Dynamic monitoring of landscape vegetation coverage based on EM-MAP-NDVI fusion algorithm
by Lianying Li; Dawei Xu; Xi Chen; Safa Fadelelseed; Bingxi Liu
International Journal of Environmental Technology and Management (IJETM), Vol. 23, No. 5/6, 2020

Abstract: Due to the complexity of the detection types of urban landscape vegetation, the existing methods have the problem of unclear image feature classification, which leads to the low accuracy of dynamic monitoring of landscape vegetation coverage. A dynamic monitoring method of urban landscape vegetation coverage based on EM-MAP-NDVI fusion algorithm is proposed. The multi-source remote sensing image feature data and vegetation dynamic characteristics of landscape vegetation are obtained. The expectation maximisation (EM) algorithm is used to estimate the vegetation coverage parameters. The problem of vegetation image feature classification is transformed into the problem of maximum posterior probability (MAP), and the dynamic monitoring results of vegetation coverage are calculated. The experimental results show that the proposed method can effectively improve the accuracy of urban landscape vegetation feature extraction and achieve high-precision dynamic monitoring of urban landscape vegetation coverage, which has good application value.

Online publication date: Fri, 09-Apr-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Environmental Technology and Management (IJETM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com