The Influence of Landscape Structure on Wildlife–Vehicle Collisions: Geostatistical Analysis on Hot Spot and Habitat Proximity Relations

Vehicle collisions with animals pose serious issues in countries with well-developed highway networks. Both expanding wildlife populations and the development of urbanised areas reduce the potential contact distance between wildlife species and vehicles. Many recent studies have been conducted to better understand the factors that influence wildlife–vehicle collisions (WVCs) and provide mitigation methods. Most of these studies examined road density, traffic volume, seasonal fluctuations, etc. However, in analysing the distribution of WVC, few studies have considered a spatial and significant distance geostatistical analysis approach that includes how different land-use categories are associated with the distance to WVCs. Our study investigated the spatial distribution of agricultural land, meadows and pastures, forests, built-up areas, rivers, lakes, and ponds, to highlight the most dangerous sections of roadways where WVCs occur. We examined six potential ‘hot spot’ distances (5–10–25–50–100–200 m) to evaluate the role different landscape elements play in the occurrence of WVC. The near analysis tool showed that a distance of 10–25 m to different landscape elements provided the most sensitive results. Hot spots associated with agricultural land, forests, as well as meadows and pastures, peaked on roadways in close proximity (10 m), while hot spots associated with built-up areas, rivers, lakes, and ponds peaked on roadways farther (200 m) from these land-use types. We found that the order of habitat importance in WVC hot spots was agricultural land < forests < meadows and pastures < built-up areas < rivers < lakes and ponds. This methodological approach includes general hot-spot analysis as well as differentiated distance analysis which helps to better reveal the influence of landscape structure on WVCs.

A Comparative Study on Noise Pollution Levels In Dhanmondi Area, Dhaka: A Geospatial Analysis

Noise pollution has been recognized as one of the most vital environmental pollutions that affecting urban area’s quality of life. Sound levels at different points of the study area have been recorded and presented spatially by geostatistical analysis. A comparison has been made between the study area data in 2019 and that of 2021. In 2021 the noise level was significantly higher despite the Covid 19 pandemic. The comparative study showed that the noise level of the study area in 2021increased significantly. Noise level data in the sample points of the study area on Friday (holiday) were also collected and found that it was higher than that of even working days, especially in the evening. J. Asiat. Soc. Bangladesh, Sci. 47(2): 99-108, December 2021

MBGapp: A Shiny application for teaching model-based geostatistics to population health scientists

User-friendly interfaces have been increasingly used to facilitate the learning of advanced statistical methodology, especially for students with only minimal statistical training. In this paper, we illustrate the use of MBGapp for teaching geostatistical analysis to population health scientists. Using a case-study on Loa loa infections, we show how MBGapp can be used to teach the different stages of a geostatistical analysis in a more interactive fashion. For wider accessibility and usability, MBGapp is available as an R package and as a Shiny web-application that can be freely accessed on any web browser. In addition to MBGapp, we also present an auxiliary Shiny app, called VariagramApp, that can be used to aid the teaching of Gaussian processes in one and two dimensions using simulations.

VARIABILIDADE ESPACIAL E CORRELAÇÃO DOS ATRIBUTOS DO SOLO COM PRODUTIVIDADE DO MILHO E DA SOJA

O emprego de técnicas de agricultura de precisão, associadas a análises geoestatísticas, possibilita mapear a variabilidade espacial existente em um campo de produção. O conhecimento da variabilidade é importante ferramenta na tomada de decisões quanto ao manejo da área, uma vez que possibilita que este seja realizado de forma localizada. O estudo foi realizado em um talhão da Fazenda Planalto, localizada no município de Maracaju – MS, com o objetivo de avaliar a variabilidade espacial e correlação entre os atributos químicos e granulométricos do solo e a produtividade do milho e da soja. Foi utilizada uma grade amostral contendo 187 pontos, utilizando-se 10 amostras simples de solo por ponto amostral. Não foi detectado dependência espacial para o cálcio, alumínio, acidez potencial, soma de bases, ferro e zinco. As melhores estimativas em locais não amostrados foram obtidos para a areia e argila. A produtividade da soja apresentou forte dependência espacial e se correlacionou positivamente de forma forte com o fósforo e moderada com o magnésio. Palavras-chave: Latossolo; dependência espacial; Glycine max; Zea mays. Spatial variability and correlation of chemicals and physical soil attributes with corn and soybean yield ABSTRACT: The use of precision farming techniques, associated with geostatistical analysis, makes it possible to map the spatial variability in a production field. The knowledge of variability is an important tool in decision making regarding the management of the area, since it allows it to be carried out in a localized manner. The study was carried out in a plot of Fazenda Planalto, located in the municipality of Maracaju - MS, with the objective of evaluating the spatial variability and correlation between the chemical and granulometric attributes of the soil and the corn and soybeans yield. A sampling grid containing 187 points was used, using 10 simple soil samples per sample point. No spatial dependence was detected for calcium, aluminum, potential acidity, sum of bases, iron and zinc. The best estimates in unsampled locations were obtained for sand and clay. The soybeans yield showed strong spatial dependence and was positively correlated strongly with phosphorus and moderately with magnesium. Keywords: Oxisol; spatial dependence; Glycine max; Zea mays.

Landscape Diversity and the Directions of Its Protection in Poland Illustrated with an Example of Wielkopolskie Voivodeship

As part of the implementation of the provisions of the European Landscape Convention, a landscape audit of the provinces has been underway in Poland for a few years. The main objectives of the audit are the delimitation of landscape units, assessment of their values, and identification of the priority of landscapes to be protected. This study presents the results of research on the landscape division of the Wielkopolskie voivodeship and a geostatistical analysis of the differentiation of ecological units. With reference to legal regulations in force in Poland, the landscape diversity of the province was characterized using two divisions: geophysical regionalization and landscape typology. In the case of regional division, the meso- and microregions of physical and geographical rank are referenced. The proposed microregional division is the first example in Poland of such a detailed landscape analysis completed for the area of the voivodeship. In the case of typological division, the study conducted in cooperation with the Wielkopolska Bureau of Spatial Planning in Poznań was used. The statistical analysis included metrics to quantitatively characterize landscape composition, including the landscape division index (DIVISION), Shannon’s diversity index (SHDI), and Simpson’s diversity index (SIDI). The results of the study were then compared with the distribution of areas associated with different forms of landscape protection such as national parks, landscape parks, and protected landscape areas. The applied methodology and the results obtained indicate the important role of physical and geographical microregions in the complex analyses of landscape diversity and their broad application in procedures connected with landscape planning and environmental protection.