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Abstract

In GIS systems, the neighbourhood of areas within an analysed region is a term applied usually to raster-screened data. The aim of the study was to adapt this term to vector and descriptive data as well as to systemize models of so defined neighbourhood. The starting point was the assumption that the basic area neighbourhood model may be based on spatial data illustrated with a graph and described with a neighbourhood matrix. It provides the basis for building subsequent models, that are linked with the introduction of new neighbourhood measures, i.e. measures resulting from the characteristics of areas entered in tables of their attributes. Based on the proposed models, spatial analysis related to area neighbourhood can be performed and aggregate models, considered essential in multidimensional analysis of neighbourhood can be developed.
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Authors and Affiliations

Elżbieta Lewandowicz
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Abstract

The research investigates the possibility of applying Sentinel-2, PlanetScope satellite imageries, and LiDAR data for automation of land cover mapping and 3D vegetation characteristics in post-agricultural areas, mainly in the aspect of detection and monitoring of the secondary forest succession. The study was performed for the tested area in the Biskupice district (South of Poland), as an example of an uncontrolled forest succession process occurring on post-agricultural lands. The areas of interest were parcels where agricultural use has been abandoned and forest succession has progressed. This paper indicates the possibility of automating the process of monitoring wooded and shrubby areas developing in post-agricultural areas with the help of modern geodata and geoinformation methods. It was verified whether the processing of Sentinel-2, PlanetScope imageries allows for reliable land cover classification as an identification forest succession area. The airborne laser scanning (ALS) data were used for deriving detailed information about the forest succession process. Using the ALS point clouds vegetation parameters i.e., height and canopy cover were determined and presented as raster maps, histograms, or profiles. In the presented study Sentinel-2, PlanetScope imageries, and ALS data processing showed a significant differentiation of the spatial structure of vegetation. These differences are visible in the surface size (2D) and the vertical vegetation structure (3D).
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Authors and Affiliations

Marta Szostak
1
ORCID: ORCID

  1. University of Agriculture in Krakow, Krakow, Poland
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Abstract

Numerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending its cost function by a relationship directly inspired by the physical formula. This publication explains the concept of Physics-guided neural networks (PGNN), makes an overview of already proposed solutions in the field and describes possibilities of implementing physics-based loss functions for spatial analysis. Our approach shows that the model predictions are not only optimal but also scientifically consistent with domain specific equations. Furthermore, we present two applications of PGNNs and illustrate their advantages in theory by solving Poisson’s and Burger’s partial differential equations. The proposed formulas describe various real-world processes and have numerous applications in the area of applied mathematics. Eventually, the usage of scientific knowledge contained in the tailored cost functions shows that our methods guarantee physics-consistent results as well as better generalizability of the model compared to classical, artificial neural networks.
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Authors and Affiliations

Bartłomiej Borzyszkowski
1
ORCID: ORCID
Karol Damaszke
1
Jakub Romankiewicz
1
Marcin Świniarski
1
Marek Moszyński
1

  1. Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
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Abstract

Local adaptation is a key concept in biology: shift of genetic structures of populations due to differential survival of genotypes is expected to lead to phenotypes providing an advantage in the local environment. Variation of sequences of twelve candidate genes was investigated in 13 Norway spruce (Picea abies (L.) Karst.) provenances originating from sites distributed along an altitudinal gradient from 550 to 1300 m a.s.l. Signals of selection were assessed in 103 single nucleotide polymorphisms (SNP). The Bayesian FST-outlier identification methods as implemented in the programs BayeScan and Arlequin did not identify any SNP with a clear evidence of selection. The approaches relying on SNP-climate associations (spatial analysis method based on logistic regression of allele frequencies with environmental variables, Bayesian method applied in BayEnv2) identified several relationships but none of them remained significant after correction for multiple testing. Gene flow, epigenetic inheritance and former management of the studied populations are discussed as potential reasons for this weak evidence of selection signals.

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Authors and Affiliations

Matúš Hrivnák
Diana Krajmerová
Dušan Gömöry
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Abstract

The red-banded stink bug, Piezodorus guildinii, is an important pest in soybean. Information on its distribution is needed to determine the most effective timing for pest control and strategies to avoid yield losses, such as adequate monitoring. The present study was aimed at examining the temporal variation and spatial distribution of P. guildinii in soybean. The experimental design comprised an area of 5400 m² planted with soybean, with 54 plots of 100 m² each, in which plants were examined weekly for nymphs and adults of P. guildinii with a beating sheet. Evaluations were carried out from soybean emergence to harvest; however, P. guildinii occurred only during the reproductive stage. Based on aggregation indices, theoretical frequency distributions, and semivariograms, nymphs and adults were randomly distributed at the beginning of infestation but, tended to be aggregate during pod setting and seed filling. Our findings have a contribution to improving pest sampling systems and infestation mapping, including future semiochemicals studies.
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Authors and Affiliations

Rafael Azevedo Silva
1
Paulo Eduardo Degrande
2
ORCID: ORCID
Bruno Souza Martins
1
ORCID: ORCID
Ellen Patricia Souza
2
ORCID: ORCID
Marcos Gino Fernandes
2
ORCID: ORCID

  1. Department of Plant Protection, Federal Institute of Mato Grosso do Sul, Brazil
  2. Department of Agricultural Science, Federal University of Grande Dourados, Dourados, Brazil
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Abstract

The development of cities and peri-urban areas is exerting an increasingly strong impact on the natural environment and, at the same time, on the living conditions and health of people. Problems and challenges that need to be addressed include increasing air pollution in these areas, formation of a surface urban heat island (SUHI), water management disruptions (water scarcity or excess), and the destruction of natural habitats. One of the solutions that contributes to climate change mitigation is the introduction of blue-green infrastructure into the city space and urbanised areas. The research objective was to identify spatial features (geodata) that determine the optimum location of selected blue-green infrastructure (BGI) components, acquire them, and then use the Geographical Information System (GIS) to determine their optimum locations. As the first step, cartographic models were developed which indicated areas that enable the development of selected blue-green infrastructure components in the Olsztyn city area, Warmińsko-Mazurskie Province, Poland. The models were juxtaposed with other two models developed by the authors, i.e. a surface urban heat island model and a demographic model that showed the age structure of the city’s population. Consequently, maps with potential locations for the blue-green infrastructure were developed, while taking into account reference data from the National Land Surveying and Cartographic Resource and Landsat 8 images.
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Authors and Affiliations

Szymon Czyża
1
ORCID: ORCID
Anna M. Kowalczyk
2
ORCID: ORCID

  1. University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, Department of Geoinformation and Cartography, Olsztyn, Poland
  2. University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Geodesy and Civil Engineering, Department of Geodesy, St. Heweliusza 12, Olsztyn, Poland
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Abstract

This study presents the indoor soundscape framework in detail by describing the variables and factors that form an indoor soundscape study. The main objective is to introduce a new indoor soundscaping framework and systematically explain the variables that contribute to the overall evaluation of an indoor soundscape. Hence, the dependencies of physical and psychoacoustical factors of the sound environment and the spatial factors of the built entity are statistically tested. The new indoor soundscaping framework leads to an overarching evaluation perspective of enclosed sound environments, combining objective room acoustics research and noise control engineering with architectural analysis. Therefore, it is hypothesised that case spaces with certain plan organisations, volumetric relations, and spatial referencing lead to differentiated sound pressure level (SPL) and loudness (N) values. SPL and N parametric variances of the sound environments are discussed through the statistical findings with respect to the architectural characteristics of each library case space. The results show that the relation between crowd level variances and sound environment parametric values is statistically significant. It is also found that increasing the atrium height and atrium void volume, the atrium’s presence as a common architectural element, and its interpenetrating reference and domain containment results in unwanted variances and acoustic formations, leading to high SPL and N values.
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Authors and Affiliations

Papatya Nur Dokmeci Yorukoglu
Jian Kang

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