Ömer K. Örücü · Department of Landscape Architecture, Faculty of Architecture, Süleyman Demirel University
Twelve QGIS plugins and two desktop applications developed in geographic information systems, remote sensing and spatial modelling are presented below. All are written in Python, implement methods defined in the open scientific literature, and report their outputs together with validation and uncertainty information. All source code is public.
Purpose and function. Classifies the water quality of inland water bodies on two dates against literature thresholds and measures the class-level change between them. Supports chlorophyll-a (ensemble, NDCI, two-band red-edge), turbidity, total suspended solids, Secchi depth and the trophic state index.
Scope. Monitoring of lakes, reservoirs and ponds; documenting eutrophication and trophic state change; producing evidence for wetland management plans; catchment-scale water quality assessment.
STREAM — Spatio-Temporal Robust Ensemble Analysis for Water Monitoring
Purpose and function. Analyses surface water change at pixel scale with multi-index remote sensing and a machine learning ensemble; produces a water probability surface through the original CAWPI index and separates the climate-driven and human-driven components of change by variance partitioning.
Scope. Monitoring lake and reservoir area or volume change; drought and water allocation studies; quantitative attribution of climate versus human influence; catchment management and water policy reporting.
Purpose and function. Retrieves shallow-water depth from Sentinel-2 imagery through band indices calibrated against in-situ soundings, performing the deep-water correction, the vertical datum reduction and the uncertainty budget as separate, individually reported steps.
Scope. Lake and coastal shallow-water bathymetry; volume and storage calculations; wetland depth mapping; reconnaissance where boat access is impossible.
Purpose and function. A three-module system that models soil erosion both with the process-based RUSLE equation and with a machine learning model that deliberately uses none of the RUSLE factors, and evaluates the results with advanced spatial statistics.
Scope. Catchment-scale erosion risk mapping; land use planning and conservation prioritisation; sediment yield estimation in reservoir catchments; targeting afforestation and terracing works.
ORMAN — Optimal Reforestation Multi-criteria ANalysis
Purpose and function. Standardises slope, aspect, elevation, rainfall, soil, erosion risk and human pressure criteria through fuzzy membership functions, combines them with AHP weights and ranks candidate afforestation sites, offering compensatory and partially compensatory aggregation side by side.
Scope. Afforestation and restoration site selection; forest management and rehabilitation planning; buffer zone and conservation prioritisation; appraisal of alternatives in landscape restoration.
Purpose and function. Reclassifies continuous rasters with literature thresholds whose source is recorded; class limits are shown and can be edited before processing, and user-defined schemes are shareable as portable files.
Scope. Reducing vegetation index, topographic, climate, land cover and erosion risk rasters to interpretable classes; keeping classification consistent across multi-date series; standardising map production.
C. ECOLOGY, BIODIVERSITY AND CLIMATE
EcoMap — Recreational Ecosystem Service Use Intensity Mapping
Purpose and function. Maps the actual use intensity of a recreational ecosystem service from field observations using machine learning; aligned with CICES v5.1 and built around buffered splitting and spatial block cross-validation for clustered visitor data.
Scope. Protected area and urban park management; establishing the spatial distribution of visitor pressure; recreation planning and carrying capacity studies; ecosystem service assessment.
EcoMetriQ — Biodiversity Metrics and Spatial Analysis
Purpose and function. Computes the complete alpha–beta–gamma diversity framework and spatially explicit range metrics from species, coordinate and abundance data, reporting estimators that have more than one standard form in both conventions, each labelled.
Scope. Biodiversity inventory and monitoring; comparison of range size against IUCN Criterion B thresholds; protected area planning; data evaluation in ecological monitoring programmes.
Purpose and function. Tests statistically whether a site lies inside a plant species' realised bioclimatic niche; thanks to cross-conformal calibration the class thresholds of its 0–100 score carry a defined probabilistic meaning.
Scope. Species selection in afforestation and restoration; species–site matching; assessing species suitability under climate change; nursery and landscape planting decisions.
D. URBAN ECOLOGICAL INDICES, VALIDATION AND TREND ANALYSIS
EcoIndex Pro — Urban & Ecological Remote Sensing Index Calculator
Purpose and function. Computes urban and ecological remote sensing indices, brings them onto a common scale and reduces them to a single ecological quality score, leaving the normalisation mode and the weighting method as explicit user choices that are recorded with every run.
Scope. Urban ecological quality assessment; heat island and thermal comfort studies; urban planning and green infrastructure prioritisation; multi-date analysis of urban environmental change.
CARAS — Classification Accuracy and Regression Assessment Suite
Purpose and function. Performs design-based accuracy assessment, bias-adjusted area estimation and continuous-map agreement analysis between two rasters, all with confidence intervals, using probability sampling designs and a fixed seed for full reproducibility.
Scope. Validation of land cover and classification maps; comparison of model output against field data; documenting accuracy statements in papers and project reports; reporting area statistics with a margin of error.
MAST — Mann-Kendall And Sen's Slope Trend Analyzer
Purpose and function. Performs pixel-wise non-parametric trend analysis on multi-temporal raster stacks; uses the exact permutation distribution for short records, applies false discovery rate control for multiplicity and offers a variance correction for serial correlation.
Scope. Trend detection in NDVI, land surface temperature, precipitation and water index time series; monitoring desertification, drought and land degradation; spatial analysis of climate change indicators.
E. DESKTOP SOFTWARE
MerQur — Integrated Academic Data Analysis and Reporting Platform
Version 1.0.17 · Windows, macOS, Linux · DOI 10.53463/merqur.2026001
Purpose and function. A desktop application bringing data preparation, statistical analysis, spatial analysis, visualisation and reporting into one interface, with more than 114 analyses in 15 categories and a Turkish, English and Spanish interface including the result texts.
Scope. Statistical analysis in postgraduate theses and journal articles; evaluation of field data in landscape, environmental and agricultural research; studies combining spatial data with statistics; teaching statistics at postgraduate level.
Purpose and function. A desktop application that runs the entire species distribution modelling workflow without programming, covering everything from data preparation to projection through an eight-step workflow and 13 modelling algorithms.
Scope. Species distribution and habitat suitability studies; projections of range change under climate change; setting conservation priorities; modelling practice in biodiversity and ecology courses.