Here we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS’ spatial capabilities to allow users to add location information to a Zotero library, a free and open source bibliography manager. Literature Mapper enhances the citations in a user’s online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user’s online database via Zotero’s web API. By using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. We evaluate Literature Mapper’s ability to provide insights into the spatial distribution of published literature by mapping the study sites described in academic publications related to California’s coastal strand vegetation. The results of this exercise are presented in static and web map form.

The evaluation of tourism sustainability has become of paramount importance for researchers and decision-makers to better protect tourist destinations, especially with the continuous increase in the number of tourists and visitors that alter the natural components of the environment and degrade ecosystems. Therefore, the use of geographical data is of great significance, particularly in environmental monitoring and land management, due to its ease of use and availability. However, calculating composite indices for sustainability involves several steps and requires a basic understanding of existing models. This article describes the development and design of a package of plugins in QGIS that serves as an easy-to-use tool for processing and automatically calculating economic, environmental, social indices, and the overall index of tourist sustainability. These plugins have been built in Python and designed as QGIS software plugins.

The identification of the most rockfall-prone areas is the first step of the risk assessment procedure. In the case of land and urban planning, hazard and risk analyses involve large portions of territory and thus preliminary methods are preferred to define specific zones where more detailed computations are needed. To reach this goal, we developed the QGIS-based plugin QPROTO, able to quantitatively compute rockfall time-independent hazard over a three-dimensional topography on the basis of the Cone Method. This is obtained by combining kinetic energy, passing frequency and detachment propensity of each rockfall source. QPROTO requires the definition of few angles (i.e., the energy angle ϕ_p and the lateral angle α) that should take into account all the phenomena occurring during the complex block movement along the slope. The outputs of the plugin are a series of raster maps reporting the invasion zones and the quantification of both the susceptibility and the hazard. In this paper, we propose a method to relate these angles to some characteristics of the block (volume and shape) and the slope (inclination, forest density), to provide QPROTO users with a tool for estimating the input parameters. The results are validated on a series of case studies belonging to the North Western Italian Alps.

MzSTools is a plugin for QGIS developed by the Institute of Environmental Geology and Geoengineering of the National Research Council (CNR-IGAG). The plugin has been designed as a set of practical and easy-to-use tools to carry out seismic microzonation (SM) studies, by producing standard compliant geographic database and maps, thus making them accurate, homogeneous and uniform for all municipalities in Italy. A geodatabase based on SQLite/SpatiaLite Relational Database Management System (RDBMS) has been designed to collect and store data related to elements such as: geognostic surveys; bedrocks and cover terrains; superficial and buried geomorphological elements; tectonic-structural elements; elements of geological instability such as landslide zones, liquefaction zones and zones affected by active and capable faults; homogeneous microzones in seismic perspective, microzones characterized by a seismic amplification factor. MzSTools assembles in a single software environment a set of useful tools in a configurable QGIS project template, comprising layers, symbol libraries, cartographic styles and print layouts for the SM maps. The plugin is open source and hosted on the GitHub platform, and available via the official QGIS plugins repository (https://plugins.qgis.org/plugins/MzSTools/).

In the context of precision agriculture (PA), geomatic surveys exploiting UAV platforms allow the trees’ dimensional characterization and crown identification. This paper focuses on the use of low-cost UAV photogrammetry to estimate the trees’ height, as part of a project for the phytoremediation of contaminated soils. Two study areas (Area 1; Area 2) have been chosen, having different characteristics in terms of mean trees’ height (5 m; 0.7 m), to test the procedure even in a challenging context. Three campaigns have been performed in Area 1 at different altitudes (30 m, 40 m, 50 m), and one UAV flight is available in Area 2 (42 m of altitude). The implemented workflow involves the elaboration of the UAV point clouds and DSMs using the standard SfM approach, the vegetation filtering, the generation of the DTM and a GIS-based analysis to obtain the CHMs for the extraction of the trees’ heights based on a local maxima approach. UAV-derived heights have been compared with in-field measurements obtaining promising results in Area 1, confirming the applicability of the procedure for trees’ height extraction, while the application in the context of low trees was more problematic.

This study assesses the applicability of different-resolution multispectral remote sensing images for mapping and estimating the aboveground biomass (AGB) of Carpobrotus edulis, a prominent invasive species in European coastal areas. The performance of three sets of multispectral images with different resolutions was compared: (i) 2.5 cm Ground Sample Distance (GSD), 5 cm GSD and 10 cm GSD images. The images were classified using the supervised classification algorithm Random Forest and later improved applying a sieve filter. The results show that the three tested image resolutions allow constructing reliable coverage maps of C. edulis, with Overall Accuracy values of 89%, 85% and 88% for the classification of the 2.5 cm, 5 cm and 10 cm GSD images, respectively. Samples were also collected, dried and weighed to estimate AGB using the relationship between the Dry Weight and Vegetation Indices (VI). The regressions were evaluated based on their R² and Normalised RMSE. The best-performing VI-DW regression models achieved: R² = 0.87 and NRMSE = 0.09 for the 2.5 cm resolution; R² = 0.77 and NRMSE = 0.12 for the 5 cm resolution; and, R² = 0.64 and NRMSE = 0.15 for the 10 cm resolution. C. edulis area and total AGB were: 3441.10 m² and 28,327.1 kg (with a Relative Error (RE) = 0.08), for the 2.5 cm resolution; 3070.04 m² and 29,170.8 kg (RE = 0.08), for the 5 cm resolution; and, 2305.06 m² and 22,135.7 kg (RE = 0.11), for the 10 cm resolution. Differences were analysed in detail, spatially, to determine their causes. Final analyses suggest that, for C. edulis, multispectral imagery of up to 5 cm GSD is adequate for the estimation of the species’ distribution and biomass.

The aim of this study was to determine the technical potential of the Polish Exclusive Economic Zone and to identify potential areas for offshore wind development. The paper proposes a GIS-based methodology in which a unique set of constraint-related criteria was employed to select the bests sites. These criteria included wind velocity, water depth, distance from nature conser-vation areas, distance from submarine cables and gas pipelines, distance from shipping routes, distance from fishing areas, distance from shipwrecks, distance from coastline. The Analytic Hi-erarchy Process was employed to indicate the best locations. Accordingly, the total suitable marine area of 16218.67 square kilometers was divided into three parts, in which the highly suitable area accounted for 17.55%, the moderately suitable area was 48.56%, and the marginally suitable area was 10.26%. Two different spatial configurations for the deployment of individual wind turbines were considered to assess the offshore wind potential. First configuration could accommodate 3664 turbines with overall electrical capacity equal to 54.96 GW, whereas the second one 2347 turbines with overall electrical capacity equal to 35.2 GW. The technical potential only in highly suitable areas was equal to 15.24 GW and 9.15 GW, respectively. The results were presented in the form of maps over the domain covering with spatial resolution of 1 km x 1 km.

This study aimed to use remote sensing and GIS to detect changes in surface water and wetlands in the Kumasi Metropolis over a period of 20 years (2002-2022). Landsat images were processed using the QGIS software, and the Maximum Likelihood Algorithm was used to perform supervised classification of land use land cover, while raster calculator aided in detecting wetlands by calculation for NDWI, MNDWI, and AWEI. The results showed that the majority of the landscape in the Kumasi metropolis was made up of built-up areas (79.4%), followed by agricultural lands (13.3%) and wetlands (7.3%). Over the 20-year period, built-up areas had gained 20.7% of the total landscape, while agricultural lands and wetlands had lost 16.7% and 4.0%, respectively. All water index methods recorded an increase in non-water cover and a loss of water cover over the period, with surface water decreasing by 5% and non-water land cover increasing by 5%. The study concludes that there have been significant changes in wetlands and surface water land use and land cover within the Kumasi Metropolis over the past 20 years, and recommends the enforcement of legislation on surface water protection in the area to protect wetlands