TITLE:
Landscape Evaluation Based on Gaofen Satellite in the Southern Part of the Nile Delta, Egypt
AUTHORS:
Hazem T. Abd El-Hamid, Wenlong Wang, Qiaomin Li
KEYWORDS:
Landscape, Nil Delta, GIS, Metrics, GF2
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.7 No.7,
July
24,
2019
ABSTRACT: Landscape segmentation and
classification is fundamental to landscape research because it provides an
important frame of reference for researchers to communicate and compare their work. Anthropogenic human activities
mainly lead to landscape changes. The present study aims to assess the
impact of anthropogenic activities on landscape classification of the Nile
Delta using remote sensing and GIS techniques. Field survey, digital
databases and GIS capabilities are applied for landscapes classification.
Vector data using a lot of maps and raster data using
satellite image have the ability to give obvious classification about
landscape. Results showed that the anthropogenic impacts affect negatively on
the landscape classification. Using GF2, landscapes are classified into major
eight classes: cultivated land, garden land, woodland, grassland, bare land, urban land, water bodies and mining land. It was
showed that the urban occupies the highest percentage of the study area.
Urban construction and development areas centered on the capital Cairo city and
the city of Giza are dumbbell-shaped to the east. Bare lands occupy the second
percentage of the study area, and it may be distributed on around the Nile
Delta, southeast of Cairo City and southwest of Giza City. According to vegetation cover, three classes were applied as the
sequence: Cultivated land > Garden land > Grass land. These classes depend mainly on the River Nile. Vegetation cover may be based mainly on the water from the Nile River. In addition, mining land occupies the least percentage of the study area.
The main distribution of mines and mineral exploration is also very small, but
it is distributed on the edge of the city. Landscape metric as Fractal Dimension (Frac) and the Square Pixel (SqP) was applied to validate the segmentation and classification. These metrics
indicated that the landscape classification is related to natural and human
changes. These changes were related to unplanned management of new
projects and some anthropogenic activities.