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EN
The purpose of this study is to present opportunities for using landscape metrics to evaluate geodiversity on individual landscape levels. The research area is located to the west of the Płock Urban and Industrial Agglomeration in Poland. Within this area, hierarchically organized regional units were delimited (Richling, Malinowska, Szumacher 2013). The area is divided into 87 first-level regions, 36 second-level regions and 9 third-level regions. The units have been treated as basic fields for geodiversity analysis purposes using selected landscape measures and metrics, to include area, density, size, edges and diversity (among others, Shannon’s Diversity Index (SDI), Shannon’s Evenness Index (SEI), domination (D) and redundancy (R)) generated in Patch Analyst v. 5, Fragstats v. 4.0, ArcGIS v.10 and Statistica v. 10 software.
EN
This study aims to investigate crop selection and spatial patterns of agricultural fields in a drought-affected region in Isfahan Province, central Iran. Based on field surveys portraying growth stages of the main crops including wheat, alfalfa, vegetables and fruit trees, three Landsat 8 operational land imager (OLI) images were acquired on March 15 (L1), June 27 (L2) and October 1 (L3), 2015. After performing radiometric and atmospheric corrections, Normalized Difference Vegetation Index (NDVI) maps of the images were produced and introduced to the Multi-Resolution Segmentation algorithm to delineate agricultural fields. An NDVI-based decision algorithm was then developed to identify crops devoted to each field. Finally, a set of landscape metrics including Number of Patches (NP), mean patch size (MPS), mean shape index (MSI), perimeter-to-area ratio (PARA) and Euclidian Nearest Neighborhood Distance (ENN) was utilized to evaluate their respective spatial formation. The results showed that nearly 46% of fields are devoted to wheat indicating that the landscape has been dramatically shifted towards wheat monoculture farming. Moreover, the farmers’ inclination to grow crops in large fields (approximate area of 1 ha) with more regular geometric shapes are considered as an effective way of optimising water use efficiency in areas experiencing significant water shortage.
EN
The key objective of the study is to analyse structural characteristics of the landscape from the viewpoint of the structure’s durability, characteristics and speed of change. The research focused on the area surrounding Płock. In the analysed period (1987-2010) slight changes were detected with regard to the land cover, though they were significant in terms of the natural environment. No single dominant process determining land cover change was identified. Fluctuations prevailed (producing a slightly different picture in each microregion), with a fixed pattern maintained. Distribution, shape and spatial location of land cover types are only partly determined by land lie and habitat quality. Fragmentation of the terrain is relatively high, which reflects intense land use, at the same time indicating opportunities to preserve the wildlife and vegetation typical for agrocenoses.
EN
Mining belongs to the types of human activity that have a significant impact on the environment, and especially on the landscape. The main objective of this study is a quantitative diagnosis of the dynamics of land use changes and landscape pattern modification in areas shaped under the influence of processes related to the open pit exploitation of lignite. The study was carried out in the Adamów-Koźmin Lignite Basin, which is a model example of an area affected by strong anthropogenic pressure. An assessment of changes was carried out using a set of maps depicting land use in the period preceding the exploitation of lignite (the year 1940) and after over 60 years of the mining activity in this area (as of 2011). The source materials for mapping for the first period were archival maps and for the second period, an orthophotomap. The heads-up digitising method was used to determine 7 types of land-cover classes according to the definitions of Corine Land Cover. Ten landscape metrics for five categories of landscape features (surface, shape, neighbourhood, edge, spatial distribution and diversity) were used in the landscape pattern analysis. The results do not confirm the hypothesis of a significant landscape simplification after reclamation. The shape of patches in the landscape was more complex and the number of land-use types was higher, which combined with their spatial arrangement, caused the landscape pattern to be more diversified in the year 2011.
PL
W niniejszej pracy zaprezentowano wyniki porównania wartości wybranych metryk krajobrazowych otrzymanych na podstawie obliczeń wykonanych dwiema metodami: metodą tradycyjną, w której pomiarów dokonuje się po zrzutowaniu mozaiki jednostek przestrzennych na powierzchnię planimetryczną, oraz metodą uwzględniającą trzeci wymiar krajobrazu – opartą na analizie numerycznego modelu terenu. Badania wykazały, że zastosowane metody mogą mieć wpływ na uzyskany obraz struktury krajobrazu wysokogórskiego. Ponadto w pracy zawarto uwagi dotyczące obliczania średniej szorstkości powierzchni oraz analiz wykonywanych przy wykorzystaniu pól geometrycznych w danym typie krajobrazu.
EN
The aim of the authors was to compare values of 2D and 3D landscape metrics in high mountains. The first part of the work takes into consideration the spatial structure of vegetation (the rank of landscape facias/ecotopes) of Kocioł Goryczkowy Świński, which was investigated in 1999 by Anna Kozłowska and Anna Jakomulska. The calculation of landscape metrics is resumed using the true surface geometries and compared with the result of traditional measurements on a reference plane. In the second part of the paper, a set of commonly used landscape metrics is calculated for the geocomplexes (rank of uroczysko unit) in the Morskie Oko catchment using both true surface and plain geometries. Finally average surface roughness is computed for the both study areas and some remarks for landscape metrics computed for geometric fields are given. The comparison shows that appropriate 2D and 3D metrics may differ significantly. Moreover, there is a strong correlation between the size of the discrepancy and the surface slope. For that reason, it is very important to distinguish between 2D and 3D metrics and to use them consciously, according to the particular problem.
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