-
Je něco špatně v tomto záznamu ?
Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region
V. Penížek, T. Zádorová, R. Kodešová, A. Vaněk,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2006
Free Medical Journals
od 2006
Public Library of Science (PLoS)
od 2006
PubMed Central
od 2006
Europe PubMed Central
od 2006
ProQuest Central
od 2006-12-01
Open Access Digital Library
od 2006-01-01
Open Access Digital Library
od 2006-10-01
Open Access Digital Library
od 2006-01-01
Medline Complete (EBSCOhost)
od 2008-01-01
Nursing & Allied Health Database (ProQuest)
od 2006-12-01
Health & Medicine (ProQuest)
od 2006-12-01
Public Health Database (ProQuest)
od 2006-12-01
ROAD: Directory of Open Access Scholarly Resources
od 2006
- MeSH
- průzkumy a dotazníky MeSH
- půda chemie MeSH
- teoretické modely * MeSH
- zeměpis MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc17023502
- 003
- CZ-PrNML
- 005
- 20200923165400.0
- 007
- ta
- 008
- 170720s2016 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1371/journal.pone.0165699 $2 doi
- 035 __
- $a (PubMed)27846230
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Penížek, Vít $u Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic.
- 245 10
- $a Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region / $c V. Penížek, T. Zádorová, R. Kodešová, A. Vaněk,
- 520 9_
- $a The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area.
- 650 _2
- $a zeměpis $7 D005843
- 650 12
- $a teoretické modely $7 D008962
- 650 _2
- $a půda $x chemie $7 D012987
- 650 _2
- $a průzkumy a dotazníky $7 D011795
- 651 _2
- $a Česká republika $7 D018153
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Zádorová, Tereza $u Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic.
- 700 1_
- $a Kodešová, Radka $u Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic.
- 700 1_
- $a Vaněk, Aleš $u Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic.
- 773 0_
- $w MED00180950 $t PloS one $x 1932-6203 $g Roč. 11, č. 11 (2016), s. e0165699
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/27846230 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20170720 $b ABA008
- 991 __
- $a 20200923165357 $b ABA008
- 999 __
- $a ok $b bmc $g 1239183 $s 984415
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2016 $b 11 $c 11 $d e0165699 $e 20161115 $i 1932-6203 $m PLoS One $n PLoS One $x MED00180950
- LZP __
- $a Pubmed-20170720