Spatial Open Data for Monitoring Risks and Preserving Archaeological Areas and Landscape: Case Studies at Kom el Shoqafa, Egypt and Shush, Iran

Abstract

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.

Evaluating the Effects of Human Activity over the Last Decades on the Soil Organic Carbon Pool Using Satellite Imagery and GIS Techniques in the Nile Delta Area, Egypt

“…In particular, satellite technologies can provide useful information to estimate SOC, allowing quantitative assessments of SOC contents using proxy indicators, such as spectral indices like the Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI), and Enhanced Vegetation Index (EVI). According to several studies [15][16][17][18][19][20][21][22][23][24], the reliability of a quantitative assessment of SOC contents depends on statistical prediction models such step-wise linear regression, principal component regression, and partial least squares regression support vector regression (SVR), artificial neural networks (ANN), and random forest (RF) used to infer the volume-dependent SOC content of the soil body [15][16][17][18][19][20][21][22][23][24][25]. Remote sensing technologies and statistical analysis can enable us to overcome the limitation of methods only based on field surveys and laboratory measurements, which provide information limited to the sites where the measurement was done.…”

Multitemporal 2016-2018 Sentinel-2 Data Enhancement for Landscape Archaeology: The Case Study of the Foggia Province, Southern Italy

“…for a deep knowledge of the contexts, essential in the field of archaeological research. The use of Sentinel-2 images could also be included in the practices for the creation of the archaeological risk assessment map to be handed over to the Soprintendenza, for the protection of cultural heritage in the case of urban sprawl and land use change processes [116][117][118][119][120][121].…”

Effects of Urban Growth on Architectural Heritage: The Case of Buddhist Monasteries in the Qinghai-Tibet Plateau

“…Landsat satellite images were provided by the United States Geological Survey Earth Explorer [61]. The Landsat satellite data offered various bands with a diverse spectral range, which provided highly differentiated applications, such as monitoring urban growth and classifying the growth's spatial and temporal characteristics [52,53]. Vector data on China's municipal administrative divisions were obtained from the 1:1 Million Basic National Geographic Database of the National Catalogues Service for Geographic Information [57].…”

“…Remote sensing data provide historical time series data and current information on urban spatial structure and city border regions. The geographic information system (GIS) is considered to be one of the most efficient tools for analyzing, mapping, and retrieving these remote sensing data, and these tools have been widely applied to mapping urban growth [47][48][49]; analyzing the impact of human activities on the climate, ecosystem, and environment of the Q-T Plateau [50,51]; cultural heritage management; and risk assessments near heritage sites [52][53][54].…”