GIS-based Landform Classification of Eneoli thic Archaeological Sites in the Plateau-plain Transition Zone (NE Romania): Habitation Practices vs. Flood Hazard Perception

The landforms of the Earth’s surface ranging from large-scale features to local topography are factors that influence human behavior in terms of habitation practices. The ability to extract geomorphological settings using geoinformatic techniques is an important aspect of any environmental analysis and archaeological landscape approach. Morphological data derived from DEMs with high accuracies (e.g., LiDAR data), can provide valuable information related to landscape modelling and landform classification processes. This study applies the first landform classification and flood hazard vulnerability of 730 Eneolithic (ca. 5000–3500 BCE) settlement locations within the plateau-plain transition zone of NE Romania. The classification was done using the SD (standard deviation) of TPI (Topographic Position Index) for the mean elevation (DEV) around each archaeological site, and HEC-RAS flood hazard pattern generated for 0.1% (1000 year) discharge insurance. The results indicate that prehistoric communities preferred to place their settlements for defensive purposes on hilltops, or in the close proximity of a steep slope. Based on flood hazard pattern, 8.2% out of the total sites had been placed in highly vulnerable areas. The results indicate an eco-cultural niche connected with habitation practices and flood hazard perception during the Eneolithic period in the plateau-plain transition zone of NE Romania and contribute to archaeological predictive modelling.

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Landform classification using GIS techniques. The case of Kimi municipality area, Euboea Island, Greece.

Bulletin of the Geological Society of Greece ◽

10.12681/bgsg.10940 ◽

2016 ◽

Vol 47 (1) ◽

pp. 264 ◽

Cited By ~ 1

Author(s):

I. Ilia ◽

D. Rozos ◽

I. Koumantakis

Keyword(s):

Spatial Analysis ◽

Power Index ◽

Stream Power ◽

Topographic Wetness Index ◽

Wetness Index ◽

Topographic Position Index ◽

Landform Classification ◽

Essential Parameter ◽

Position Index ◽

Stream Power Index

The main objective of this paper is to classify landforms in Kimi municipality area of Euboea Island, Greece using advanced spatial techniques. Landform categories were determined by conducting morphometric analysis through the use of advanced GIS functions. In particular, the process of classifying the landscape into landform categories was based on Topographic Position Index (TPI). The main topographic elements such as slope inclination, aspect, slope shape (curvature), topographic wetness index and stream power index were obtained from the DEM file of the study area. Landform classification was obtained using TPI grids and the classes were related with the geological pattern and the land cover by sophisticated spatial analysis function. The knowledge obtained from the present study could be useful in identifying areas prone to land degradation and instability problems in which landforms are identified as an essential parameter

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Satellite–Derived Topography and Morphometry for VHR Coastal Habitat Mapping: The Pleiades–1 Tri–Stereo Enhancement

Remote Sensing ◽

10.3390/rs14010219 ◽

2022 ◽

Vol 14 (1) ◽

pp. 219

Author(s):

Dorothée James ◽

Antoine Collin ◽

Antoine Mury ◽

Rongjun Qin

Keyword(s):

Control Point ◽

Habitat Mapping ◽

Slope Aspect ◽

Coastal Habitat ◽

Topographic Position Index ◽

Landform Classification ◽

Surface Models ◽

Position Index ◽

The Impact

The evolution of the coastal fringe is closely linked to the impact of climate change, specifically increases in sea level and storm intensity. The anthropic pressure that is inflicted on these fragile environments strengthens the risk. Therefore, numerous research projects look into the possibility of monitoring and understanding the coastal environment in order to better identify its dynamics and adaptation to the major changes that are currently taking place in the landscape. This new study aims to improve the habitat mapping/classification at Very High Resolution (VHR) using Pleiades–1–derived topography, its morphometric by–products, and Pleiades–1–derived imageries. A tri–stereo dataset was acquired and processed by image pairing to obtain nine digital surface models (DSM) that were 0.50 m pixel size using the free software RSP (RPC Stereo Processor) and that were calibrated and validated with the 2018–LiDAR dataset that was available for the study area: the Emerald Coast in Brittany (France). Four morphometric predictors that were derived from the best of the nine generated DSMs were calculated via a freely available software (SAGA GIS): slope, aspect, topographic position index (TPI), and TPI–based landform classification (TPILC). A maximum likelihood classification of the area was calculated using nine classes: the salt marsh, dune, rock, urban, field, forest, beach, road, and seawater classes. With an RMSE of 4 m, the DSM#2–3_1 (from images #2 and #3 with one ground control point) outperformed the other DSMs. The classification results that were computed from the DSM#2–3_1 demonstrate the importance of the contribution of the morphometric predictors that were added to the reference Red–Green–Blue (RGB, 76.37% in overall accuracy, OA). The best combination of TPILC that was added to the RGB + DSM provided a gain of 13% in the OA, reaching 89.37%. These findings will help scientists and managers who are tasked with coastal risks at VHR.

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Towards risk-based flood management in highly productive paddy rice cultivation – concept development and application to the Mekong Delta

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2859-2018 ◽

2018 ◽

Vol 18 (11) ◽

pp. 2859-2876 ◽

Cited By ~ 4

Author(s):

Nguyen Van Khanh Triet ◽

Nguyen Viet Dung ◽

Bruno Merz ◽

Heiko Apel

Keyword(s):

Land Use ◽

Flood Risk ◽

Large Scale ◽

Flood Hazard ◽

Mekong Delta ◽

Flood Management ◽

Paddy Rice ◽

Rice Cultivation ◽

Spatially Explicit ◽

Risk Maps

Abstract. Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost–benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.

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Estimating extreme river discharges in Europe through a Bayesian Network

10.5194/hess-2016-250 ◽

2016 ◽

Author(s):

Dominik Paprotny ◽

Oswaldo Morales Nápoles

Keyword(s):

Large Scale ◽

Graphical Model ◽

Flood Hazard ◽

Physical Models ◽

Method Performance ◽

Discharge Data ◽

Dependency Structure ◽

Spatial Coverage ◽

Geographical Characteristics ◽

Better Than

Abstract. Large-scale hydrological modelling of flood hazard requires adequate extreme discharge data. Models based on physics are applied alongside those utilizing only statistical analysis. The former requires enormous computation power, while the latter are most limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian Networks (BN), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables describing the geographical characteristics of their catchments. Data on annual maxima of daily discharges from more than 1800 river gauge stations were collected, together with information on terrain, land use and climate of catchments that drain to those locations. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe, and better than a comparable global statistical method. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and is not affected by a split-sample validation. The BN was applied to a large domain covering all sizes of rivers in the continent, both for present and future climate, showing large variation in influence of climate change on river discharges, as well as large differences between emission scenarios. The method could be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

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Comparative Cladistics: Fossils, Morphological Data Partitions and Lost Branches in the Fossil Tree of Life

10.31237/osf.io/7sa6d ◽

2017 ◽

Author(s):

Ross Mounce

Keyword(s):

Large Scale ◽

Phylogenetic Signal ◽

Scientific Progress ◽

Molecular Data ◽

Morphological Data ◽

Data Sets ◽

Phylogenetic Groups ◽

Use Of Data ◽

Wide Range ◽

Cladistic Analyses

In this thesis I attempt to gather together a wide range of cladistic analyses of fossil and extant taxa representing a diverse array of phylogenetic groups. I use this data to quantitatively compare the effect of fossil taxa relative to extant taxa in terms of support for relationships, number of most parsimonious trees (MPTs) and leaf stability. In line with previous studies I find that the effects of fossil taxa are seldom different to extant taxa – although I highlight some interesting exceptions. I also use this data to compare the phylogenetic signal within vertebrate morphological data sets, by choosing to compare cranial data to postcranial data. Comparisons between molecular data and morphological data have been previously well explored, as have signals between different molecular loci. But comparative signal within morphological data sets is much less commonly characterized and certainly not across a wide array of clades. With this analysis I show that there are many studies in which the evidence provided by cranial data appears to be be significantly incongruent with the postcranial data – more than one would expect to see just by the effect of chance and noise alone. I devise and implement a modification to a rarely used measure of homoplasy that will hopefully encourage its wider usage. Previously it had some undesirable bias associated with the distribution of missing data in a dataset, but my modification controls for this. I also take an in-depth and extensive review of the ILD test, noting it is often misused or reported poorly, even in recent studies. Finally, in attempting to collect data and metadata on a large scale, I uncovered inefficiencies in the research publication system that obstruct re-use of data and scientific progress. I highlight the importance of replication and reproducibility – even simple reanalysis of high profile papers can turn up some very different results. Data is highly valuable and thus it must be retained and made available for further re-use to maximize the overall return on research investment.

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Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

10.5194/hess-2016-620 ◽

2017 ◽

Cited By ~ 1

Author(s):

Cherry May R. Mateo ◽

Dai Yamazaki ◽

Hyungjun Kim ◽

Adisorn Champathong ◽

Jai Vaze ◽

...

Keyword(s):

Spatial Resolution ◽

Large Scale ◽

Flood Hazard ◽

Regional Scale ◽

Global Scale ◽

Test Case ◽

Efficiency Coefficient ◽

Computational Power ◽

Extreme Flood ◽

Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-3-4967-2015 ◽

2015 ◽

Vol 3 (8) ◽

pp. 4967-5013 ◽

Cited By ~ 1

Author(s):

H. Apel ◽

O. M. Trepat ◽

N. N. Hung ◽

D. T. Chinh ◽

B. Merz ◽

...

Keyword(s):

Hydrodynamic Model ◽

Urban Areas ◽

Large Scale ◽

Method Development ◽

Flood Hazard ◽

Hazard Analysis ◽

Mekong Delta ◽

Rain Gauge ◽

Convective Precipitation ◽

Can Tho City

Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

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