By Topic

Notice of Retraction
The dynamical monitoring on quality of agricultural land resources based on vegetation index by MODIS data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xueyan Sui ; Dept. of Land Resources & Tourism Sci., Nanjing Univ., Nanjing, China ; Shenglu Zhou ; Chen Lin

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

One of the hot issues of the current research on agricultural land quality is how to employ remote sensing image processing technique to monitor the temporal-spatial changes of agricultural land quality dynamically. The paper elaborates on grid-pixel based vegetation index in light of MODIS image and agricultural land grading data of agricultural land in Jiangsu Province, since vegetation index is an efficient characterization to measure natural quality of regional agricultural land; it, taking Yixing as research region, also analyzes the correlativity between vegetation index from remote sensing image and natural quality index of agricultural land by combining GIS spatial analysis and statistics principles. The Paper builds regression model, with which it takes a sample from agricultural land in Wuxi for test; the result shows that the model has a good fitting degree and it is feasible to making NDVI-based dynamical monitoring on the temporal-spatial changes of agricultural land quality.

Published in:

Natural Computation (ICNC), 2011 Seventh International Conference on  (Volume:1 )

Date of Conference:

26-28 July 2011