Depending on the band position on the electromagnetic spectrum, optical and electronic characteristics, sensors collect the reflected energy by the Earth’s surface and the atmosphere. Currently, the availability of the new generation of medium resolution, such as the Multi-Spectral Instrument (MSI) on board the Sentinel-2 satellite, offers new opportunities for long-term high-temporal frequency for Earth’s surfaces observation and monitoring. This paper focuses on the analysis and the comparison of the visible, the near-infrared (VNIR), and the shortwave infrared (SWIR) spectral bands of the MSI for soil salinity discrimination in an arid landscape. To achieve these, a field campaign was organized, and 160 soil samples were collected with various degrees of soil salinity, including non-saline soil samples. The bidirectional reflectance factor was measured above each soil sample in a goniometric laboratory using an ASD (Analytical Spectral Devices) spectroradiometer. In the laboratory work, pHs, electrical conductivity (EC-Lab), and the major soluble cations (Na+, K+, Ca2++, and Mg2+) and anions (CO32−, HCO3−, Cl−, and SO42−) were measured using extraction from a saturated soil paste, and the sodium adsorption ratio (SAR) was calculated using a standard procedure. These parameters, in addition to the field observations, were used to interpret and investigate the spectroradiometric measurements and their relevant transformations using the continuum removed reflectance spectrum (CRRS) and the first derivative (FD). Moreover, the acquired spectra over all the soil samples were resampled and convolved in the solar-reflective spectral bands using the Canadian Modified Herman transfer radiative code (CAM5S) and the relative spectral response profiles characterizing the Sentinel-MSI band filters. The statistical analyses conducted were based on the second-order polynomial regression (p < 0.05) between the measured EC-Lab and the reflectances in the MSI convolved spectral bands. The results obtained indicate the limitation of VNIR bands and the potential of SWIR domain for soil salinity classes’ discrimination. The CRRS and the FD analyses highlighted a serious spectral-signal confusion between the salt and the soil optical properties (i.e., color and brightness) in the VNIR bands. Likewise, the results stressed the independence of the SWIR domain vis-a-vis these soil artifacts and its capability to differentiate significantly among several soil salinity classes. Moreover, the statistical fit between each MSI individual spectral band and EC-Lab corroborates this trend, which revealed that only the SWIR bands were correlated significantly (R2 of 50% and 64%, for SWIR-1 and SWIR-2, respectively), while the R2 between the VNIR bands and EC-Lab remains less than 9%. According to the convergence of these four independent analysis methods, it is concluded that the Sentinel-MSI SWIR bands are excellent candidates for an integration in soil salinity modeling and monitoring at local, regional, and global scales.
The study of water resources at watershed scale is widely adopted as approach to manage, assess and simulate these important natural resources. The development of remote sensing and GIS techniques has allowed the use of spatially and physically based hydrologic models to simulate as simply and realistically as possible the functioning of watershed systems. Indeed, the major constraint that has hindered the expansion use of these tools was the unavailability or scarcity of data especially in the developing countries. In this context, the objective of this study is to model the hydrology in the Bouregreg basin, located at the north-central of Morocco, using the Soil and Water Assessment Tool (SWAT) in order to understand and determine the different watershed hydrological processes. Thus, it aims to simulate the stream flow, establish the water balance and estimate the monthly volume inflow to SMBA dam situated at the basin outlet. The ArcSWAT interface implemented in the ArcGIS software was used to delineate the basin and its sub-components, combine the data layers and edit the model database. The model parameters were analyzed, ranked and adjusted for hydrologic modeling purposes using daily temporal data series. They were calibrated using an auto-calibration method based on a Shuffled Complex Evolution Algorithm from 1989 to 1997 and validated from 1998 to 2005. Based on statistical indicators, the evaluation indicates that SWAT model had a good performance for both calibration and validation periods in Bouregreg Watershed. In fact, the model showed a good correlation between the observed and simulated monthly average river discharge with R² and Nash coefficient of about 0.8. The water balance components were correctly estimated and the SMBA dam inflow was successfully reproduced with R² of 0.9. These results revealed that if properly calibrated, SWAT model can be used efficiently in semi-arid regions to support water management policies.
Casablanca, Morocco's economic capital continues today to fight against the proliferation of informal settle- ments affecting its urban fabric illustrated especially by the slums. Actually Casablanca represents 25% of the total slums of Morocco [1]. These are the habitats of all deprived of healthy sanitary conditions and judged precarious from the perspective humanitarian and below the acceptable. The majority of the inhabi- tants of these slums are from the rural exodus with insufficient income to meet the basic needs of daily life. Faced with this situation and to eradicate these habitats, the Moroccan government has launched since 2004 an entire program to create cities without slums (C.W.S.) to resettle or relocate families. Indeed the process control and monitoring of this program requires first identifying and detecting spatial habitats. To achieve these tasks, conventional methods such as information gathering, mapping, use of databases and statistics often have shown their limits and are sometimes outdated. It is within this framework and that of the great German Morocco project “Urban agriculture as an integrative factor of development that fits our project de- tection of slums in Casablanca. The use of satellite imagery, particulary the HSR, has the advantage of providing the physical coverage of urban land but it raises the difficulty of choosing the appropriate method to apply.This paper is actually to develop new approaches based mainly on object-oriented classification of high spatial resolution satellite images for the detection of slums.This approach has been developed for mapping the urban land through by integration of several types of information (spectral, spatial, contextual ...) (Hofmann, P ., 2001, Herold et al. 2002b; Van Der Sande et al., 2003, Benz et al., 2004, Nobrega et al., 2006). In order to refine the result of classification, we applied mathematical morphology and in particular the closing filter. The data from this classification (binary image), which then will be used in a spatial data- base (ArcGIS)
Abstract:The urban heat island (UHI) phenomenon is a harmful environmental problem in urban areas affecting both climatic and ecological processes. This paper aims to highlight and monitor the spatial distribution of Surface UHI (SUHI) in the Casablanca region, Morocco, using remote sensing data. To achieve this goal, a time series of Landsat TM/ETM+/OLI-TIRS images was acquired from 1984 to 2016 and analyzed. In addition, nocturnal MODIS images acquired from 2005 to 2015 were used to evaluate the nighttime SUHI. In order to better analyze intense heat produced by urban core, SUHI intensity (SUHII) was computed by quantifying the difference of land surface temperature (LST) between urban and rural areas. The urban core SUHII appears more significant in winter seasons than during summer, while the pattern of SUHII becomes moderate during intermediate seasons. During winter, the average daytime SUHII gradually increased in the residential area of Casablanca and in some small peri-urban cities by more than 1 • C from 1984 to 2015. The industrial areas of the Casablanca region were affected by a significant rise in SUHII exceeding 15 • C in certain industrial localities. In contrast, daytime SUHII shows a reciprocal effect during summer with emergence of a heat island in rural areas and development of cool islands in urban and peri-urban areas. During nighttime, the SUHII remains positive in urban areas year-round with higher values in winter as compared to summer. The results point out that the seasonal cycle of daytime SUHII as observed in the Casablanca region is different from other mid-latitude cities, where the highest values are often observed in summer during the day.
Oued El Maleh watershed is considered the largest ocean basin of the Chaouia-Ouardigha region in Morocco. Severe flooding occurred in 1996, 2001 and 2002 in the watershed. Thus, significant economic and human damage has been caused. The floods of Mohammedia city, located in the outlet of the watershed, were due to the silting of the Oued El Maleh dam which has lost its ability to retain water. This work, therefore, aims to assess soil losses by water erosion in the Oued El Maleh watershed through modeling main factors involved in water erosion. The methodology used is based on the use of the universal soil loss equation (USLE). The model includes the following factors: soil erodibility, the inclination of slopes, the rainfall erosivity, vegetation cover and erosion control practices. The aggressiveness of rainfall was calculated for a number of stations bordering the study area and interpolated across the watershed using geostatistical model. Soil erodibility was extracted from soil map and soil survey. The effect of topography was approached by combining the degree of slope and slope length using a digital elevation model (ASTER) and ArcHydrology extension (ArcGIS). The vegetation cover was derived from Landsat image ETM through the supervised classification method. The index of erosion control practices was approached by field visits. All factors have been measured and integrated into a geographic information system which enabled us to spatialize the degree of sediment production at the watershed scale in a synthetic map. The annual soil loss is 8.21 t/ha/yr and the soil loss classification shows that surfaces affected by high erosion are equivalent to 10% of the watershed. Furthermore, this map is available to support land managers policy makers in the process of decision making related to soil conservation, infrastructure and citizens' property protection.
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