Assessment of Soil Degradation by Erosion Based on Analysis of Soil Properties Using Aerial Hyperspectral Images and Ancillary Data, Czech Republic

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027049%3A_____%2F17%3AN0000005" target="_blank" >RIV/00027049:_____/17:N0000005 - isvavai.cz</a>

Alternative codes found

RIV/60460709:41210/17:74026

Result on the web

<a href="http://www.mdpi.com/2072-4292/9/1/28" target="_blank" >http://www.mdpi.com/2072-4292/9/1/28</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs9010028" target="_blank" >10.3390/rs9010028</a>

Result language

angličtina

Original language name

Assessment of Soil Degradation by Erosion Based on Analysis of Soil Properties Using Aerial Hyperspectral Images and Ancillary Data, Czech Republic

Original language description

This paper brings an approach for assessment of soil degradation by erosion by means of determining soil erosion classes representing soils differently influenced by erosion impact. The adopted methods include field sampling, laboratory analysis, predictive modelling of soil properties using aerial hyperspectral data and the digital elevation model and fuzzy classification. Different multivariate regression techniques (PLS, SVM, RF and ANN) were applied in the predictive modelling. The properties with satisfying performance (R2 > 0.5) were used as input data in erosion classes determination by fuzzy C-means classification method. The study was performed at four study sites about 1 km2 large representing the most extensive soil units of the agricultural land in the Czech Republic. The influence of site-specific conditions on prediction of soil properties and classification of erosion classes was assessed. The prediction accuracy (R2) of the best performing models predicting the soil properties varies in range 0.8–0.91 for soil organic carbon content, 0.21–0.67 for sand content, 0.4–0.92 for silt content, 0.38–0.89 for clay content and 0.82 for CaCO3. The performance and suitability of different properties for erosion classes’ classification are highly variable at the study sites. Soil organic carbon was the most frequently used as the erosion classes’ predictor, while the textural classes showed lower applicability. The presented approach was successfully applied in Chernozem and Luvisol loess regions where the erosion classes were assessed with a good overall accuracy (82% and 67%, respectively). The model performance in two Cambisol/Stagnosol regions was rather poor (51%–52%). The results showed that the presented method can be directly applied in pedologically homogeneous areas. The sites with heterogeneous structure of the soil cover will require more precise local-fitted models and use of further auxiliary information such as terrain or geological data.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

DF - Pedology

OECD FORD branch

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Project

<a href="/en/project/QJ1330118" target="_blank" >QJ1330118: Using remote sensing for monitoring of soil degradation by erosion and erosion evidence.</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Remote sensing

ISSN

2072-4292

e-ISSN

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Volume of the periodical

9

Issue of the periodical within the volume

1

Country of publishing house

CH - SWITZERLAND

Number of pages

24

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85010677180