eprintid: 3992
rev_number: 9
eprint_status: archive
userid: 30
dir: disk0/00/00/39/92
datestamp: 2011-11-16 12:58:08
lastmod: 2011-11-16 13:19:10
status_changed: 2011-11-16 12:58:08
type: book_section
metadata_visibility: show
contact_email: Library-ICRISAT@CGIAR.ORG
item_issues_count: 0
creators_name: Ayoubi, S
creators_name: Shahri, A P
creators_name: Karchegani, P M
creators_name: Sahrawat, K L
icrisatcreators_name: Sahrawat, K L
affiliation: Isfahan University of Technology(Isfahan)
affiliation: Islamic Azad University(Isfaha)
affiliation: ICRISAT(Patancheru)
country: Iran
country: India
title: Application of Artificial Neural Network (ANN) to Predict Soil Organic Matter Using Remote Sensing Data in Two Ecosystems
ispublished: pub
subjects: s2.11
full_text_status: public
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................
date: 2011
date_type: published
publisher: InTech Open Access
place_of_pub: InTechWeb.org
pagerange: 181-196
pages: 262
refereed: TRUE
isbn: 978-953-307-490-0
book_title: Biomass and Remote Sensing of Biomass
official_url: http://www.intechopen.com/books/show/title/biomass-and-remote-sensing-of-biomass
related_url_url: http://scholar.google.co.in/scholar?as_q=%22Application+of+Artificial+Neural+Network+%28ANN%29+to+Predict+Soil+Organic+Matter+Using+Remote+Sensing+Data+in+Two+Ecosystems%22&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=title&as_sauthors=&as_pub
related_url_type: author
citation:   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     
document_url: http://oar.icrisat.org/3992/1/InTech-Application_of_artificial_neural_network_ann_to_predict.pdf