Title: Dynamic monitoring of landscape vegetation coverage based on EM-MAP-NDVI fusion algorithm

Authors: Lianying Li; Dawei Xu; Xi Chen; Safa Fadelelseed; Bingxi Liu

Addresses: College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China; College of Art and Design, Harbin University, Harbin 150000, China ' College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China; Key Lab for Garden Plant Germplasm Development and Landscape Eco-Restoration in Cold Regions of Heilongjiang Province, Harbin 150000, China ' College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China ' College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China; Landscape and Ornamental Plants Department, Horticulture Administration Sector, Ministry of Agriculture, Elmogran 999129, Sudan ' College of Landscape Architecture, Northeast Forestry University, Hexing Road 26, Harbin 150000, China

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.

Keywords: remote sensing data; landscape; vegetation coverage; dynamic monitoring.

DOI: 10.1504/IJETM.2020.114133

International Journal of Environmental Technology and Management, 2020 Vol.23 No.5/6, pp.323 - 339

Received: 25 Mar 2020
Accepted: 28 Sep 2020
Published online: 09 Apr 2021 *

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