Determination of grid size for digital terrain modelling in landscape investigations—exemplified by soil moisture distribution at a micro-scale

Florinsky, Igor V.; Kuryakova, Galina A.

doi:10.1080/136588100750022804

Cited by 109 publications

(52 citation statements)

References 26 publications

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“…Nevertheless, the plateau and hilly regions of the northwest of Europe are as well affected by slope instability phenomena as, for example, among others, ChampagneArdennes in France (Mare et al, 2002;van den Eeckhaut et al, 2010), Yorkshire in England (Foster et al, 2007), the Flemish Ardennes in Belgium (van den Eeckhaut., 2006), and the Pays d'Auge in France (Fressard et al, 2010. Despite the known activity and serious management issues, few scientists have studied them compared to mountain or coastal regions.…”

Section: Fressard Et Al: Which Data For Quantitative Landslide Sumentioning

confidence: 99%

Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)

Fressard

Thiéry²,

Maquaire

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper aims at assessing the impact of the data set quality for landslide susceptibility mapping using multivariate statistical modelling methods at detailed scale. This research is conducted on the Pays d'Auge plateau (Normandy, France) with a scale objective of 1 / 10 000, in order to fit the French guidelines on risk assessment. Five sets of data of increasing quality (considering accuracy, scale fitting, and geomorphological significance) and cost of acquisition are used to map the landslide susceptibility using logistic regression. The best maps obtained with each set of data are compared on the basis of different statistical accuracy indicators (ROC curves and relative error calculation), linear cross correlation and expert opinion. The results highlight that only high-quality sets of data supplied with detailed geomorphological variables (i.e. field inventory and surficial formation maps) can predict a satisfying proportion of landslides in the study area.

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Section: Fressard Et Al: Which Data For Quantitative Landslide Sumentioning

confidence: 99%

Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)

Fressard

Thiéry²,

Maquaire

2014

Nat. Hazards Earth Syst. Sci.

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“…Previous studies have indicated that topographical variables can be used to explain the spatial distribution of soil properties within landscapes (Odeh et al 1991;Moore et al 1993;Florinsky and Kuryakova 2000;Florinsky et al 2002). An important finding of this study was the substantial increase in the level of Kd prediction obtained for ZT when both soil and topographic data were used, relative to the soil properties only.…”

Section: Possibilities and Limitations Of Digital Terrain Modelling Fmentioning

confidence: 99%

Evaluating the use of digital terrain modelling for quantifying the spatial variability of 2,4-D sorption by soil within agricultural landscapes

Farenhorst

Florinsky²,

Monreal³

et al. 2003

Can. J. Soil. Sci.

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Farenhorst, A., Florinsky, I. V., Monreal C. M. and Muc, D. 2003. Evaluating the use of digital terrain modelling for quantifying the spatial variability of 2,4-D sorption by soil within agricultural landscapes. Can. J. Soil Sci. 83: 557-564.The most sensitive input parameter in many herbicide fate and transport models is the sorption-partitioning coefficient (Kd), a measure of herbicide sorption by soil. Spatial analyses of Kd are traditionally performed using geostatistics, but this approach requires intensive soil sampling and herbicide analysis. This study examined the use of digital terrain modelling as an alternative tool for quantifying the distribution of herbicide sorption within agricultural fields. Soil samples from a conventional-till (CT) and zero-till (ZT) field were analysed for soil organic carbon (SOC), soil pH, clay content, and the 2,4-D ([(2,4-dichlorophenoxy)acetic acid]) soil-water partitioning coefficient. Digital terrain models were used to calculate topographical variables (elevation, slope gradient, slope aspect, horizontal curvature, vertical curvature, mean curvature, specific catchment area, topographic index and stream power index) for each sampling point. Results indicated that topographic variables were adequate predictors of all soil properties in ZT (R 2 ranging from 0.64 to 0.76), and of SOC in CT (R 2 = 0.65, P < 0.001). For CT, 2,4-D sorption by soil was very well predicted with soil properties alone (R 2 = 0.82, P < 0.001) and with soil properties in combination with topographic variables (R 2 = 0.85, P < 0.001), but was less predicted by topographic variables alone (R 2 = 0.50, P < 0.001). For ZT, the level of prediction of 2,4-D sorption by soil was weak with soil properties alone (R 2 = 0.53, P < 0.001) or when topographical variables alone (R 2 = 0.56, P < 0.001) were used, but a substantial increase in the level of prediction was achieved when both soil properties and topographic variables were used (R 2 = 0.73, P < 0.001). We conclude that digital terrain modelling, in combination with soil properties data, is an appropriate approach for predicting the spatial distribution of 2,4-D sorption within undulating-to-hummocky glacial till landscapes in western Canada.Key words: herbicide sorption, topography, zero-tillage, conventional-tillage, digital terrain modelling.Farenhorst, A., Florinsky, I. V., Monreal, C. M. et Muc, D. 2003. Evaluation de l'utilisation de la modélisation numérique du terrain pour quantifier la variabilité de la sorption du 2,4-D par la terre dans les paysages agricoles. Can. J. Soil Sci. 83: 557-564. Pour beaucoup de modèles sur la dispersion et le transport des herbicides dans le sol le paramètre d'entrée le plus variable est le coefficient de distribution de la sorption (Kd). Les analyses du Kd sont généralement réalisées en utilisant des méthodes géostatistiques, mais cette approche requière d'intensifs échantillonnages de terre avec recherche d'herbicides. Notre étude se propose de vérifier l'utilité de la modélisation numérique du terrain comm...

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“…Scale is predominantly considered a function of the resolution of Digital Surface Models (DSMs) (Hengl & Evans, 2009;Mac Millan & Shary, 2009). The dependency of land surface has been confirmed by several researches (Chang & Tsai, 1991;Wood, 1996;Florinsky & Kuryakova, 2000;Evans, 2003;Hengl, 2006;Arrell et al, 2007;Deng et al, 2007;Pogorelov & Doumit, http://www.scholink.org/ojs/index.php/se Sustainability in Environment Vol. 3, No.…”

Section: Introductionmentioning

confidence: 75%

Multiscale Landforms Classification Based on UAV Datasets

Doumit¹

2018

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Determination of grid size for digital terrain modelling in landscape investigations—exemplified by soil moisture distribution at a micro-scale

Cited by 109 publications

References 26 publications

Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)

Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)

Evaluating the use of digital terrain modelling for quantifying the spatial variability of 2,4-D sorption by soil within agricultural landscapes

Multiscale Landforms Classification Based on UAV Datasets

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