GDAL and PROJ Libraries Integrated with GRASS GIS for Terrain Modelling of the Georeferenced Raster Image

Lemenkova, Polina; Debeir, Olivier

doi:10.3390/technologies11020046

Cited by 10 publications

(8 citation statements)

References 62 publications

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“…Programming methods and scripts present the recent trend widely used in geospatial data processing. Scripting emerged as a powerful alternative to the traditional GIS (Lighezzolo et al, 2019;Lemenkova and Debeir, 2023b;Bu et al, 2015). Among the diverse existing methods and software that can be used for satellite image processing, a scripting-based approach of GRASS GIS stands apart due to its advantages and functionality.…”

Section: Methodsmentioning

confidence: 99%

Using open-source software GRASS GIS for analysis of the environmental patterns in Lake Chad, Central Africa

Lemenkova

2023

Die Bodenkultur: Journal of Land Management, Food and Environment

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Summary Lake Chad, situated in the semi-arid region of African Sahel, plays a vital role in hydrogeological balance of regional ecosystems. It presents an essential water source and provides a habitat for rare wildlife species including migrating waterbirds. However, the lake has shrunk significantly since the 1960s and has continued to reduce in size and extent during recent decades. Trends in drying and shrinking of Lake Chad are caused by environmental factors and changed climate. The desiccation of the lake is threatening environmental sustainability. This study focused on identification of changes in the Chad Lake area, wetland extent, and associated land cover types. The methods include the Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) for remote sensing data classification. The maximum likelihood discriminant analysis classifier was applied for analysis of multispectral Landsat 8–9 OLI/TIRS images in 2013, 2017, and 2022. Detected changes in land cover types reflect variations in water balance and wetland area and extent around Lake Chad over recent decades. Cartographic scripting tools of GRASS GIS provide an efficient method of digital image processing for monitoring endorheic lakes of Central Africa. GRASS GIS methods provide an opportunity to automatically classify Earth observation data with cartographic scripts for environmental monitoring.

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Section: Methodsmentioning

confidence: 99%

Using open-source software GRASS GIS for analysis of the environmental patterns in Lake Chad, Central Africa

Lemenkova

2023

Die Bodenkultur: Journal of Land Management, Food and Environment

Self Cite

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“…Another problem in the commercial GIS is data format handling. In contrast, scripting methods of cartographic approach present more in-depth ways of data processing and visualization (Lemenkova and Debeir, 2022b, 2023c, 2023d. Scripting ensures an effective solution to automation in data processing.…”

Section: Methodsmentioning

confidence: 99%

Correlations between the Topography-Induced Gravity, Terrain Structure and the Seismicity in the Gulf of Panama

Lemenkova

Debeir

2023

EREM

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This study presents new maps of the topographic and geophysical setting and seismicity in the region of the Gulf of Panama. The spatial analysis is based on the comparative analysis of the datasets on geoid, free-air gravity anomaly, topography and earthquakes. The cartographic framework is developed using the Generic Mapping Tools (GMT) scripting toolset. Seismic activity in the Central America is high due to the complex geologic setting, tectonic activity and lithosphere plate subduction. The data include the Earth Gravitational Model (EGM2008), the General Bathymetric Chart of the Oceans (GEBCO) and gravity grids. The seismicity data were collected from the Incorporated Research Institutions for Seismology (IRIS) catalogue on 1970–2021. The variations in data were compared to analyse correlations between the geophysical, seismic and topographic parameters. Free-air gravity, geoid and topographic data derived from the high-resolution datasets were used to investigate their effects on the main seismic sources in the region. The comparison of the maps showed that the distribution of the shallow earthquakes in the Pacific segment of Panama coincides with negative free-air anomalies and lower geoid values. The results revealed high values of geoid in the high mountainous regions of Panama (Cordilliera de Talamanca, southern coast of Peninsula de Azuero and eastern Panama, 77.5–78.5°W), which correspond to the topographic roughness in the highlands. Negative values of geoid are found over the Caribbean Sea basin (−4 to 0 m). The analyses of seismicity showed 1740 earthquake events varying by magnitudes from 2.9 to 7.8 at the depths up to 225 m (near the west coast of Colombia). A high concentration of the earthquakes is in the western region of the Panama’s shelf waters (~82–83.5°W), and on the border with Colombia (~77–78.5°W). High gravity anomalies (over 220 mGal) are found in the mountainous regions which match the geodynamic processes associated with the Earth structure and geodetic and geophysical effects. The regions of the high seismicity were defined in the Gulf of Chiriqui and eastern part of the Gulf of Panama.

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“…The image series was acquired automatically through the Application Programming Interface of Google Earth Engine (API-GEE) 44,45 and Python 3.8, manipulating data using functions from the Pandas 46 and GDAL 47 libraries. We considered images obtained by the Sentinel-1 (A and B) satellites, which operate in the C band (5.405 GHz) with a spatial resolution of 10 m, temporal resolution of 12 days and in VV and VH polarization.…”

Section: Experimental Designmentioning

confidence: 99%

Unsupervised burned areas detection using multitemporal synthetic aperture radar data

Simões,

Negri,

Souza

et al. 2024

J. Appl. Rem. Sens.

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Climate change is a critical concern that has been greatly affected by human activities, resulting in a rise in greenhouse gas emissions. Its effects have far-reaching impacts on both living and non-living components of ecosystems, leading to alarming outcomes such as a surge in the frequency and severity of fires. This paper presents a data-driven framework that unifies time series of remote sensing images, statistical modeling, and unsupervised classification for mapping fire-damaged areas. To validate the proposed methodology, multiple remote sensing images acquired by the Sentinel-1 satellite between August and October 2021 were collected and analyzed in two case studies comprising Brazilian biomes affected by burns. Our results demonstrate that the proposed approach outperforms another method evaluated in terms of precision metrics and visual adherence. Our methodology achieves the highest overall accuracy of 58.15% and the highest F1 score of 0.72, both of which are higher than the other method. These findings suggest that our approach is more effective in detecting burned areas and may have practical applications in other environmental issues such as landslides, flooding, and deforestation.

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GDAL and PROJ Libraries Integrated with GRASS GIS for Terrain Modelling of the Georeferenced Raster Image

Cited by 10 publications

References 62 publications

Using open-source software GRASS GIS for analysis of the environmental patterns in Lake Chad, Central Africa

Using open-source software GRASS GIS for analysis of the environmental patterns in Lake Chad, Central Africa

Correlations between the Topography-Induced Gravity, Terrain Structure and the Seismicity in the Gulf of Panama

Unsupervised burned areas detection using multitemporal synthetic aperture radar data

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