Lucian Drǎguţ

West University of Timişoara · Department of Geography

Land suitability assessment is used in conjunction with geographic information systems to spatially model diverse aspects of soil functions, having the potential to facilitate a sustainable increase in agricultural production, reduce land degradation, or aid humans in adapting to climate change. Compared to the existing datasets, this study provide...

Reliable landslide inventories are essential for assessing landslide susceptibility and hazards. Historical landslides provide insights into periods of variable mass movement activity, contrasting with more recent decades. However, landslide features have been altered over time, particularly due to human activities. These features often remain well...

Reliable landslide inventories are essential for assessing landslide susceptibility and hazards. Historical landslides provide insights into periods of variable mass movement activity, contrasting with more recent decades. However, landslide features have been altered over time, particularly due to human activities. These features often remain well...

For assessing landslide susceptibility and hazard reliable landslide inventories are essential. Historic landslides might indicate periods of increased landslide activity compared to more recent decades. However, landslide features might have diminished over time especially due to human impact. Often features of historic landslides are well preserv...

By interpretations related to energy, elementary land surface segmentation can be treated as a physical problem. Many pieces of such a view found in the literature can be combined into a synthetic comprehensive physical approach. The segmentation has to be preceded by defining the character and size of searched units to result from the segmentation...

So far, the estimation of sediment quantities in hydrographic basins has been carried out both in international research and at the national level based on the USLE (Universal Soil Loss Equation) model proposed by Wischmeier & Smith, 1978. Furthermore, the evaluation of the transport capacity of eroded materials through topography can be modeled ba...

Land suitability assessment (LSA) provides geospatial information about growing crops where they are best suited and can play a crucial role in addressing contemporary challenges such as feeding 9 billion people by 2050, coping with climate change, and enabling sustainable production. Despite the known limitations of the current mapping units (conv...

It is long recognized that the processes that define the shape of the landscape operate at specific scales, and that mismatch between the scale of analysis and the scale of the process leads to erroneous results. A priori knowledge is often used in specific applications when appropriate scales are known; otherwise selecting an optimal scale of anal...

This work aims at evaluating the sensitivity of landslide susceptibility mapping (LSM) to sampling design in lithologically-heterogeneous areas. We hypothesize that random sampling of the landslide absence data in such areas can be biased by statistical aggregation of the explanatory variables, which impact the model outputs. To test this hypothesi...

Multiscale methods have become progressively valuable in geomorphometric analysis as data have become increasingly detailed. This paper evaluates the theoretical and empirical properties of several common scaling approaches in geomorphometry. Direct interpolation (DI), cubic convolution resampling (RES), mean aggregation (MA), local quadratic regre...

Scientists have long been developing better and more efficient methods to improve the prediction of the spatial distribution of soils and their presence in the landscape, but research in this field is still needed. This study introduces an algorithm to derive terrain attributes at multiple scales and automatically calibrate the optimal scale for ea...

Traditional methods for individual tree-crown (ITC) detection (image classification, segmentation, template matching, etc.) applied to very high-resolution remote sensing imagery have been shown to struggle in disparate landscape types or image resolutions due to scale problems and information complexity. Deep learning promised to overcome these sh...

Abstract As geomorphological processes operate at various spatial scales, their morphological expressions, i.e., land-surface variables (LSVs) should be scaled accordingly. Most approaches on landslide susceptibility modeling and landslide detection have been performed based on arbitrarily scaled LSVs. We propose a methodology to improve automated...

The intensive use of geophysics in archaeological investigations demands new ways of fast and meaningful data interpretation. With the increasing size and complexity of magnetometer data, manual identification and delineation of magnetic anomalies becomes a time‐consuming activity. In this respect, our study introduces a new approach to automate th...

The complexity of landslides makes it difficult to predict the spatial distribution of landslide susceptibility and hazard. Although in most European countries the basic preconditions for the occurrence of mass movements (rocks and topography) have been mapped in detail, the triggering factors (e.g. precipitation or earthquakes) are much less predi...

Spatial extent (i.e. the size of the study area) is acknowledged as an important component of scale, together with grain (i.e. cell size). While the influence of grain on multiresolution segmentation has been evaluated, the impact of spatial extent is still poorly understood. The main goal of our study was to evaluate how changing the extent affect...

Crayfish can be used as model organisms in phylogeographic and divergence time studies if reliable calibrations are available. This study presents a comprehensive investigation into the phylogeography of the European stone crayfish (Austropotamobius torrentium) and includes samples from previously unstudied sites. Two mitochondrial markers were use...

There is increasing interest for developing automatic procedures for landscape segmentation into soil spatial entities, aiming at replacing conventional, expensive manual procedures for delineating and classifying soils. Geographic object based image analysis (GEOBIA) emerged as a solution to partition remote sensing imagery or digital elevation mo...

Attempts towards a global geomorphometric atlas have been done in the past when computational power was less evolved than nowadays. In this study, we present a possible way to create a global geomorphometric atlas by taking advantage of the Google Earth Engine (GEE) computational capabilities. To exemplify how accessible, efficient and fast GEE wor...

Results of a physically-based methodology to delineate morphometrical-morphostructural subdivision of the Western Carpathian region (Central Europe) from DEMs and their derivatives are presented. Previous suitability evaluation of an object-oriented methodology showed its potential in recognition of morphostructural features. In this study we moved...

Results of a physically-based methodology to delineate morphometrical-morphostructural subdivision of the Western Carpathian region (Central Europe) from DEMs and their derivatives are presented. Previous suitability evaluation of an object-oriented methodology showed its potential in recognition of morphostructural features. In this study we moved...

Incorporation of a physically-based general geomorphological theory directly into the segmentation algorithm is fundamental to physically-based land surface segmentation. Topographical steady state for morphostructural segmentations with five types of elementary forms defined by the principle of equilibrium provides a basis for definition of input...

Incorporation of a physically-based general geomorphological theory directly into the segmentation algorithm is fundamental to physically-based land surface segmentation. Topographical steady state for morphostructural segmentations with five types of elementary forms defined by the principle of equilibrium provides a basis for definition of input...

The current paper explores the suitability of geomorphons for the automatic extraction of drumlins. To calibrate the geomorphons to the size of drumlins, it is necessary to optimally define the maximum scale of mapping, i.e., the lookup distance parameter (L). Therefore, based on the concept of topographic grain, we introduce a new automated approa...

The intensive use of geophysics as a tool for archaeological science demands new ways of fast and conclusive data interpretation. With the increasing size and complexity of geomagnetic data, manual delineation and classification of magnetic anomalies can be a large time consuming process. In this respect, our study introduces a new approach to auto...

Hummocky landforms are often observed on the surface of debris avalanche deposits induced by catastrophic rockslide or sector collapse of volcanic mountains, and the quantitative assessment of the size and shape of hummocks is crucial for estimating the magnitude, kinematics, and runout distance of such sector collapse. However, extraction of hummo...

An assessment of the suitability of object-based image analysis to automatically delineate morphostructural subdivisions of the Western Carpathians is presented. Segmentation of three geomorphometric layers (elevation, slope gradient and vertical dissection) enabled us to delineate relatively homogeneous regions that represent the main active morph...

Soil information covering regional, continental, or even global scales is needed for modelling, prediction, or estimation of environmental risks, crop yield estimation, carbon stock estimation, or research on climate change. This study aims to evaluate the extent to which geographic object-based image analysis and expert-knowledge, using digital ma...

A random forest (RF) classifier is an ensemble classifier that produces multiple decision trees, using a randomly selected subset of training samples and variables. This classifier has become popular within the remote sensing community due to the accuracy of its classifications. The overall objective of this work was to review the utilization of RF...

The strength of a population resides in the resilience of its individuals and is closely related to the stability of its habitat. Stream macroinvertebrates are sensitive to environmental changes concerning habitat stability, thus they require shelter to prevent drift during severe floods. We propose a novel approach to estimate the impact of flash-...

Over the last decades, landscape metrics have been increasingly used to describe and analyse landscape structure. This article highlights some limitations of standard landscape structure analysis approaches and examines four major developments in this field: ways of integrating the height dimension of surface and vegetation into landscape metrics,...

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which c...

Preliminary results of an object-based methodology for delineation of the morphostructural division of the Western Carpathians region are presented. Normalized slope gradient and vertical dissection were used as input layers. Automated object extraction was carried out using a multi-resolution segmentation algorithm implemented in the eCognition® D...

During the recent years landform classification and mapping has been one of the most active areas of geomorphometry. However, there is still a lack of studies approaching the problematic of classifying repeating patterns of landform types by analyzing digital elevation models (DEMs). Therefore, our interest in such methods stems from the need to re...

Automated procedures are developed to alleviate long tails in frequency distributions of morphometric variables. They minimize the skewness of slope gradient frequency distributions, and modify the kurtosis of profile and plan curvature distributions towards that of the Gaussian (normal) model. Box-Cox (for slope) and arctangent (for curvature) tra...

Although multiresolution segmentation (MRS) is a powerful technique for dealing with very high resolution imagery, some of the image objects that it generates do not match the geometries of the target objects, which reduces the classification accuracy. MRS can, however, be guided to produce results that approach the desired object geometry using ei...

We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and...

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedur...

The stone crayfish, Austropotamobius torrentium, is one of the oldest freshwater crayfish species in Europe. Most Carpathian populations are in Romania, with a distribution clustered in 2 compact metapopulations in the western part of the country. Our goal was to understand if this pattern is the result of a coincidence or a complex set of restrict...

Current sampling methods require a large number of samples to account for spatial variation of environmental covariates, which often conflicts the available financial resources. Thus, efficient sampling strategies are desirable. The aim of this study was to evaluate the potential of land-surface segmentation in stratifying a landscape into homogene...

In this paper, we introduce an algorithm to delineate elementary forms on Digital Elevation Models (DEMs). Elementary forms are defined by constant values of fundamental morphometric properties and limited by discontinuities of these properties. A multiresolution segmentation technique was customized to partition the layers of altitude derivatives...

Geomorphological mapping is an important tool in geomorphology and related disciplines, yet it depends on the expertise and experience of the practitioner. The reliability of the technique and its products has not been subject to sufficient quantitative evaluation. In this study, we evaluated the magnitudes of differences in mapping glacial cirques...

Landform mapping is more important than ever before, yet the automatic recognition of specific landforms remains difficult. Object-based image analysis (OBIA) steps out as one of the most promising techniques for tackling this issue. Using the OBIA approach, in this study, a multiscale mapping workflow is developed and applied to two different inpu...

Until recently, landforms such as drumlins have only been manually delineated due to the difficulty in integrating contextual and semantic landform information in per cell classification approaches. Therefore, in most cases the results of per cell classifications presented basic landform elements or broad-scale physiographic regions that were only...

Digital classification of the Earth's surface has significantly benefited from the availability of global DEMs and recent advances in image processing techniques. Such an innovative approach is object-based analysis, which integrates multi-scale segmentation and rule-based classification. Since the classification is based on spatially configured ob...

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-drive...

In this paper we report the results of an experiment with automated landform delineation and classification from digital elevation models (DEMs) using object-based image analysis (OBIA). Archaeologists rely on accurate and detailed geomorphological maps to predict and interpret the location of archaeological sites. However, they have been using hig...

ZIP file containing the Google maps of the most important areas described in this article.

In most landform classification studies – either per cell or object-based – the authors have ignored modeling the semantics of landforms explicitly. Thus, landform classification schemes rely on individual knowledge, and are too much tailored to specific areas and/or scales. Integration of structured knowledge models in the classification process h...

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, fo...

In the last decade landform classification and mapping has developed as one of the most active areas of geomorphometry. However, translation from continuous models of elevation and its derivatives (slope, aspect, and curvatures) to landform divisions (landforms and landform elements) is filtered by two important concepts: scale and object ontology....

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-drive...

Relating spatial patterns to ecological processes is one of the central goals of landscape ecology. The patch-corridor-matrix model and landscape metrics have been the predominant approach to describe the spatial arrangement of discrete elements ("patches") for the last two decades. However, the widely used approach of using landscape metrics for c...

The spatial resolution of imaging sensors has increased dramatically in recent years, and so too have the challenges associated with extracting meaningful information from their data products. Object-based image analysis (OBIA) is gaining rapid popularity in remote sensing science as a means of bridging very high spatial resolution (VHSR) imagery a...

Very high resolution (VHR) DEMs such as obtained from LiDAR (Light Detection And Ranging) often present too much detail for various applications. Finding the right spatial scale for analysis is a challenging task, especially in landscape ecology. It still seems to be unsettled, whether scales in digital representations of the land surface are expli...

This paper presents a procedure to optimize parametrization and scale for terrain-based environmental modeling. The workflow was exemplified on crop yield data, which is assumed to represent a proxy for soil productivity. Focal mean statistics were used to generate different scale levels of terrain derivatives by increasing the neighborhood size in...

Digital Elevation Models (DEMs) and their derived terrain attributes are commonly used in soil-landscape modeling. Process-based terrain attributes meaningful to the soil properties of interest are sought to be produced through digital terrain analysis. Typically, the standard 3 X 3 window-based algorithms are used for this purpose, thus tying the...

The main objective of this chapter is to segment and classify Shuttle Radar Topography Mission (SRTM) data into specific landforms. Based on the results of previous research (DRĂGUŢ and Blaschke 2006), a classification system of landform elements was improved and adapted for SRTM 3 arc second data. Terrain derivatives such as elevation, slope gradi...