bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)

205.767

2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents

 

Best Articles 2011

 

 

 

Vol. 164, Issue 2, February 2014, pp. 256-264

 

Bullet

 

Retrieval of Land Surface Component Temperature by Particle Swarm Optimization Algorithm
 

1 Zhenhua LIU, 2 Manqin Hu, 3 Qiaoyi Chen, 4 Yueming Hu * WANG Lu

1, 2, *, 4 College of Information, South China Agricultural University, Guangzhou 510642, China

3 Surveying and Mapping Institute Lands and Resource Department of Guangdong Province, Guangzhou 510642, China

* Guangzhou Institute of Geochemistry, Chinese Academic of Science, Guangzhou, 510642, China

* Graduate University of Chinese Academic of Science, Beijing 100039, China

* Guangdong Province Land Use and Remediation of the Key Laboratory, Guangzhou, 510642, China

E-mail: 1 grassmoutain@163.com, 2 cqy3929198@21cn.com, 3 985354903@qq.com, 4 ymhu163@163.com, *selinapple@163.com

 

Received: 29 October 2013 /Accepted: 27 December 2013 /Published: 28 February 2014

Digital Sensors and Sensor Sysstems

 

Abstract: The temperature of the individual components can differ significantly, introducing errors in the quantity estimations by remote sensing technique. Because the measured radiation by these sensors can be an aggregation of radiation emitted by the different canopy components, the objective of this research was to create an inversion scheme to retrieve three component temperatures: vegetation, sunlit soil and shade soil temperature by Particle swarm optimization algorithm in the YingKe wheat study area. Given Aster spatial resolution varies with wavelength: 15 m in the visible and 90 m in the thermal infrared (TIR), area ratios of components in the pixel is acquired by the optical part of the spectrum to improve component temperature retrieval precision. Comparing with field measured data, the results showed that comparing simultaneous field data, the error range of simulated temperature under condition of considering thermal radiation and reflectance data was 1.5271 %-9.58 %. There for, the retrieval method for land Surface Component Temperature by Particle Swarm Optimization Algorithm is feasible.

 

Keywords: Component temperature, ASTER data, Particle swarm optimization algorithm.

 

Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format

 

 

Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)

 

 

 

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

 

 

Download <here> the Library Journal Recommendation Form

 

 

Read more about Temperature Sensors

 

 

 

 

 


1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.


Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn