Gis in the Studies of Soil and Water Environment

Rozpondek, Rafał; Wancisiewicz, Katarzyna; Kacprzak, Małgorzata

doi:10.12911/22998993/63476

Cited by 6 publications

(3 citation statements)

References 10 publications

(11 reference statements)

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“…The result is affected by several parameters such as range searches, the number of points involved in the analysis, and power factor. The process of IDW interpolation can be divided into the following steps [ 12 ]: Searching for points that meet the criterion of neighborhood (the amount or the distance). Allocating weights to each typed point.…”

Section: Methodsmentioning

confidence: 99%

Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity

Danilov

Pivovarova

Krotova

2018

The Scientific World Journal

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The methodology for assessing the spatial homogeneity of ecosystems with the possibility of subsequent zoning of territories in terms of the degree of disturbance of the environment is considered in the study. The degree of pollution of the water body was reconstructed on the basis of hydrochemical monitoring data and information on the level of the technogenic load in one year. As a result, the greatest environmental stress zones were isolated and correct zoning using geostatistical analysis techniques was proved. Mathematical algorithm computing system was implemented in an object-oriented programming C #. A software application has been obtained that allows quickly assessing the scale and spatial localization of pollution during the initial analysis of the environmental situation.

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Section: Methodsmentioning

confidence: 99%

Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity

Danilov

Pivovarova

Krotova

2018

The Scientific World Journal

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“…ArcGIS desktop was used for this study. It allows collect, processing, searching and output of geographic information [ROZPONDEK et al 2016, LEITMANOVÁ et al 2013.…”

Section: Creation Of Map Outputs In Gismentioning

confidence: 99%

Journal of Water and Land Development

Čimo,

Šinka,

Tárník

et al. 2020

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The aim of the paper is to provide climatic data from the basic elements and characteristics of the energy balance in terms of the current state and in terms of trends and assumptions of their future changes in Slovakia. Climate change affect agriculture and its procedures. Changes in vegetation period in Slovakia of selected vegetables are presented in this study. We used for agro-climatic analysis one hundred climatological stations, which were selected to cover all agricultural regions up to 800 m a.s.l. Actual data and predictions were compared with time period 1961-2010. Due to homogeneity in data measurements, was chosen this period. We obtained climate trends and assumed map outputs of future climate changes by mathematical-statistical methods for horizons of

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“…Spatiotemporal autocorrelation refers to the correlation of events within themselves over space and through time. It reflects the extent to which events with similar properties are clustered or dispersed [15,16]. Spatial autocorrelation analysis aims to analyze whether the variables are spatially correlated and how relevant they are and how they generate hot spots [17,18].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Patterns of Burned Areas Based on the Geographic Information System for Fire Risk Monitoring

Arisanty

Muhaimin

Rosadi

et al. 2021

International Journal of Forestry Research

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Forest and land fires occur every year in Indonesia. Efforts to handle forest and land fires have not been optimal because fires occur in too many places with unclear patterns and densities. The study analyzed the spatiotemporal patterns of burned areas and fire density in fire-prone areas in Indonesia. Data of burned areas were taken from http://sipongi.menlhk.go.id/. The website collected its data from NOAA (National Oceanic and Atmospheric Administration) images. Data were analyzed using the hot spot analysis to determine the spatiotemporal patterns of the burned areas and the kernel density analysis to examine the density of land fires. Findings showed that the spatiotemporal pattern from 2016 to 2019 formed a hot spot value in the peatland area with a confidence level of 90–99%, meaning that land fires were clustered in that area. In addition, the highest density of land fires also occurred in the peatland areas. Clustered burned areas with high fire density were found in areas with low–medium vegetation density—they were the peatland areas. The peatland areas must become the priority to prevent and handle forest and land fires to reduce fire risks.

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Gis in the Studies of Soil and Water Environment

Cited by 6 publications

References 10 publications

Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity

Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity

Journal of Water and Land Development

Spatiotemporal Patterns of Burned Areas Based on the Geographic Information System for Fire Risk Monitoring

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