolo Applications for...EXPLORATORY SOIL MAP 1980 SCALE 1.000000 KENYA...
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Digital Soil
Mapping:
Applications for
Fertilizer
Management
Jake Campolo
&
David Guerena
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Hydrology
Climate
Soil data
Elevation
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Case study 1 - Mexico
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Seven estimated yield potentials for
maize
● 2.5 t/ha
● 5 t/ha
● 7.5 t/ha
● 10 t/ha
● 12.5 t/ha
● 17.5 t/ha
● 20 t/ha
● P2O5
● K2O
● Mg
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Case study 2 - Nepal
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1. 180: 50:50 kg NPK/ ha (sufficiency
plots)
2. 180: 50:50 kg NPK + 13.5 kg Borax
+ 12 kg ZnSO4 /ha
3. 180:50:0 kg NP /ha
4. 180: 0:50 kg NK/ha
5. 0: 50:50 kg PK/ha
6. 60:50:50 kg NPK/ha
7. 100:50:50 kg NPK/ha
8. 140:50:50 kg NPK/ha
9. 160:50:50 kg NPK/ha
Treatments:
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$ $$
$$$$
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SQI = 0.35 * OMscl + 0.28 * Clayscl + 0.28 * Sandscl + 0.20 * Boronscl + 0.17 * Zincscl
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Conclusion
● RS data and ML tools can provide a scalable way to
integrate ground data with landscape management
predictions
● ML algorithms are powerful tools, but need large quantities
of data, good quality ground data is still scarce.
● This approach benefits most from the synergies between
field trials, RS data, and advanced algorithms.
● A critical missing component has been validation trials at
the landscape-level to test the predictions from these new
models.
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bigdata.cgiar.org