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Author(s):  
Colin Daly

AbstractAn algorithm for non-stationary spatial modelling using multiple secondary variables is developed herein, which combines geostatistics with quantile random forests to provide a new interpolation and stochastic simulation. This paper introduces the method and shows that its results are consistent and similar in nature to those applying to geostatistical modelling and to quantile random forests. The method allows for embedding of simpler interpolation techniques, such as kriging, to further condition the model. The algorithm works by estimating a conditional distribution for the target variable at each target location. The family of such distributions is called the envelope of the target variable. From this, it is possible to obtain spatial estimates, quantiles and uncertainty. An algorithm is also developed to produce conditional simulations from the envelope. As they sample from the envelope, realizations are therefore locally influenced by relative changes of importance of secondary variables, trends and variability.


Diversity ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 43
Author(s):  
Carlo Nike Bianchi ◽  
Annalisa Azzola ◽  
Silvia Cocito ◽  
Carla Morri ◽  
Alice Oprandi ◽  
...  

Biodiversity is a portmanteau word to indicate the variety of life at all levels from genes to ecosystems, but it is often simplistically equated to species richness; the word ecodiversity has thus been coined to address habitat variety. Biodiversity represents the core of the natural capital, and as such needs to be quantified and followed over time. Marine Protected Areas (MPAs) are a major tool for biodiversity conservation at sea. Monitoring of both species and habitat diversity in MPAs is therefore mandatory and must include both inventory and periodic surveillance activities. In the case of inventories, the ideal would be to census all species and all habitats, but while the latter goal can be within reach, the former seems unattainable. Species inventory should be commeasured to investigation effort, while habitat inventory should be based on mapping. Both inventories may profit from suitability spatial modelling. Periodic surveillance actions should privilege conspicuous species and priority habitats. Efficient descriptor taxa and ecological indices are recommended to evaluate environmental status. While it seems obvious that surveillance activities should be carried out with regular recurrence, diachronic inventories and mapping are rarely carried out. Time series are of prime importance to detect marine ecosystem change even in the absence of direct human impacts.


2022 ◽  
Vol 14 (1) ◽  
pp. 574
Author(s):  
Emiliia Iakovleva ◽  
Margarita Belova ◽  
Amilcar Soares ◽  
Anton Rassõlkin

This paper examines the possibility of the spatial modelling of the Earth’s natural pulsed-electromagnetic-field measured values, which form a closed profile without the data inside. This geophysical method allows us to map active tectonic movement which breaches the integrity of pipes. During the experiment, 4.5 km of profiles were measured in the Admiralteysky district of St. Petersburg, Russia. Regular electromotive force (EMF) values and anomalous EMF values were obtained, ranging from 0 to 900 µV and above 900 µV, respectively. The anomalous values are associated with tectonic faults in the bedrock. The data obtained are characterized by complex spatial anisotropy associated with the development of two groups of tectonic faults of different orientations. The authors have considered the problems of the spatial modeling of the data obtained. The main problems, the solutions to which should allow the obtaining of adequate models, have been identified. Based on the analysis of the measurement results, geological features of the studied areas, as well as variography, the following possible solutions were proposed: changing the measurement technique; dividing the data array according to the main directions of anisotropy; the need to introduce additional correction coefficients. The problem revealed in this article requires further research on the basis of the obtained results, which will reduce the cost and timing of such studies, and, as a result, give an opportunity to take into account active tectonic disturbances during the construction and scheduled maintenance of underground utilities, which is especially important within the framework of the concept of sustainable development.


Author(s):  
Marco Ciolfi ◽  
Francesca Chiocchini ◽  
Rocco Pace ◽  
Giuseppe Russo ◽  
Marco Lauteri

We developed a novel approach in the field of spatiotemporal modelling, based on the spatialisation of time: the Timescape algorithm. It is especially aimed at sparsely distributed datasets in ecological research, whose spatial and temporal variability is strongly entangled. The algorithm is based on the definition of a spatiotemporal distance that incorporates a causality constraint and that is capable of accommodating the seasonal behaviour of the modelled variable as well. The actual modelling is conducted exploiting any established spatial interpolation technique, substituting the ordinary spatial distance with our Timescape distance, thus sorting, from the same input set of observations, those causally related to each estimated value at a given site and time. The notion of causality is expressed topologically and it has to be tuned for each particular case. The Timescape algorithm originates from the field of stable isotopes spatial modelling (isoscapes), but in principle it can be used to model any real scalar random field distribution.


Transport ◽  
2021 ◽  
Vol 36 (5) ◽  
pp. 386-394
Author(s):  
Simona Šinko ◽  
Bojan Rupnik ◽  
Klemen Prah ◽  
Tomaž Kramberger

A new approach for spatial modelling of transport mode choice is presented in the paper. The approach tackles the problem by considering the trade-off between subjective and objective factors. To obtain mode Preference Rates (PRs) based on subjective factors, the Analytic Hierarchy Process (AHP) method is applied. The objective factors are expressed with the journey time from any point in the map to destination according to the available transport mode choice on the specific connection. The results are presented as PRs of individual transport modes. The model is validated on the conducted the survey, with students of Vienna University of Economics and Business (WU) as a target audience. Members of different target groups (age, national, employment) decide differently regarding the transport choice, so it is better to analyse them separately. The presented model can be used for the city transport planning in any urban area. It can help promote the sustainable modes of transport in the areas that are less adjusted in sustainable manner.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ziyu Zheng ◽  
Xi-an Li ◽  
Li Wang

AbstractLoess presents very unique collapsible behaviour due to its special under-compactness, weak cementation and porousness. Many environmental issues and geological hazards including subgrade subsidences, slope collapses or failures, building cracking and so on are directly caused by the collapsible deformation of loess. Such collapsible behaviour may also severe accidents due to sinkholes, underground caves or loess gullies. Moreover, with the increasing demand of construction and development in the loess areas, an in-depth research towards effective evaluation of loess collapsibility is urged. Currently no studies have made attempts to explore a rather complete and representative area of Loess Plateau. This paper thus provides a novel approach on spatial modelling over Jin-Shan Loess Plateau as an extension to experimental studies. The in-lab experiment results have shown that shown that the porosity ratio and collapsibility follow a Gaussian distribution and a Gamma distribution respectively for both sampling areas: Yan’an and Lv Liang. This establishes the prior intuition towards spatial modelling which provides insights of potential influential factors on loess collapsibility and further sets a potential direction of the loess studies by considering an extra dimension of spatial correlation. Such modelling allows robust predictions taken into account of longitudinal information as well as structural parameters and basic physical properties. Water contents, dry densities, pressure levels and elevations of samples are determined to be statistically significant factors which affect the loess collapsibility. All regions in Lv Liang area are at risk of high collapsibility with average around 0.03, out of which roughly a third of them are predicted to be at high risk. Clear spatial patterns of higher expected collapsibility in the southwest comparing to the northeast are shown adjusting for influential covariates. On reference guidelines for potential policy makings, county-level regions with the highest expected loess collapsibility are also identified.


2021 ◽  
Vol 10 (11) ◽  
pp. 788
Author(s):  
Marcela Jarošová ◽  
František Staněk

The present study is focused on spatial modelling of a kaolin deposit in Karlovy Vary, Czech Republic, and the methodical procedure of development, evaluation and visualization of a 3D model are described step by step. The implementation of this methodology is performed in Visual Studio 2019 with use of the Surfer and Voxler objects from Golden Software. This methodology combined with the newly developed software (Kaolin_A and Kaolin_Viz programs) allow a user to create a variant dynamic model for the same or similar types of deposits. It enables a quick update of the model when changing the input data, based on the new mining exploration or when changing the modelling parameters. The presented approach leads to a more advanced evaluation of deposits, including various estimates of reserves according to pre-specified usability conditions. The efficiency of the developed methodology and the software for the evaluation of the deposit are demonstrated on the kaolin deposit Jimlíkov-East, located near the village Jimlíkov about 5 km west of Karlovy Vary in the Czech Republic.


2021 ◽  
pp. 189-256
Author(s):  
Jay Gao
Keyword(s):  

Author(s):  
Syed Ali Asad Naqvi ◽  
Muhammad Sajjad ◽  
Liaqat Ali Waseem ◽  
Shoaib Khalid ◽  
Saima Shaikh ◽  
...  

The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.


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