Remotely-Sensed Ecosystem Health Assessment (RSEHA) model for assessing the changes of ecosystem health of Lake Urmia Basin-Reference-Cited by-同舟云学术

Remotely-Sensed Ecosystem Health Assessment (RSEHA) model for assessing the changes of ecosystem health of Lake Urmia Basin

Published:2021-05-25 Issue: Volume: Page:1-26
ISSN:1947-9832
Container-title:International Journal of Image and Data Fusion
language:en
Short-container-title:International Journal of Image and Data Fusion

Author:

Abbaszadeh Tehrani Nadia¹,Mohd Shafri Helmi Zulhaidi²,Salehi Sara³,Chanussot Jocelyn⁴,Janalipour Milad¹

Affiliation:

1. Department of Aerospace Application for Environment, Aerospace Research Institute, Ministry of Science, Research, and Technology, Tehran, Iran

2. Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia

3. Department of Petrology and Economic Geology, Geological Survey of Denmark and Greenland, Copenhagen, Denmark

4. GIPSA-Lab, Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/19479832.2021.1924880

Reference91 articles.

1. Predicting ecosystem shift in a Salt Lake by using remote sensing indicators and spatial statistics methods (case study: Lake Urmia basin)

2. An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

3. Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

4. A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)

5. Spatiotemporal dynamics of ecosystem services provision in a degraded ecosystem: A systematic assessment in the Lake Urmia basin, Iran

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