| Attributes | Values |
|---|
| rdf:type
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| Description
| - Remote sensing data have an important advantage, the data provide spatially exhaustive sampling of teh area of interest instead of having samples of tiny fractions. Vegetation cover is, however, one of the application constaints in soil science. Areas of bare soil can be mapped. These spatially dense data require proper technigues to map identified patterns. The objective of this study was mapping of spatial patterns of bare soil colour brightness in a Landsat 7 satellite image in the study area of Central Bohemia using object-oriented fuzzy analysis. A soil map (1:200.000) was used to associate soil types with the soil brightness in the image. Several approaches to determine membership functions (MF) of the fuzzy rule base were tested. These included a simple manual aproach, k-means clustering, a method based on the sample hisogram, and one using the probability density function. The method that generally provided the best results for mapping the soil brightness was based on the probability density
- Remote sensing data have an important advantage, the data provide spatially exhaustive sampling of teh area of interest instead of having samples of tiny fractions. Vegetation cover is, however, one of the application constaints in soil science. Areas of bare soil can be mapped. These spatially dense data require proper technigues to map identified patterns. The objective of this study was mapping of spatial patterns of bare soil colour brightness in a Landsat 7 satellite image in the study area of Central Bohemia using object-oriented fuzzy analysis. A soil map (1:200.000) was used to associate soil types with the soil brightness in the image. Several approaches to determine membership functions (MF) of the fuzzy rule base were tested. These included a simple manual aproach, k-means clustering, a method based on the sample hisogram, and one using the probability density function. The method that generally provided the best results for mapping the soil brightness was based on the probability density (en)
- Remote sensing data have an important advantage, the data provide spatially exhaustive sampling of teh area of interest instead of having samples of tiny fractions. Vegetation cover is, however, one of the application constaints in soil science. Areas of bare soil can be mapped. These spatially dense data require proper technigues to map identified patterns. The objective of this study was mapping of spatial patterns of bare soil colour brightness in a Landsat 7 satellite image in the study area of Central Bohemia using object-oriented fuzzy analysis. A soil map (1:200.000) was used to associate soil types with the soil brightness in the image. Several approaches to determine membership functions (MF) of the fuzzy rule base were tested. These included a simple manual aproach, k-means clustering, a method based on the sample hisogram, and one using the probability density function. The method that generally provided the best results for mapping the soil brightness was based on the probability density (cs)
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| Title
| - Object- oriented Fuzzy Analysis of Remote Sensing Data for Bare Soil Brightness Mapping
- Objektivně orientovaná fuzzy analýza údajů dálkového průzkumu Země pro mapování světlosti holé půdy (cs)
- Object- oriented Fuzzy Analysis of Remote Sensing Data for Bare Soil Brightness Mapping (en)
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| skos:prefLabel
| - Object- oriented Fuzzy Analysis of Remote Sensing Data for Bare Soil Brightness Mapping
- Objektivně orientovaná fuzzy analýza údajů dálkového průzkumu Země pro mapování světlosti holé půdy (cs)
- Object- oriented Fuzzy Analysis of Remote Sensing Data for Bare Soil Brightness Mapping (en)
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| skos:notation
| - RIV/60460709:41210/06:16376!RIV07-GA0-41210___
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| http://linked.open.../vavai/riv/strany
| |
| http://linked.open...avai/riv/aktivita
| |
| http://linked.open...avai/riv/aktivity
| - P(GA526/06/1182), Z(MSM6046070901)
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| http://linked.open...iv/cisloPeriodika
| |
| http://linked.open...vai/riv/dodaniDat
| |
| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
| |
| http://linked.open...iv/duvernostUdaju
| |
| http://linked.open...titaPredkladatele
| |
| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/60460709:41210/06:16376
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| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - remote sensing, soil colour, digital soil mapping, fuzzy analysis, fuzzy membership function (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...odStatuVydavatele
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| http://linked.open...ontrolniKodProRIV
| |
| http://linked.open...i/riv/nazevZdroje
| |
| http://linked.open...in/vavai/riv/obor
| |
| http://linked.open...ichTvurcuVysledku
| |
| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...vavai/riv/projekt
| |
| http://linked.open...UplatneniVysledku
| |
| http://linked.open...v/svazekPeriodika
| |
| http://linked.open...iv/tvurceVysledku
| - Borůvka, Luboš
- Brodský, Lukáš
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| http://linked.open...n/vavai/riv/zamer
| |
| issn
| |
| number of pages
| |
| http://localhost/t...ganizacniJednotka
| |
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