INTELLIGENT APPROACHES TO ANALYSING THE IMPORTANCE OF LAND USE MANAGEMENT IN SOIL CARBON STOCK IN A SEMIARID ECOSYSTEM, WEST OF IRAN

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

PARVIZI YAHYA; HESHMATI MOSAYEB; GHEITURI MOHAMMAD

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: ECOPERSIA Year:2017 | Volume:5 | Issue:1 Page(s): 1699-1709

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

523

Download:

113

Cites:

Information Journal Paper

Title

INTELLIGENT APPROACHES TO ANALYSING THE IMPORTANCE OF LAND USE MANAGEMENT IN SOIL CARBON STOCK IN A SEMIARID ECOSYSTEM, WEST OF IRAN

Author(s)

PARVIZI YAHYA | HESHMATI MOSAYEB | GHEITURI MOHAMMAD | Issue Writer Certificate

Keywords

CARTQ1

MLRQ2

NEURAL NETWORKSQ1

SEMI ARID ENVIRONMENTQ1

SOIL ORGANIC CARBONQ1

Abstract

The effects of different climatic, soil, geometric, and management factors on SOIL ORGANIC CARBON (SOC) degradation and sequestration potential was evaluated in the semi-arid zone of Mereg watershed, west of Iran. Two nonparametric methods, viz. Classification and Regression Tree (CART) and feed forward back propagation Artificial Neural Network (ANN) were compared with parametric Multivariate Linear Regression (MLR) in estimation of SOC content. Soil sampling was conducted using randomized systematic method in work unit map by overlying soil, aspect and slope maps. Results indicated that linear models had higher prediction errors. The CART with all variables (physical and management) and the ANN with 31-2-1 topology carried the highest predictive capability, explaining 81% and 76% of SOC variability, respectively. ANN models overestimated SOC content and showed a higher capability to detect the effects of management factors on SOC variations. In all the methods, management factors dominantly controlled SOC stock sequestration or degradation in different land use.

Cites

No record.

References

No record.

Cite

APA: Copy

PARVIZI, YAHYA, HESHMATI, MOSAYEB, & GHEITURI, MOHAMMAD. (2017). INTELLIGENT APPROACHES TO ANALYSING THE IMPORTANCE OF LAND USE MANAGEMENT IN SOIL CARBON STOCK IN A SEMIARID ECOSYSTEM, WEST OF IRAN. ECOPERSIA, 5(1 ), 1699-1709. SID. https://sid.ir/paper/263643/en

Vancouver: Copy

PARVIZI YAHYA, HESHMATI MOSAYEB, GHEITURI MOHAMMAD. INTELLIGENT APPROACHES TO ANALYSING THE IMPORTANCE OF LAND USE MANAGEMENT IN SOIL CARBON STOCK IN A SEMIARID ECOSYSTEM, WEST OF IRAN. ECOPERSIA[Internet]. 2017;5(1 ):1699-1709. Available from: https://sid.ir/paper/263643/en

IEEE: Copy

YAHYA PARVIZI, MOSAYEB HESHMATI, and MOHAMMAD GHEITURI, “INTELLIGENT APPROACHES TO ANALYSING THE IMPORTANCE OF LAND USE MANAGEMENT IN SOIL CARBON STOCK IN A SEMIARID ECOSYSTEM, WEST OF IRAN,” ECOPERSIA, vol. 5, no. 1 , pp. 1699–1709, 2017, [Online]. Available: https://sid.ir/paper/263643/en

Related Journal Papers