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

Abstract

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