Utilization of Satellite Images-Based Indices for Assessment of Al-Hammar Marsh Restoration plan

Bayda Dhaidan,Mahmoud Al-Khafaji,Imzahim Alwan

doi:10.30684/etj.v39i8.2149

Abstract

Wetland landscape characterization is an important component of determining the degree to which wetlands improve environmental conditions. The present study aims to create a model used to automated extraction of the land cover of the western part of the Al-Hammar Marsh south of Iraq, and then monitor the change in land cover overtime. A model builder in ArcGIS created based on a series of spectral-based indices included the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), and the Normalized Difference Water Index (NDWI), the OLI satellite images from 2013 to 2020, ENVI 5.3 and ArcGIS 10.4 were used to achieve this goal. The results were six land cover classes: water, density vegetation, medium dense vegetation, low dense vegetation, wet barren land and, dry barren land. From the monitoring of the changing trend, it is clear that there is no improvement in the vegetation area, only a slight temporal improvement to 48% in 2017, an increase in water area for the years 2019 and 2020 to 47.33%, and 42.85% from the total area of the marsh respectively. The highest percentage was in 2019 while decreasing to the lowest rate of 14.05% for the year 2018. The developed model was accepted and can be applied for reflectance Landsat 8 data in the study area and can be applied in the southern Iraqi marshes. It also can be applied to other types of sensors, but according to determinants.

Highlights

The southern Iraqi marshlands are the largest wetland in the continent of Asia
The results showed that the Maximum Likelihood Classification (MLC) method applied provides higher overall accuracy and the kappa coefficient compared to the Artificial Neural Networks (ANN) and Support Vector Machine (SVM) methods
This study presents a developed model by the model builder and three spectral indices Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Moisture Index (NDMI) applied on Landsat satellite images to monitor western part of the Al-Hammar Marsh

Summary

Introduction

The southern Iraqi marshlands are the largest wetland in the continent of Asia These marshlands are extended over more than 20000 km2of the area surrounding the confluence of the Euphrates and Tigris Rivers in southern Iraq and part of southwestern Iran. Great challenges and obstacles are facing the implementation of these plans, such as the severe shortage of available water resources, demographic changes, and oil exploration and extraction works. According to these challenges, an integrated assessment is required of the extent to which the restoration plan has been achieved. The satellite-based and Geographical Information System (GIS) methodologies are effective tools used to monitor and assess the spatiotemporal change in land cover, and some effective features of ecological systems

Objectives

Methods

Findings

Discussion

Conclusion