Instrumental to the concept of sustainability must be the search for feasible ways to implement sustainability, especially connecting heritage and tourism. This should be understood in relationship with the persistence in time and the current and future conception of the human-made environment. This study deals with the spatial characterization over time of the urban sprawl close to and around two important archaeological areas: Kom el Shoqafa, Egypt and Shush, Iran. For both of the investigated sites, change detection analyses have been conducted using satellite declassified Corona and multidate Thematic Mapper (TM) imagery available for free from the USGS Earth Explorer. The study involves the collection of Corona 1964, Landsat TM 1984, Landsat ETM+ 1998 and L8 2016. The past and current urban and agricultural areas have been extracted by using consolidated classification techniques. Analyses and quantification of the spatial dimension of the urban expansion showed that, for both the study sites, urban areas have expanded to a significant percentage. In particular, the analysis of Corona and Landsat TM, ETM+, L8 imagery in Kom el Shoqafa revealed that, for the urban area, the evaluation of the change detection presented generally increasing chronology in both of the study areas, but for the agriculture lands, we can see that the changes sometimes decreased and sometimes increased. As a whole, outputs from our investigations clearly highlight that the current availability free of charge of long term satellite time series provides an excellent low cost tool for several applications including environmental monitoring and change detection to observe and quantify urban and land use changes from a global down to a local scale. We examine the capabilities of integrating remote sensing and GIS and suggest some innovative solutions to preserve the archaeological sites.
Food security has become a global concern for humanity with rapid population growth, requiring a sustainable assessment of natural resources. Soil is one of the most important sources that can help to bridge the food demand gap to achieve food security if well assessed and managed. The aim of this study was to determine the soil quality index (SQI) for El Fayoum depression in the Western Egyptian Desert using spatial modeling for soil physical, chemical, and biological properties based on the MEDALUS methodology. For this purpose, a spatial model was developed to evaluate the soil quality of the El Fayoum depression in the Western Egyptian Desert. The integration between Digital Elevation Model (DEM) and Sentinel-2 satellite image was used to produce landforms and digital soil mapping for the study area. Results showed that the study area located under six classes of soil quality, e.g., very high-quality class represents an area of 387.12 km2 (22.7%), high-quality class occupies 441.72 km2 (25.87%), the moderate-quality class represents 208.57 km2 (12.21%), slightly moderate-quality class represents 231.10 km2 (13.5%), as well as, a low-quality class covering an area of 233 km2 (13.60%), and very low-quality class occupies about 206 km2 (12%). The Agricultural Land Evaluation System for arid and semi-arid regions (ALESarid) was used to estimate land capability. Land capability classes were non-agriculture class (C6), poor (C4), fair (C3), and good (C2) with an area 231.87 km2 (13.50%), 291.94 km2 (17%), 767.39 km2 (44.94%), and 416.07 km2 (24.4%), respectively. Land capability along with the normalized difference vegetation index (NDVI) used for validation of the proposed model of soil quality. The spatially-explicit soil quality index (SQI) shows a strong significant positive correlation with the land capability and a positive correlation with NDVI at R2 0.86 (p < 0.001) and 0.18 (p < 0.05), respectively. In arid regions, the strategy outlined here can easily be re-applied in similar environments, allowing decision-makers and regional governments to use the quantitative results achieved to ensure sustainable development.
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