@incollection{icrisat3992,
       publisher = {InTech Open Access},
       booktitle = {Biomass and Remote Sensing of Biomass},
         address = {InTechWeb.org},
            year = {2011},
           title = {Application of Artificial Neural Network (ANN) to Predict Soil Organic Matter Using Remote Sensing Data in Two Ecosystems},
           pages = {181--196},
          author = {S Ayoubi and A P Shahri and P M Karchegani and K L Sahrawat},
             url = {http://oar.icrisat.org/3992/},
        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................}
}