Remote Sensing for Land Use Mapping, Case of The Study Area: Urban Commune of Saada, Morocco

The phenomenon of urban planning in favor of agricultural land on the outskirts of the city of Marrakech is in full expansion. The study of land use changes is of pivotal interest for the knowledge, management, monitoring, surveillance, and evaluation of our environment. Indeed, the city of Marrakech has been experiencing exponential population growth for several decades. This phenomenon has led to a dynamic urban characterized by the increase and densification of urbanized areas (e.g. buildings and infrastructures) which leads to the occupation of natural spaces. To this end, this study aims at highlighting the mapping and evolution of land use in the city of Marrakech from Landsat satellite image data (1989, 2005 and 2020) through the application of the Image classification using Machine Learning algorithms with the QGis Orfeo Toolbox, which facilitate the production of land use maps at three dates as well as an evolution map of the conurbation and also to quantify the obtained results. The directions of extension of the urban area were defined and thus demonstrate its impact on the agricultural land located in the peri-urban area

Remote Sensing for Spatio-temporal Mapping of Land surface temperature and Surface Energy Fluxes in the Bouregreg-Chaouia Region of Morocco

In recent decades, the Bouregreg Chaouia region has been subject to urban growth and a reduction in agricultural land in this region, which has changed its environmental variables and made it vulnerable to climate change. This work raises the spatiotemporal monitoring of land use and certain environmental parameters (vegetation cover, albedo, surface temperature from 1987 to 2015 by exploring intelligent spatial data in the region. The remote sensing products were computed from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 Oli/TIRS images obtained during the dry seasons 1987, 2000 and 2015. The results showed a reduction in NDVI vegetation index (∼0.86 in 1987 to ∼0. 56 in 2000 to ∼ 0.54 in 2015) and with an increase in surface albedo (0.51 in 1987 to 0.52 in 2000 to 0. 69 in 2015), temperature (∼67°C in 1987 to 54°C in 2000 to 40°C in 2015) and to understand the impact of urbanization on the variation of environmental parameters, the evolution of the built-up area has been followed as a determining factor. However, it recorded 3.27% surface area in 1987 to 7.45% in 2000 to 28.18% in 2015. Indeed, the contribution of new technologies (GIS and remote sensing) is essential for better management and monitoring of the impact of urban expansion on the state of the environment. The results obtained remain so promising and highlight the contribution and feasibility of intelligent spatial data to assess the evolution of the urban environment on a large scale

Lithological mapping using Landsat 8 Oli multispectral data in Boumalne, Imider, and Sidi Ali Oubork, High Central Atlas, Morocco

The recognition of geological formations, from a lithological point of view, as well as their tectonic character always remain a major challenge for any precise geological study, in this work we will see the great importance of the application of remote sensing (Landsat OLI, DEM) to realize lithological maps of great interest as well as the realization of detailed lineament maps with the statistics of the performed measurements, the application of some indicated techniques showed a good discrimination of the lithology of geological formations (Fig.8 ,Fig.10,Fig.11),better results and interpretations are also obtained for lineaments affecting the whole area by using the CP1 and DEM methods (Fig.5,Fig.6).Topographic map and geological maps of JBEL SAGHRO DADES and TODGHA MADER (1/200000) gained from ministry of energy and mines, direction of geology (1975), are used for validation of the obtained results by eliminating of artificial structures (roads) and geological layer boundaries. All data sets were pre-processed and projected in the Universal Transverse Mercator (UTM Zone 29 North) projection system and the WGS84 datum using GIS tools (ArcGIS 10.2)

Lithological mapping and automatic lineament extraction using Aster and Gdem data in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech, Morocco

Lithological and lineament mapping using remote sensing is a fundamental step in various geological studies, as it forms the basis for the interpretation and validation of the results obtained. There were two objectives for this study, applied in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech region: first, lithological mapping by satellite image processing techniques such as ASTER L1B (hight spectral and spatial resolution), namely Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), as well as the application of three types of supervised classification, namely Spectral Angle Mapper (SAM), Maximum Likelihood (ML) and Minimum Distance (MD), on the visible/near-infrared (VNIR) and short-wave infrared (SWIR) spectral bands of our ASTER image; second, an analysis of the distribution of lineaments by automatic extraction using a Global Digital Elevation Model (GDEM) and the PC1 image derived from the PCA transformation applied to the satellite image. The best results are highlighted by the delineation of new facies in relation to the existing map; after confirmation in the field, all of these facies, which include Eocene, Triassic and Jurassic formations, are represented on the new map. The results of lineaments showed that each of them systematically shows a similarity in terms of concentration and orientation, with four preferential oriented systems: NE-SW, E-W, NNE-SSW and NW-SE. The lineaments mainly follow those of the major fault zones, with high concentrations in the northeast and southwest parts of the study area

Multi-Criteria GIS-Based Analysis for Mapping Suitable Sites for Onshore Wind Farms in Southeast France

Wind energy is critical to traditional energy sources replacement in France and throughout the world. Wind energy generation in France is quite unevenly spread across the country. Despite its considerable wind potential, the research region is among the least productive. The region is a very complicated location where socio-environmental, technological, and topographical restrictions intersect, which is why energy production planning studies in this area have been delayed. In this research, the methodology used for identifying appropriate sites for future wind farms in this region combines GIS with MCDA approaches such as AHP. Six determining factors are selected: the average wind speed, which has a weight of 38%; the protected areas, which have a relative weight of 26%; the distance to electrical substations and road networks, both of which have a significant influence on relative weights of 13%; and finally, the slope and elevation, which have weights of 5% and 3%, respectively. Only one alternative was investigated (suitable and unsuitable). The spatial database was generated using ArcGIS and QGIS software; the AHP was computed using Excel; and several treatments, such as raster data categorization and weighted overlay, were automated using the Python programming language. The regions identified for wind turbines installation are defined by a total of 962,612 pixels, which cover a total of 651 km2 and represent around 6.98% of the research area. The theoretical wind potential calculation results suggest that for at least one site with an area bigger than 400 ha, the energy output ranges between 182.60 and 280.20 MW. The planned sites appear to be suitable; each site can support an average installed capacity of 45 MW. This energy benefit will fulfill the region’s population’s transportation, heating, and electrical demands