This study documents the changes in the Land Use/Land Cover (LULC) in the region of saline lakes in north Tunisia, Sahara Desert. Remote sensing data are a valuable data source in monitoring LULC in ...lacustrine landscapes, because variations in the extent of lakes are visible from space and can be detected on the images. In this study, changes in LULC of the salt pans of Tunisia were evaluated using a series of 12 Landsat 8-9 Operational Land Imager (OLI) and Thermal Infrared (TIRS) images. The images were processed with the Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) software. The study area included four salt lakes of north Tunisia in the two regions of the Gulf of Hammamet and Gulf of Gabès: (1) Sebkhet de Sidi el Hani (Sousse Governorate), (2) Sebkha de Moknine (Mahdia Governorate), (3) Sebkhet El Rharra and (4) Sebkhet en Noual (Sfax). A quantitative estimate of the areal extent analysed in this study is 182 km × 185 km for each Landsat scene in two study areas: Gulf of Hammamet and Gulf of Gabès. The images were analysed for the period 2017–2023 on months February, April and July for each year. Spatio-temporal changes in LULC and their climate–environmental driving forces were analysed. The results were interpreted and the highest changes were detected by accuracy assessment, computing the class separability matrices, evaluating the means and standard deviation for each band and plotting the reject probability maps. Multi-temporal changes in LULC classes are reported for each image. The results demonstrated that changes in salt lakes were determined for winter/spring/summer months as detected changes in water/land/salt/sand/vegetation areas. The accuracy of the classified images was evaluated using pixel rejection probability values, which were filtered out using the ‘r.mapcalc’ module of GRASS GIS. The confidence levels were computed and visualised with a series of maps along with the error matrix and measured convergence level of classified pixels. This paper contributes to the environmental monitoring of Tunisian landscapes and analysis of climate effects on LULC in landscapes of north Africa.
Mapping coastal regions is important for environmental assessment and for monitoring spatio-temporal changes. Although traditional cartographic methods using a geographic information system (GIS) are ...applicable in image classification, machine learning (ML) methods present more advantageous solutions for pattern-finding tasks such as the automated detection of landscape patches in heterogeneous landscapes. This study aimed to discriminate landscape patterns along the eastern coasts of Mozambique using the ML modules of a Geographic Resources Analysis Support System (GRASS) GIS. The random forest (RF) algorithm of the module ‘r.learn.train’ was used to map the coastal landscapes of the eastern shoreline of the Bight of Sofala, using remote sensing (RS) data at multiple temporal scales. The dataset included Landsat 8-9 OLI/TIRS imagery collected in the dry period during 2015, 2018, and 2023, which enabled the evaluation of temporal dynamics. The supervised classification of RS rasters was supported by the Scikit-Learn ML package of Python embedded in the GRASS GIS. The Bight of Sofala is characterized by diverse marine ecosystems dominated by swamp wetlands and mangrove forests located in the mixed saline–fresh waters along the eastern coast of Mozambique. This paper demonstrates the advantages of using ML for RS data classification in the environmental monitoring of coastal areas. The integration of Earth Observation data, processed using a decision tree classifier by ML methods and land cover characteristics enabled the detection of recent changes in the coastal ecosystem of Mozambique, East Africa.
The applications of the machine learning and programming approaches in cartography has been increasing in recent years. This paper presents a case study of the scripting techniques used for ...cartographic mapping using Generic Mapping Tools (GMT) and R language (raster and tmaps packages). The aim of the study is environmental mapping of Ghana. The materials include high-resolution raster grids: topography by the General Bathymetric Chart of the Oceans (GEBCO), climate and environmental datasets (TerraClimate) and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) for geomorphometric analysis (slope, aspect, hillshade and elevations). The methodology includes code snippets commented and explained with details of scripts. It is argued that using console-based scripting tools for mapping is effective for cartographic workflow due to the logical structure and repeatability of scripts. The results include eight new thematic maps of Ghana performed using scripting approach in GMT scripting toolset and R language for quantitative and qualitative environmental assessment. Maps show correlations between the landforms of Ghana and certain environmental variables (drought index and soil moisture) showing the effects of the topographic relief on the distribution of the continuous geographic fields. These varied in several geographically distinct regions of Ghana: Ashanti (Kumasi), Volta, Savannah, coastal and northern regions. Demonstrated maps show that scripting method works effectively on a wide range of geosciences including environmental, topographic and climate studies. In such a way, this paper contributes both to the regional studies of Ghana and development of cartographic techniques.
Le développement de techniques de programmation et de langages de script intégrés aux SIG a amélioré le traitement des images satellitaires pour obtenir des informations spatiales à partir des ...données de télédétection. Dans cet article, l'efficacité de l'intégration des données multi-temporelles d'observation spatiale avec des techniques de script est démontrée à travers un exemple pris en Afrique du Sud. Quatre images Landsat couvrant la région côtière du Cap ont été acquises auprès de l'USGS pour les années 2016, 2018, 2021 et 2023. Leur traitement a permis le calcul de quatre indices de végétation à l'aide du module 'i.vi' de GRASS SIG : DVI, NDVI, SAVI et CI. Les valeurs des indices ont été cartographiées pour chacune des images traitées. Ces cartes traduisent les changements de l'occupation du sol depuis 2016, notamment la déforestation et l'expansion des terres agricoles.
The development of the programming techniques and scripting languages integrated in GIS, facilitated satellite image processing for obtaining information from the remote sensing data. In this paper, the effectiveness of integration of space observation multi-temporal data with scripting techniques is demonstrated with an example from South Africa. Four Landsat images covering the coastal region of Cape Town were acquired from the USGS for years 2016, 2018, 2021 and 2023. Their processing enabled the calculation of four vegetation indices using 'i.vi' module of GRASS GIS: DVI, NDVI, SAVI and CI. The index values were mapped for each of the processed images. These maps reflect changes in land use since 2016, such as deforestation and expansion of agricultural land.
This study demonstrated the use of GRASS GIS scripts for satellite image analysis. The aim is to perform topographic and environmental analysis in eastern China, Shandong Province, Qingdao region. ...Variables include land surface temperature evaluated by correlation between the Landsat ETM+ channels and colour composites. The methodology is based on scripting by GRASS GIS modules. Data include two satellite Landsat TM images with a 5 years span (2009 and 2004). The images were imported to GRASS GIS using GDAL library by 'r.in.gdal' module. The topography (DEM) was assessed by GRASS GIS 'd.rast' module with isolines plotted using 'r.contour' and 'd.vect'. The map elements were displayed by 'v.in.region', 'd.vect', 'v.info'. The slope and aspect maps based on DEM were plotted using module 'r.slope.aspect' and visualised by a consecutive combination of 'd.rast', 'r.colours', 'd.legend', 'd.text' and 'd.grid' modules. The scatterplot of pairwise correlation of the selected Landsat TM7 channels (10 and 20, 50 and 70) was done by 'd.correlate'. The applied code from the 'r.mapcalc' was used for image calibration from the DN to apparent radiance at sensor. Two maps showing land surface temperature for 2009 and 2004 were plotted by 'r.mapcalc'. The land surface temperature maps show lower values over the water and forests, while higher values in cities. Plotting land surface temperature map was made to analyse variations in climate settings in Shandong during 5 years based on the comparative analysis using 'r.mapcalc' module. The images were plotted by natural and false colour band composites using 'd.rgb' module and band combinations: 1) colour infrared with focus on vegetation (5-4-3); 2) natural colour composites (1-2-3); 3) contrasting slopes for topography (4-5-7); 4) vegetation analysis (2-3-4); 5) focus on land/water borders (5-6-7). The study has shown cartographic functionality of GRASS GIS scripts specifically for remote sensing data processing and topographic analysis. The environmental modelling has shown variations in land surface temperature, slope steepness and orientation (aspect). The GRASS GIS demonstrated to be an effective tool for remote sensing. Full codes are available on the GitHub repository of the author with provided link to scripts.
This paper presents the object detection algorithms GRASS GIS applied for Landsat 8-9 OLI/TIRS data. The study area includes the Sudd wetlands located in South Sudan. This study describes a ...programming method for the automated processing of satellite images for environmental analytics, applying the scripting algorithms of GRASS GIS. This study documents how the land cover changed and developed over time in South Sudan with varying climate and environmental settings, indicating the variations in landscape patterns. A set of modules was used to process satellite images by scripting language. It streamlines the geospatial processing tasks. The functionality of the modules of GRASS GIS to image processing is called within scripts as subprocesses which automate operations. The cutting-edge tools of GRASS GIS present a cost-effective solution to remote sensing data modelling and analysis. This is based on the discrimination of the spectral reflectance of pixels on the raster scenes. Scripting algorithms of remote sensing data processing based on the GRASS GIS syntax are run from the terminal, enabling to pass commands to the module. This ensures the automation and high speed of image processing. The algorithm challenge is that landscape patterns differ substantially, and there are nonlinear dynamics in land cover types due to environmental factors and climate effects. Time series analysis of several multispectral images demonstrated changes in land cover types over the study area of the Sudd, South Sudan affected by environmental degradation of landscapes. The map is generated for each Landsat image from 2015 to 2023 using 481 maximum-likelihood discriminant analysis approaches of classification. The methodology includes image segmentation by ‘i.segment’ module, image clustering and classification by ‘i.cluster’ and ‘i.maxlike’ modules, accuracy assessment by ‘r.kappa’ module, and computing NDVI and cartographic mapping implemented using GRASS GIS. The benefits of object detection techniques for image analysis are demonstrated with the reported effects of various threshold levels of segmentation. The segmentation was performed 371 times with 90% of the threshold and minsize = 5; the process was converged in 37 to 41 iterations. The following segments are defined for images: 4515 for 2015, 4813 for 2016, 4114 for 2017, 5090 for 2018, 6021 for 2019, 3187 for 2020, 2445 for 2022, and 5181 for 2023. The percent convergence is 98% for the processed images. Detecting variations in land cover patterns is possible using spaceborne datasets and advanced applications of scripting algorithms. The implications of cartographic approach for environmental landscape analysis are discussed. The algorithm for image processing is based on a set of GRASS GIS wrapper functions for automated image classification.
The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is ...notable for a complex tectonic origin and geologic formation related to the Cretaceous history of the continents. This is reflected in the varying age of the oceanic crust adjacent to the plateau and the highly heterogeneous bathymetry of the Kerguelen Plateau, with seafloor structure differing for the southern and northern segments. Remote sensing data derived from marine gravity and satellite radar altimetry surveys serve as an important source of information for mapping complex seafloor features. This study incorporates geospatial information from NOAA, EMAG2, WDMAM, ETOPO1, and EGM96 datasets to refine the extent and distribution of the extracted seafloor features. The cartographic joint analysis of topography, magnetic anomalies, tectonic and gravity grids is based on the integrated mapping performed using the Generic Mapping Tools (GMT) programming suite. Mapping of the submerged features (Broken Ridge, Crozet Islands, seafloor fabric, orientation, and frequency of magnetic anomalies) enables analysis of their correspondence with free-air gravity and magnetic anomalies, geodynamic setting, and seabed structure in the southwest Indian Ocean. The results show that integrating the datasets using advanced cartographic scripting language improves identification and visualization of the seabed objects. The results include 11 new maps of the region covering the Kerguelen Plateau and southwest Indian Ocean. This study contributes to increasing the knowledge of the seafloor structure in the French Southern and Antarctic Lands.
Mapping seafloor geomorphology is a complex task requiring the integration of advanced cartographic technologies and high-resolution spatial data. This paper provides a comparative geomorphological ...analysis of the Hellenic Trench (HT) and the Pliny Trench (PT) located in the Eastern Mediterranean Sea, southern Greece. These trenches were formed as a result of the tectonic plate subduction in the Eastern Mediterranean Sea: the northward motion of the African and Arabian plates, complicated by the regional geological settings, such as active faults and earthquakes, which resulted in their different geomorphological forms and bathymetric shapes. Technically, this paper presents an example of the advanced scripting mapping by scripting the cartographic toolset of Generic Mapping Tools (GMT), which performs mapping through shell scripts. The maps are based on the high-quality topographic, geological and geophysical data: GEBCO, EGM96, geoid, and marine free-air gravity fields. The GMT builds upon the modules used for data processing. The region was subsetted by ‘grdcut’, analysed by the Geospatial Data Abstraction Library (GDAL) (gdalinfo utility), and visualized by ‘grdimage’. Two segments of the trenches formed in a condition of varying geological and geophysical settings, have been modelled, visualized and compared, as representative cross-sections. As a result of the automated digitizing, spatial interpolation and sequential aggregating of GMT codes, the segments of the cross-sections were represented. The HT (Ionian segment) has an asymmetric one-sided shape; a steepness of 56.8° on the NE side and 7° on the SW flank. The PT has a more symmetric view; a steepness of 42.14° on its NW flank and 26.66° on its SE flank. The PT has a clear peak of the depths at -2600 to -2800 m and the most representative data range at -5000 to -6000 m. The HT has a bimodal data distribution with two peaks. The most frequent data for HT is -3200 m to -3400 m. Compared to PT, the HT is deeper. The histogram shows the peak of data for HT in the interval between -3200 to -3400 m (135 samples) while the PT shows the peak of data in the interval at -2600 to -2800 m (310 samples). Besides, 105 samples of the HT have depths exceeding 4000 m, while only 20 samples were recorded for PT in the same interval. This paper contributes to the geomorphological studies of the general Eastern Mediterranean Sea region, particularly relating to regional seafloor mapping of the Hellenic and Pliny trenches.
The study area is focused on the Mariana Trench, west Pacific Ocean. The research aim is to investigate
correlation between various factors, such as bathymetric depths, geomorphic shape, geographic
...location on four tectonic plates of the sampling points along the trench, and their influence
on the geologic sediment thickness. Technically, the advantages of applying Python
programming language for oceanographic data sets were tested. The methodological approaches
include GIS data collecting, data analysis, statistical modelling, plotting and visualizing. Statistical
methods include several algorithms that were tested: 1) weighted least square linear regression
between geological variables, 2) autocorrelation; 3) design matrix, 4) ordinary least square
regression, 5) quantile regression. The spatial and statistical analysis of the correlation of these
factors aimed at the understanding, which geological and geodetic factors affect the distribution
of the steepness and shape of the trench. Following factors were analysed: geology (sediment
thickness), geographic location of the trench on four tectonics plates: Philippines, Pacific, Mariana
and Caroline and bathymetry along the profiles: maximal and mean, minimal values, as well as the
statistical calculations of the 1st and 3rd quantiles. The study revealed correlations between the
sediment thickness and distinct variations of the trench geomorphology and sampling locations
across various segments along the crescent of the trench.
Cartographic visualization is a key means for the analysis of the Earth's environmental processes. In view of the rapidly increasing multi-source data, cartographic approaches are updated ...accordingly. Mapping of countries characterized by complex geologic settings, such as Tanzania, requires implementation of advanced approaches. Cartographic solutions for the best visualization aim to provide elaborate content in an understandable and interoperable way in multi-disciplinary studies. This study presents such an approach by using Generic Mapping Tools (GMT), R and QGIS for cartographic mapping of Tanzania, with five maps addressing the natural setting (geology, topography, geophysics) and four maps showing the geomorphometric analysis. The 2D maps and the 3D mesh model were made by the traditional Geographic Information System (GIS) and scripting approaches. The features of the geomorphometric maps (slope, aspect, hillshade, elevation) were plotted by means of R. The technical methods are illustrated by the example of scripts. The paper contributes to the regional studies of Tanzania. Keywords: GMT, R, QGIS, Tanzania, cartography.