Social Values for Ecosystem Services (SolVES) version 4.0 is a fully open-source, GIS-based tool designed to aid in the creation of quantitative, spatially explicit models of the nonmonetary values attributed to cultural ecosystem services, such as aesthetics and recreation, specifically to facilitate their incorporation into larger ecosystem service assessments. Newly redeveloped for QGIS, SolVES

The MODFLOW API allows other programs to control MODFLOW and interactively change variables without having to modify the source code. The MODFLOW API is based on the Basic Model Interface (BMI), which is a set of conventions that define how to initialize a simulation, update the model state by advancing in time, and finalize the run. For many existing MODFLOW coupling applications, the information

Escher tiling is well known as a tiling that consists of one or a few recognizable figures, such as animals. The Escherization problem involves finding the most similar shape to a given goal figure that can tile the plane. However, it is easy to imagine that there is no similar tile shape for complex goal shapes. This article devises a method for finding a satisfactory tile shape in such a situation

Tangles are complex patterns, which are often used to decorate the surface of real-world artisanal objects. They consist of arrangements of simple shapes organized into nested hierarchies, obtained by recursively splitting regions to add progressively finer details. In this article, we show that 3D digital shapes can be decorated with tangles by working interactively in the intrinsic metric of the

In this article, we introduce a compact representation for measured BRDFs by leveraging Neural Processes (NPs). Unlike prior methods that express those BRDFs as discrete high-dimensional matrices or tensors, our technique considers measured BRDFs as continuous functions and works in corresponding function spaces. Specifically, provided the evaluations of a set of BRDFs, such as ones in MERL and EPFL

As low-cost air quality sensors become more widely utilized, more tools and methods are needed to help users access/process sensor data, identify poorly performing sensors, and analyze/visualize sensor data. Free and open-source software (FOSS) packages developed for use on FOSS data science platforms are well-suited to support this need by offering replicable and shareable tools that can be adapted

Water resource management is of crucial societal and economic importance, requiring a strong capacity for anticipating environmental change. Progress in physical process knowledge, numerical methods and computational power, allows us to address hydro-environmental problems of growing complexity. Modeling of river and marine flows is no exception. With the increase in IT resources, environmental modeling

Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of uncertainty. Here we present RODEO, an algorithm for estimating river discharge using Landsat observations

Automatic calibration is widely used to estimate parameters in hydrological models. The main idea is to use optimization algorithms to minimize the discrepancy between field data and simulation prediction. This process involves iterative exchanges of a parameter set chosen by the optimization and simulation. However, for computationally expensive models, such as groundwater flow and transport models

By mapping land use under projections of socio-economic change, ecological changes can be predicted to inform conservation decision-making. We present a land use model that enables the fine-scale mapping of land use change under future scenarios. Its predictions can be used as input to virtually all existing spatially-explicit ecological models. Our model maps the fractional cover of land use within

Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include

Attribute Based Encryption (ABE) can be employed to enforce fine grained access control over encrypted data. Due to expressiveness, ABE schemes are currently employed in cloud computing and storage systems. The classical ABE schemes based on bilinear pairing are vulnerable to quantum cryptanalysis, whereas ABE schemes from lattices can resist quantum attacks. In this work, we comprehensively survey

Eutrophication causes structural changes to the ecosystem of a water body such as increased production of algae and aquatic plants, depletion of fish species, and a general deterioration of water quality. We discuss the development of an Augmented Reality (AR) application (App) based on a generalised system dynamics model of chemical and biological processes involved in the development of algal blooms

Interacting entities in human society and their roles considering land exploration and occupation are crucial for studying land use/cover change (LUCC) in landscape ecology. For investigation of games in LUCC models, this work presents an agent-based decision model based on evolutionary game theory with three layers of interactive deliberation (individual, peer-to-peer, and social) implemented in MASE-EGTI

Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWT's solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we

Organizations collect an ever-increasing amount of data concerning environmental parameters. Non-experts may be confronted with an information overload, making the data meaningless. A way to circumvent this problem is visualizing the trends in the pollution concentrations measured over time. However, non-experts do not have a mental model to derive air quality information from displayed concentration

Under ongoing global warming due to climate change, heat waves in Australia are expected to become more frequent and severe. Extreme heat waves have devastating impacts on both terrestrial and marine ecosystems. A multi-characteristic heat wave framework is used to estimate historical and future projected heat waves across Australia. A Google Earth Engine-based toolkit named heat wave tracker (HWT)

Lake Kivu is a 485 m deep, Central-East African rift lake with huge amounts of carbon dioxide and methane dissolved in its stably stratified deep waters. In view of future large-scale methane extraction, one-dimensional numerical modelling is an important and computationally inexpensive tool to analyze the evolution of stratification and the content of gases in Lake Kivu. For this purpose, we coupled

A framework that integrates Bayesian optimization (BO) and high-performance computing was developed, to automate calibration of complex hydrological models. It adopts a loosely coupled web architecture, integrating Tornado and SpringBoot, to facilitate bidirectional transfer of variables between BO and model evaluation. Extensive model evaluations were implemented on a Hadoop cluster, to wrap the model

Meta-analysis, power analysis, and sensitivity analysis are widespread statistical techniques, which can be correctly performed only if variability statistics, such as standard deviation, are available; however, standard deviations are often missing in published articles. This work illustrates the functionality and the versatility of a newly developed Excel© tool for the standard deviation extraction

We present a fully automatic system that can produce high-fidelity, photo-realistic three-dimensional (3D) digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head and can produce a high-quality head reconstruction in less than 30 s. Our main contribution is a new facial geometry modeling and reflectance synthesis

Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving complex global illumination. One of the most successful variance-reduction techniques is path guiding, which can learn better distributions for importance sampling to reduce pixel noise. However, previous methods require a

In this article, we present TightCap, a data-driven scheme to capture both the human shape and dressed garments accurately with only a single three-dimensional (3D) human scan, which enables numerous applications such as virtual try-on, biometrics, and body evaluation. To break the severe variations of the human poses and garments, we propose to model the clothing tightness field—the displacements

In recent years, Convolutional Neural Networks (CNN) have proven to be efficient analysis tools for processing point clouds, e.g., for reconstruction, segmentation, and classification. In this article, we focus on the classification of edges in point clouds, where both edges and their surrounding are described. We propose a new parameterization adding to each point a set of differential information

This paper presents the Agent-Based Modelling System of spatial distribution of species SDSim. SDSim is an agent-based modelling system designed to simulate spatial distribution of species and populations for conservation and management purposes. SDSim gives to modellers the ability to simulate movements and colonization patterns of species given locations under study and a set of eco-geographical

Watershed models are robust tools that inform management and policy in a variety of sectors, but these models are often neglected through time due to economic or technical constraints. Additionally, they are not readily accessible tools for key decision makers. Conversely, machine learning models are robust alternatives to common hydrologic modeling frameworks. The random forest algorithm specifically

Due to the seasonal increase in soil salt accumulation after cessation of monsoon rains, the simulation of cropping system performance becomes highly challenging in coastal saline cropping areas. Rapidly changing groundwater (GW) dynamics during this period (GW depth and salinity) drive changes in capillary soil moisture rise, soil evaporation and consequent deposition of salts in the crop root zone

Model emulation has become an integral tool in scenario analysis, risk assessment, and calibration of environmental models. Of particular interest is dynamic emulation – the approximation of model outputs from inputs or processes that vary in time. This paper presents a method for data-driven dynamic emulation of high-dimensional model outputs that overcomes the logistical challenges from assumptions

Traditional population viability analysis (PVA) does not address the degree of measurement error or spatial and temporal variability of vital rate parameters, potentially leading to inappropriate conservation decision-making. We provide a methodology of applying Bayesian network (BN) modeling to PVA addressing these considerations, particularly for species with complex stage-class structures. We provide

Subspace clustering is an important unsupervised clustering approach. It is based on the assumption that the high-dimensional data points are approximately distributed around several low-dimensional linear subspaces. The majority of the prominent subspace clustering algorithms rely on the representation of the data points as linear combinations of other data points, which is known as a self-expressive

Sensitivity analysis (SA) as a ‘formal’ and ‘standard’ component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA over the last three decades, and the SAMO (sensitivity analysis of model output) conferences, since 1995, have been the primary driver of breeding a community culture in this heterogeneous

Environmental models are often essential to implement projects in planning, consulting and regulatory institutions. Research models are often poorly suited to such applications due to their complexity, data requirements, operational boundaries, and factors such as institutional capacities. This contribution enhances a modeling framework to help mitigate research model complexity, streamline data and

The rapid development of scene text detection shows us the need for text recognition in a scene image. Road signs recognition, reading the scene image for machine translation, text recognition on commercial products, billboards, and vehicle plates are examples of text recognition on natural images. This review discussed the related research of scene text detection in the last ten years. We analysed

The Universal Soil Loss Equation (USLE) has been the de-facto standard for soil erosion management studies since its seminal publication in the 1970's. Widespread use of the model is due, in part, to its simple empirical modelling structure and parsimonious parameterization; however, these benefits have also led to criticism of its relevance as a tool for estimating soil erosion. While the USLE has

Portability of web applications between web servers of different organizations can be challenging and can complicate sharing and collaborative use of such tools. Given the distributed nature of the web, this lack of portability is usually not a concern because a user in one organization can link to and use a web application hosted by another organization. However, access control or differentiation

TOUGH3 is a powerful numerical tool that simulates the heat and fluid flows in porous and fractured media. However, setting up the “MESH” file for a model with several rock types is tedious and error-prone. This study presents a MATLAB code for converting ArcMap three-dimensional conceptual models into TOUGH3 input files. This code builds a rectangular computational mesh using the MESHMAKER tool and

Grid-based spatially distributed hydrological modeling has become feasible with advances in watershed routing schemes, remote sensing technology, and computing resources. However, the need for long-running times on a substantial set of computational resources prevents a spatially detailed modeling program from being widely used, particularly in fine-resolution large-scale studies. Parallelizing computational

In this paper, two emerging strategies for the reduction of the computational time of 2D large-scale flood simulations are compared, with the aim of evaluating their strengths and limitations and of suggesting guidelines for their effective application. The analysis is based on two state-of-the-art raster flood models with different governing equations and parallelization strategies: PARFLOOD, a GPU-accelerated

There is a need to determine and quantify global change induced phenological asynchrony because of possible loss of biodiversity and implications for the food web. Phenological asynchrony in freshwater lakes can be studied retrospectively by analysing historical data, and prospectively by scenario analysis based on historical data. Models allowing to study phenology by scenario analysis need to be

Data portals and services have increased coastal water quality data availability and accessibility. However, tools to process this data are limited – geospatial frameworks at the land-sea interface are either adapted from open-water frameworks or extended from watershed frameworks. This study explores use of a geospatial framework based on hexagons from a Discrete Global Grid System (DGGS) in a coastal

A comprehensive spatial and temporal understanding of the manganese cycle in drinking water reservoirs has beneficial implications for the management of water treatment related issues. In this study, a three-dimensional manganese cycle model was developed and coupled with a hydrodynamic model, for the simulation of the distribution of manganese in a monomictic water reservoir. The model was successfully

The behavior and impact of trace metals discharged into rivers depend on their solid/liquid fractionation and the fate of these two phases according to hydro-sedimentary processes. The solid/liquid fractionation depends on many environmental factors which imply uncertainties of several orders of magnitude in the evaluation of the partition coefficients, whether by geochemical modelling, in situ measurements

Marine Ecosystem Models (MEMs) provide a deeper understanding of marine ecosystem dynamics. The United Nations Decade of Ocean Science for Sustainable Development has highlighted the need to deploy these complex mechanistic spatial-temporal models to engage policy makers and society into dialogues towards sustainably managed oceans. From our shared perspective, MEMs remain underutilized because they

Approximately 15% of global land is currently in some state of protection. Recent conservation research suggests the need for a drastic increase of protected lands by 2050. In order to reach this target, an additional 35% of lands need to be conserved or restored in a cost-effective and time-efficient manner in order to support the resiliency of our planet and its climate. While many individuals and

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values. We propose a novel method of developing guidelines for calibration of process-based models, based on development of recommendations for calibration of the phenology component of crop models

Land Use Land Cover (LULC) change assessment and prediction are essential for optimised water resources planning and management. This paper attempts to intercompare the different LULC change modelling techniques (two-hybrid and two traditional models) to predict the future LULC change. These include Multi-Layer Perceptron Markov Chain (MLP_MC), Logistic Regression-Markov Model (LR-MC), and two hybrid

In the last decades, the number of publications dedicated to the application of species distribution models (SDMs) to invasive alien plants (IAPs) has constantly increased. Although recent reviews have addressed very relevant issues in the application of SDMs, the modelling approaches (i.e., algorithms) applied to IAPs have not been systematized. Therefore, we undertook a bibliographic review of articles

Composite Indicators (CIs, a.k.a. indices) are increasingly used as they can simplify interpretation of results by condensing the information of a plurality of underlying indicators in a single measure. This paper demonstrates that the strength of the correlations between the indicators is directly linked with their capacity to transfer information to the CI. A measure of information transfer from

Shallow water models are used for simulating flood and lake hydrodynamics. However, the computational cost of those models is often high and require high performance computing. We present the SW2D-GPU: a two-dimensional shallow water model accelerated by General Purpose Graphics Processing Unit. The model is implemented in parallel using CUDA C/C++. We exemplify the use of the model with two case studies:

We present a sparse Gauss-Newton solver for accelerated sensitivity analysis with applications to a wide range of equilibrium-constrained optimization problems. Dense Gauss-Newton solvers have shown promising convergence rates for inverse problems, but the cost of assembling and factorizing the associated matrices has so far been a major stumbling block. In this work, we show how the dense Gauss-Newton

Wrapping objects using ropes is a common practice in our daily life. However, it is difficult to design and tie ropes on a 3D object with complex topology and geometry features while ensuring wrapping security and easy operation. In this article, we propose to compute a rope net that can tightly wrap around various 3D shapes. Our computed rope net not only immobilizes the object but also maintains

Visualization of the outputs from sensitivity analyses of spatially explicit models can potentially enhance the perception of the uncertainty in model outputs. However, spatial global sensitivity analysis (GSA) produces multiple output maps, twice as many as the number of input parameters under investigation, which can result in an overwhelming visual load to interpret. In this research, we tested

porousMedia4Foam is a package for solving flow and transport in porous media using OpenFOAM® - a popular open-source numerical toolbox. We introduce and highlight the features of a new generation open-source hydro-geochemical module implemented within porousMedia4Foam, which relies on micro-continuum concept and which makes it possible to investigate hydro-geochemical processes occurring at multiple

This paper compares the well-known genetic algorithm (GA) and pattern search (PS) optimization methods for forecasting optimal flow releases in a multi-storage system for flood control. The simulation models used by the optimization models include (a) a batch of scripts for data acquisition of forecasted precipitation and their automated post-processing; (b) a hydrological model for rainfall-runoff