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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/60460709:41210/17:74026

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DF - Pedologie

OECD FORD obor

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Projekt

<a href="/cs/project/QJ1330118" target="_blank" >QJ1330118: Monitoring erozního poškození půd a projevů eroze pomocí metod DPZ</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Remote sensing

ISSN

2072-4292

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

24

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-85010677180