Abstract We developed a comprehensive set of tools to simplify the design and layout of subsurface drainage systems. These tools, which utilize publicly available LiDAR (light detection and ranging) datasets, may also be used for other applications. The tool streamline operations include harmonizing geographic information system (GIS) layers into a single State Plane or Universal Transverse Mercator Coordinate System, clipping and thinning LiDAR data within a defined boundary, generating drainage networks with contour lines and laylines for surface flow visualization, identifying depressions and creating gridlines with user‐specified angles and spacings. To showcase their use, an illustrative example using a diverse dataset from the University of Illinois’ South Farm is provided. These user‐friendly tools, optimized for compatibility with all versions of QGIS3 (quantum geographic information system 3), are freely accessible for download or installation from the official QGIS plugin repository. A user manual with step‐by‐step instructions is available online on the Illinois Drainage Guide website.

Coastal instability in the form of rock fall is widespread along the northern coasts of Malta and is strictly connected to structural controls, such as lithology and tectonics. The local geological and geomorphological setting combined with extreme weather events, whose spatial and temporal occurrence is enhanced by ongoing climate and land use change, determines rock-fall hazard along the north–west coast of Malta, a hotspot for Mediterranean tourism. The present research portrays the results of a pilot study aimed at analyzing rock-fall runout probability along this stretch of coast. Cliffs and downslope terrains were the object of detailed field surveys. This included the detection of persistent joints in the source areas and the identification of slope-forming materials like debris and boulders present along the downslope terrains. The outcomes of the field surveys and GIS-based processing of topographic information were used for identification of the input parameters for rock-fall runout simulation. The latter was performed using a QGIS based plugin (QPROTO) that allows to determine expected runout extents and assess the rock-fall susceptibility. The result is the characterization and mapping of rock-fall runout probability zones along six investigated sites. The outputs of the research and the replicability of the method can be of interest for authorities aiming at defining risk management actions and undertaking mitigation measures compliant with sustainable development of coastal areas.

Abstract. The FAO WaPOR (Water Productivity Open Access Portal) is a significant initiative developed by the Food and Agriculture Organization of the United Nations (FAO). It provides extensive datasets derived from remote sensing, specifically aimed at monitoring water productivity in agriculture. The primary goal of WaPOR is to enhance water use efficiency and promote sustainable agricultural practices globally. Given the importance of this datasets and with the objective to streamline access to the datasets for users, we have developed WaPLUGIN. WaPLUGIN is a QGIS plugin designed to help users easily retrieve WaPOR datasets directly into QGIS environment and enables the computation of various performance metrics that are useful to assess efficiency of the irrigation schemes. This plugin is a useful tool which helps users and stakeholders to focus on the interpretation of the datasets and make subsequent decisions. The plugin also helps to download and process the WaPOR data.

Introducing MapSWAT: An open source QGIS plugin integrated with google earth engine for efficiently generating ready-to-use SWAT+ input maps.

The eastern flank of the Argentine Frontal Cordillera at ~30°30’ S is a remote area with rugged topography and high elevations that hinder geological field mapping. This task is also challenging because several outcrops are dominated by Permian-Triassic and Cenozoic volcanic rocks of intermediate to acid compositions with scarce geochronological age constraints. In this work, we use ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data to clarify the structural and stratigraphic framework of the region. Visible and near infrared (VNIR) and shortwave infrared (SWIR) band combinations, integrated with field observations, are effective in identifying first-order geological features. In addition, the Semi-Automatic Classification Plugin (SCP; a free open-source plugin for QGIS) is capable of discriminating lithological units and is especially useful to visualize their distribution. Results presented here allow us to characterize Permian-Triassic and Cenozoic units, propose tentative correlations between the Permian-Triassic rocks, and outline major tectonic structures in the study area. This work demonstrates the capability of ASTER data to improve geological mapping, especially in those places where field work is difficult.

The qualitative dimensions of visible features in space can be captured by connecting spatial configurations arranged in a variety of different ways to diverse conceptual spaces. By conceptual spaces, we intend mental concepts describing specific spatial configurations present in a geographical area, defined by the contextual relationships among their constitutive elements.This paper presents a new supervised post-classification method allowing the extraction of semantically complex spatial objects from a single image of the Earth as, for instance, diverse conceptual spaces referring to multiple dimensions of land use (temporal, cultural, social, etc.).Computationally, our method is operationalised by CONTEXTS.py (CS.py), a plugin written in Python for QGIS. CS.py relies on training areas, defined by the user at diverse scales, to identify and extract in the input image conceptual spaces whose spatial contexts have the same spatial features present in the training areas.Applied to a case study on the island of Sicily, where millennial land use dynamics have resulted in a mosaic landscape, CS.py could detect from an orthophoto diverse conceptual spaces of land use in an area ordinarily classified as one land cover, thus expanding the capabilities of geospatial analysis to reach additional qualitative dimensions of information from image data.•CS.py simplifies a supervised contextual post-classification routine in an easy-to-use, practical and accessible QGIS plugin;•CS.py joins a family of tools for supervised object-based classification (e.g. OTB, GRASS), providing, additionally, the possibility to include contextual information as spatial criteria to train the classification routine.•CS.py has broad applications in different disciplines investigating landscape from quantitative and qualitative perspectives, allowing both, as in multiple environments.

Abstract. The Unified Map and Data Sharing or UMD-Sharing Project are tools and protocols for the preparation of a unified map for the various tenure instrument. It aims to provide NGAs and LGUs with guidelines on how to effectively utilize several tenure data from various NGA and LGU sources. With varying scales of data sources, in both spatial and textual dimensions, the project aims to explore these dimensions to create the Unified Map’s spatial data model. In general, map is regarded as a basic tool in land administration and management (LAM) and a unified map’s solution of harmonizing these disparate tenure instruments could mitigate conflicts. To implement the Unified Map and to show how data sharing is handled among the different organizations, including the LGUs, the project developed a QGIS plugin interface that can utilize a remote database repository.

AIRS: A QGIS plugin for time series forecasting using deep learning models

Planning shared mobility hubs in European cities: A methodological framework using MCDA and GIS applied to Barcelona

A management unit-based land cover change analysis was examined in Kahayan Tengah Forest Management Unit (FMU) to understand past, present, and future land cover to assist forest management planning in Kahayan Tengah FMU. This study aims to model land cover change in 2011 and 2016, predict 2021, and simulate land cover in 2026 in Kahayan Tengah FMU. Modeling land cover prediction and simulation using MOLUSCE from the QGIS plugin. The results revealed that agricultural land experienced significant increase in total area during 2011–2016. Modeling potential land cover transitions in 2011 and 2016 with the Artificial Neural Network method showed a Kappa coefficient of 0.701 in the good category, and simulation of land cover in 2021 with the Cellular Automata method showed a Kappa coefficient of 0.672 in the good category. By 2026, the agricultural land will continue to increase while forest land tends to remain stable in its total area. This study managed to predict land cover in 2021 and simulated 2026 with good accuracy. Thus, this data and information can support forest management planning in Kahayan Tengah FMU. Keywords: forest management unit, Kahayan Tengah, land cover change, land cover prediction, MOLUSCE

Introducing QAnnAGNPS - A QGIS plugin to facilitate the use of AnnAGNPS (Annualized Agricultural Nonpoint source model)

Exposure to environmental noise can have significant health effects, including environmental sleep disorders, hypertension, ischemic heart disease, and stroke. Accurately predicting sound levels and estimating health risks is critical to studying the exposure-response relationships and formulating effective policies at the local community level. However, such predictions typically require specialized knowledge, expensive commercial software, and extensive computational resources. To address this issue, the author has developed a solution that integrates publicly available vector tile maps, open source environmental noise modeling modules called "Noise-Modelling", and user interfaces implemented in QGIS through a dedicated QGIS plugin. This plugin allows for direct execution of the calculation modules implemented in NoiseModelling, ensuring compatibility with future updates to NoiseModelling. Users can easily access and manipulate geographic features, define receiver points, predict sound levels, and estimate health risks for any desired area using the plugin. For a relatively small computational domain, such as 1 km2, the volume of calculations is manageable and can be performed on a local computer. This plugin is invaluable for conducting epidemiological research on the health effects of environmental noise and for noise policy planning. It facilitates the maintenance of a quiet environment, helps to mitigate noise problems, and aids in estimating the noise generated by new sources.

The distribution of wild animals and their monitoring over large areas raises many logistical and technical difficulties that hinder the collection of observation data. The use of Geographic Information Systems (GIS) has increased significantly in recent years. QGIS, an open-source GIS software dedicated to the processing of geospatial data, enables the development of dedicated plugins for specific workflows. The open-source PelaSIG plugin has been developed in Python for QGIS 3 to facilitate and standardise the different steps before and after distance sampling surveys. It brings together a set of tools for survey preparation, automatic data checking, visualisation and presentation of survey effort and sightings to provide an adapted workflow. This plugin is currently designed to process dedicated aerial datasets collected with the SAMMOA software during marine megafauna surveys (i.e., marine mammals, seabirds, elasmobranchs, sea turtles, etc.). Here, we first describe the different tools already available, and then, we present an application with the dataset from the aerial survey of the ACCOBAMS Survey Initiative (ASI) conducted in 2018 over the Mediterranean Sea and using a multi-target protocol.

The subject of this research was to develop an effective strategy for combining various data sources, including the feasibility of implementing BIM in CityGML into an existing system supported by the GIS program. The study analyzed the path for converting BIM files to the CityGML format and the course of transmission of this data and data from the completed queries to the GIS program. An overview of external sources, map services, tools for acquiring accurate information about the terrain, and IT tools that could potentially be used was also carried out. The collected data proved deficiencies in the geospatial information of the analyzed area, defining the type of missing data necessary for the planned analyses. The results made it possible to determine further work and the basis for developing a plugin for the QGIS program. The plugin should facilitate energy efficiency, urban, and architectural analyses. The article also discusses the future opportunities for developing research directions for developing new 3D models of cities and collecting data for analysis. The analyses took into account the directions of geometric changes in 3D models as the result of the rapid development of digital tools. Ultimately, this research demonstrated the development demand for modern digital tools in the context of spatial and urban analysis, emphasizing the dynamic evolution in the field of GIS and the prospects of accelerating work on the integration of spatial data and their analysis thanks to the possibility of using open-source programs and our own efforts for their expansion.

HighlightsNew publicly accessible drainage design QGIS plugins were developed.These tools were successfully used to create topologically-sound subsurface drainage layout networks.The tools are easy to use and reduce the level of expertise required to prepare drainage networks that can be successfully sized and buried.Abstract. An important step in designing a drainage system is laying out the network. Successful installation and sizing of the system require that the network be topologically sound and unidirectional. Online digitization of drainage systems does not always result in networks that meet these criteria. Tile lines may not be consistently digitized from upstream to downstream, and there may be disconnected segments, dangles, and overshoots. We have developed a set of open-source tools (plugins) in QGIS that convert a series of laterals and mains digitized on a map into a topologically-sound drainage network to facilitate both burying and sizing the drainage lines. Steps include reversing node numbering, if necessary, to ensure that tile nodes are numbered from upstream to downstream, connecting the ends of tile lines that are within a certain tolerance of each other, correcting overshoots, and setting an order for burying or calculating cumulative flow in line segments. An application example is presented using a proposed tile network layout at the university farm to demonstrate the capacity of these new tools to fix topologically disconnected tile lines and generate sound tile networks that can be successfully buried and sized. These easy-to-use tools are compatible with all versions of QGIS3 and may be freely downloaded or installed from the official QGIS Plugin Repository. Keywords: Line Geometry, Plugins, QGIS Software, Tile Layout Routines, Tile Nodes and Lines.

In this research article, we propose a practical methodology for evaluating the affecting potential of detachment areas in rockfalls. Our innovative approach combines an assessment of the visibility of rockfall source areas, with reference to specific rockfall scenarios and elements at risk, considering the rockfall Susceptibility Index to Failure (SIF) of these areas. The result is the characterization of source areas through a rockfall Source Affecting Index (SAI), which considers both the morphology of the slope and the geostructural conditions of the rock walls. This information can be very useful since it aids in optimizing more in-depth analyses, as well as the placement of monitoring instruments or stabilization systems. The proposed methodology has been implemented in the open-source software QGIS through the development of an easy-to-use plugin named Ranking of the Affecting Potential of Detachment Areas in Rockfalls, or “RADAR”. RADAR is designed to be used in conjunction with QPROTO, a well-known QGIS plugin for preliminary rockfall susceptibility/hazard analyses based on a visibility analysis and a simplified mechanical method. To demonstrate the effectiveness of the proposed approach, an application to a case study located in the Western Alps (Bardonecchia, Italy) is presented and discussed in the paper.

Abstract. Climate change poses a significant threat to humans and biodiversity, impacting various aspects of livelihoods, infrastructure, and ecosystems. Understanding climate change and its interaction with the environment is crucial for achieving Sustainable Development Goals. Local Climate Zones (LCZ) play a key role in comprehending climate change by categorizing urban areas also based on their thermal characteristics. This study presents prototype open-source software tools developed to integrate ground and satellite data for LCZ analysis in the Metropolitan City of Milan (Northern Italy). These tools consist of a QGIS plugin to access and preprocess ground-based meteorological sensor data and a client-server platform, based on the Open Data Cube and Docker technologies, for the exploitation of multispectral and hyperspectral satellite data in LCZ mapping and analysis. The tools’ architecture, data retrieval methods, and analysis capabilities are described in detail. The QGIS plugin facilitates the access and preprocessing of ground-based sensor data within the user-friendly QGIS environment. The platform enables seamless ground-sensor and satellite data management and analysis, using Jupyter Notebooks as an interface to support programmatic operations on the data. The proposed tools provide a framework for studying climate change and its local impacts on urban environments, with the potential of empowering users to effectively analyze and mitigate its effects.

Sidewalks are a relevant part of the living space in urban environments but are still rarely mapped. In recent years, the mapping of sidewalks has grown in importance among the OSM and academic communities as a matter of concern for many UN SDGs. To cover this gap, we propose a GitHub-hosted, fully open-source QGIS Plugin entitled "OSM SidewalKreator" to automatically draw the geometries of sidewalks for OSM crossings and curb crossing interfaces. The plugin workflow encompasses the steps of input area selection; data fetching, data cleaning, sidewalk geometries generation; crossings and kerbs generation; optional sidewalk splitting; and data exporting. Furthermore, the tool gives the user the capacity to have control over the process. Our tests revealed that the proposed method embodied by the plugin surpasses the manual process in many contexts, highlighting completeness, topological and thematic accuracies. We conclude that deepening, improving, and increasing the amount of open sidewalk mapping, mainly in the widely available OSM, can be a valuable asset to improve the development of accessibility and mobility worldwide.

Abstract. In the context of climate change, the increasing demand for energy-efficient buildings and sustainable urban development has become a pressing issue due to the significant proportion of global energy consumption and carbon dioxide (CO2) emissions attributable to the building sector. This requires a concerted effort to reduce its environmental impact, and Geographic Information System (GIS) applications are vital tools for achieving this by optimizing heat supply, calculating costs, analyzing profitability, and balancing CO2 emissions. This study aims to address the challenge of achieving energy efficiency and reducing CO2 emissions in the building sector, specifically at the district level. To this end, the research objective is to develop a QGIS plugin that can simulate urban energy demand at the district level by integrating 2D data with CityGML files and connecting QGIS to SimStadt software via API to visualize the simulated urban energy results in 3D on the Web Globe. The proposed plugin leverages the open-source QGIS tool QField to capture building conditions and connect 2D and 3D data on urban energy simulation. Supplementary to this, this plugin provides up-to-date information on energy demand, consumption, CO2 emissions, building component conditions via updating related tables in the database. Decision-makers can use this comprehensive and user-friendly tool to understand and act on the results, ultimately leading to a CO2-neutral district by 2045. The development of the QGIS plugin represents a significant step towards sustainable urban development and climate change mitigation by utilizing GIS applications for optimizing energy demand and reducing CO2 emissions in the built environment.

This work focuses on developing a software system for concurrently analyzing co-located multibeam echo sounder (MBES) datasets and seafloor imagery, fulfilling the need for a unified seafloor data exploration and analysis platform. The system comprises a graphical user interface where image browsing and geospatial data are linked and several toolboxes for extracting backscatter distribution, its angular response, and bathymetric derivatives to ultimately build detailed quantitative reports. The overall objective is to provide an efficient means of understanding the relationships between morphology, backscatter, and the observed biota and, thus, understanding the relationship between the physical and ecological elements of the seafloor. In addition, Groundtruther provides new ways to interpret remotely sensed information derived from MBES and aid the development of spatial distribution models. Furthermore, it could lead to the enrichment of ground-truth databases used to develop formal geophysical models that link acoustic backscatter observations to intrinsic properties of the seafloor.