The mapping of soil nutrients is a key issue for numerous applications and research fields ranging from global changes to environmental degradation, from sustainable soil management to the precision agriculture concept. The characterization, modeling and mapping of soil properties at diverse spatial and temporal scales are key factors required for different environments. This paper is focused on the use and comparison of soil chemical analyses, Visible near infrared and shortwave infrared VNIR-SWIR spectroscopy, partial least-squares regression (PLSR), Ordinary Kriging (OK), and Landsat-8 operational land imager (OLI) images, to inexpensively analyze and predict the content of different soil nutrients (nitrogen (N), phosphorus (P), and potassium (K)), pH, and soil organic matter (SOM) in arid conditions. To achieve this aim, 100 surface samples of soil were gathered to a depth of 25 cm in the Wadi El-Garawla area (the northwest coast of Egypt) using chemical analyses and reflectance spectroscopy in the wavelength range from 350 to 2500 nm. PLSR was used firstly to model the relationship between the averaged values from the ASD spectroradiometer and the available N, P, and K, pH and SOM contents in soils in order to map the predicted value using Ordinary Kriging (OK) and secondly to retrieve N, P, K, pH, and SOM values from OLI images. Thirty soil samples were selected to verify the validity of the results. The randomly selected samples included the spatial diversity and characteristics of the study area. The prediction of available of N, P, K pH and SOM in soils using VNIR-SWIR spectroscopy showed high performance (where R2 was 0.89, 0.72, 0.91, 0.65, and 0.75, respectively) and quite satisfactory results from Landsat-8 OLI images (correlation R2 values 0.71, 0.68, 0.55, 0.62 and 0.7, respectively). The results showed that about 84% of the soils of Wadi El-Garawla are characterized by low-to-moderate fertility, while about 16% of the area is characterized by high soil fertility.

This paper is focused on the use of satellite Sentinel-2 data for assessing their capability in the identification of archaeological buried remains. We selected the "Tavoliere delle Puglie" (Foggia, Italy) as a test area because it is characterized by a long human frequentation and is very rich in archaeological remains. The investigations were performed using multi-temporal Sentinel-2 data and spectral indices, commonly used in satellite-based archaeology, and herein analyzed in known archaeological areas to capture the spectral signatures of soil and crop marks and characterize their temporal behavior using Time Series Analysis and Spectral Un-mixing. Tasseled Cap Transformation and Principal Component Analysis have been also adopted to enhance archaeological features. Results from investigations were compared with independent data sources and enabled us to (i) characterize the spectral signatures of soil and crop marks, (ii) assess the performance of the diverse spectral channels and indices, and (iii) identify the best period of the year to capture the archaeological proxy indicators. Additional very important results of our investigations were (i) the discovery of unknown archaeological areas and (ii) the setup of a database of archaeological features devised ad hoc to characterize and categorize the diverse typologies of archaeological remains detected using Sentinel-2 Data.

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Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

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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.

Soil sealing is currently one of the most critical barriers to sustainable development, particularly in developing countries such as Egypt. Agriculture is a major component of the Egyptian economy and the country’s main source of food security. Urbanization is devouring vast areas of agricultural land, and therefore, in the present study, urbanization was used to determine the degree of soil sealing in a region of Kafr El Sheikh Governorate, Egypt. In this work, remote sensing data were used to monitor changes in land use and land cover (LULC) between 1984 and 2016. A field survey and population data were also used in the analysis. Support vector machine (SVM) classification was used to produce LULC maps of the study area. An accuracy assessment was performed by calculating overall accuracy and individual kappa coefficients. Additionally, soil sealing was assessed using data from 1984 to 2016, and the potential expansion of soil sealing until 2048 was simulated using the cellular automata (CA)–Markov model. Our analysis showed that in the study area (i) about 90% of the soils had soil capability degrees between class II and class III; (ii) soil sealing was not uniformly distributed in the study area; (iii) between 1984 and 2016, the area of soil sealing in fertile soils due to urbanization increased by 19,500 hectares; and (iv) between 1984 and 2000, the urban area increased by around 29%, whereas between 2000 and 2010 it increased by around 43.6%. The results suggest that the magnitude of soil sealing is a good indicator of the soil loss rate and the potential for agricultural development in the Nile Delta. The model predicted that by 2048 an area of 32,290 hectares of agricultural soil will be lost to urbanization. This study indicates that the change of LULC has a negative impact on soil sealing. Between 2000 and 2010, the area of agricultural land decreased by 4%, despite an increase in land reclamation in the north of the study area. The amount of soil sealing was found to increase towards the southeast and northeast of the study area, except for the northern parts, where the amount of soil sealing increased towards the east. Our analyses and forecasts are useful for decision-makers responsible for soil-sealing mitigation strategies and soil-sealing protection plans in the Kafr El Sheikh Governorate, Egypt.

Historic Jeddah is located on the eastern shore of the Red Sea. Historic Jeddah was designated as a UNESCO world heritage site in 2014. The new urban development for the city of Jeddah has resulted in different spatial patterns. The southern part of Jeddah city falls within the moderate zone, because this area is well developed in regard to infrastructure with rainstorm and sewage networks. The middle area of the city falls within high vulnerability risk due to its high population, shallow water depth, flat slopes, and various incomplete network services (i.e., leakage from septic tanks and water pipes). The western and northwestern parts of the city are subject to very high pollution risk, due to the highly permeable area with coralline formation, very shallow water depth, and depressions. Unfortunately, historic Jeddah has been affected by the unplanned development and shallow water depth. Most of the construction and decoration of the ancient buildings are suffering from deterioration. The paper aims to detect the environmental changes, assessing the geo-environmental status, and creating some of the innovative solutions while using the integration between remote sensing and GIS techniques. The combination of SRTM, Corona 1966, Spot 1986, Landsat 1987, Orbview 2003, and Sentinel2A 2017 data will help in monitoring the changes around the study area. The Bands combination and the spatial statistical analysis are considered to be the most effective methods in the examination of the new built-up indices. GIS techniques and some models would be suggested as solutions to protect the archaeological area, according to UNESCO recommendations.