Ayoubi, S and Shahri, A P and Karchegani, P M and Sahrawat, K L (2011) Application of Artificial Neural Network (ANN) to Predict Soil Organic Matter Using Remote Sensing Data in Two Ecosystems. In: Biomass and Remote Sensing of Biomass. InTech Open Access, InTechWeb.org, pp. 181-196. ISBN 978-953-307-490-0
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Abstract
Concern over global problems induced by rising CO2 has prompted attention on the role of forests and pastures as carbon ‘storage’ because forests and pastures store a large amount of carbon in vegetation biomass and soil. Soil organic matter (SOM) plays a critical role in soil quality and has the potential to cost-effectively mitigate the detrimental effects of rising atmospheric CO2 and other greenhouse gas emissions that cause global warming and climate change(Causarano-Medina, 2006). SOM, an important source of plant nutrients is itself influenced by land use, soil type, parent material, time, climate and vegetation (Loveland &Webb, 2003). Important climatic factors influencing SOM include rainfall and temperature. Within the same isotherm, the SOM content increases with increase in rainfall regime. For the same isohyet, the SOM content................
| Item Type: | Book Section |
|---|---|
| Divisions: | UNSPECIFIED |
| CRP: | UNSPECIFIED |
| Subjects: | Others > Soil Science |
| Depositing User: | Mr Sanat Kumar Behera |
| Date Deposited: | 16 Nov 2011 12:58 |
| Last Modified: | 16 Nov 2011 13:19 |
| URI: | http://oar.icrisat.org/id/eprint/3992 |
| Acknowledgement: | UNSPECIFIED |
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