Multiobjective Network Optimization for Soil Monitoring of the Loess Hilly Region in China

Dianfeng Liu, Yaolin Liu, Mingze Wang and Xiang Zhao

Discrete Dynamics in Nature and Society, 2014, vol. 2014, 1-11

Abstract:

The soil monitoring network plays an important role in detecting the spatial distribution of soil attributes and facilitates sustainable land-use decision making. Reduced costs, higher speed, greater scope, and a loss of accuracy are necessary to design a regional monitoring network effectively. In this paper, we present a stochastic optimization design method for regional soil carbon and water content monitoring networks with a minimum sample size based on a modified particle swarm optimization algorithm equipped with multiobjective optimization technique. Our effort is to reconcile the conflicts between various objectives, that is, kriging variance, survey budget, spatial accessibility, spatial interval, and the amount of monitoring sites. We applied the method to optimize the soil monitoring networks in a semiarid loess hilly area located in northwest China. The results reveal that the proposed method is both effective and robust and outperforms the standard binary particle swarm optimization and spatial simulated annealing algorithm.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/DDNS/2014/805175.pdf (application/pdf)
http://downloads.hindawi.com/journals/DDNS/2014/805175.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:805175

DOI: 10.1155/2014/805175

Access Statistics for this article

More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().