DEM Generation based on UAV Photogrammetry Data in Critical Areas

Giulia Sammartano and Antonia Spanò

(DAD) Department of Architecture and Design, Politecnico di Torino, Torino, Italy

Keywords: UAV Photogrammetry, DEM, DSM, GIS, Filtering, Landscape Heritage.

Abstract: Many Geomatics technologies based on the use of terrestrial and aerial sensor offer a significant support and

new potentialities in term of quickness, multi-scale precision, cost-cutting, and in short, sustainability. The

3D data and mapping products, above all the large-scale ones derived from aerial acquisitions (e.g. Unmanned

Aerial Vehicles, UAV) can be gradually adopted even when the context is not enough accessible or standard

airborne data does not fulfill the requested resolution and accuracy.

Starting from the availability of large scale UAV data, the paper is mostly purposed to examine the use of

tools aimed to generate DEM (Digital elevation model) from DSM (digital surface model) obtained from

UAV flights. In literatures many application concern the point cloud data generation from aerial

photogrammetry or airborne laser scanner. Several different filtering approaches and algorithms (filtering

point along density, direction, slope) are used to derive bare-Earth, but in the test case, the high level of detail

of objects, together with the complexity of high slope of ground impose some adaptation.

The test is included in a decision-making processes concerning the promotion of Alpine landscape leaded

through a project of sustainable mobility. Therefore the DEM generation is used to foresee a possible and

sustainable path of the railway rack, achieved by a simple multi-criteria analysis performed by Geographic

Information Systems (GIS) tools. In the end an important aspect of the test is the use of open source GIS tools

employed in the experience.

1 INTRODUCTION

Nowadays the documentation technologies based of

advanced Geomatics tools offer a significant support

in maps updating, in term of quickness, precision,

cost-cutting, and in short, sustainability.

The use of Unmanned Aerial Vehicles (UAV)

offers almost new potentialities with high detail

value, and related applications truly become

progressively affordable, even where the context is

not enough accessible for traditional terrestrial survey

techniques. (Aicardi et al., 2014)

A project of sustainable mobility in mountain

framework (a rack railway) have been analysed and

improved through the setting up of an integrated project

of 3D landscape documentation and modelling. This has

been achieved using aerial photogrammetry by drone and

3D data treatment and spatial analysis in GIS. In

landscape documentation, the use of UAV and integrated

sensors, together with the application of more traditional

Lidar terrestrial and aerial techniques, perform very

interesting results in the context of large-scale mapping

and in terms and effectiveness.

In case of complex documentation applied at

specific valuable zones of the built and natural

heritage, that are located often in arduous areas very

scarcely accessible, the previous issues lead us to

choose specific survey tools able to reach great detail

and at the same time, a relatively large area of

coverage. (Boccardo et al., 2015).

2 DEM FROM UAV

The UAV approach can be useful to produce spatial-

temporal high-resolution models, in competitive period

and resources, that providing useful 3D data for many GIS

monitoring applications, as georeferenced information at

large-scale derived from orthoimages and DSM (Yastıklı

et al., 2013).

The main application of UAV survey producing

spatial data for GIS modelling and analysis are the

territorial, geological, urbanistic, agricultural and forestry

ones (Perko et al., 2015; Höfle et al., 2013; Susaki, 2012;

Grenzdörffer et al., 2008). Even in the architectural and

archaeological contexts the use of UAV become

increasingly important and common, adding to essential

to achieve accurate metric documentation, integrate

Sammartano, G. and Spanò, A.

DEM Generation based on UAV Photogrammetry Data in Critical Areas.

In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2016), pages 92-98

ISBN: 978-989-758-188-5

different source geospatial data, as well as categorize and

store spatial-temporal information. (Themistocleous et al.,

2015

; Rinaudo et al., 2012)

For investigation purposes about land forms the

use of UAV acquisitions enables to obtain high

detailed morphological data of the area, that can be

processed in order to generate a DSM, comparable to

the Lidar ones; with these results we can proceed in

many cases to update effectively traditional

cartography and numerical data. However, the 3D

information regarding the earth surface need to be

processed for the derivation of a useful DEM, without

the interference caused by vegetation cover and

buildings. In literatures many application in these

direction concern point cloud data from aerial

photogrammetry or airborne laser scanning and

different filtering approaches and algorithms.

(Hosseini et al., 2014; Korzeniowska et al., 2011,

Chen et al., 2007; Masaharua et.al., 2002).

In many cases, the bare-Earth extraction can be

obtained with algorithms of point clouds classification

and segmentation, by filtering point along density,

direction, slope, etc. (Pfeifer, 2008)

This takes moderately a large amount of time of

human action in modelling systematic errors, filtering,

feature extraction and thinning, up to 60%-80% of the

processing time (Sithole, 2004).

This becomes more complex in the case of areas

where the ground is not flat and common algorithm of

analysis in high density urban, peri-urban or forestry areas

(Perko, 2015. Susaki, 2012, Korzeniowska, 2011), that

recognize objects according to their variation of high and

density from ground, as an almost plane level do not work

effectively. In past year, some procedures have been

developed for slope land applications (Ismail, 2015.

Hosseini, 2014), and adaptive algorithms where the

threshold varies with respect to the slope of the terrain

have been implemented (from the proposed one by

Sithole, 2001).

3 THE EXPERIENCE ON ALPINE

SLOPES

The overall experience of high scale mapping of the

hamlets in the Castelmagno area (Piedmont, Italy)

had numerous purposes, combining terrestrial

scanning and low aerial acquisition with the aim to

achieve multi-scale models. It’s not objective of this

paper the description of used instruments and

techniques, since we are going to evaluate the use and

processing of DSM derived from the UAV flights.

The DSM and orthophoto generation have been

accomplished by Structure from Motion (SfM)

combining photogrammetry and computer vision

methods. In spite of the availability of two flights, the

first one from an hexacopter flying at the height of

about 70 m. and a second by a fix wing Ebee drone

flying at the height of 120m, we are going to consider

only the second source. The next results are the

starting point of the present work. Covered area: 2.43

ground resolution: 0.11 m/pix, camera stations: 544,

Tie-points: 1044668 GCPs residual: 2.5 pixel, CPs

residual: 3 pixel

3.1 The Need of Large Scale Map

Updating

The placement of a railway rack as a tool of local

development has been designed to provide a large

fruition, satisfying a tourist need and a private use.

The feasibility study expects that a path

connecting three hamlets could promise a process of

repopulation of the area in order to re-establish the

main economic activity as desired.

So the railway rack has to cross in a transverse

direction the hydro-geological basin of Valliera,

which is a tributary of the Grana River. The departure

station is designed to be placed in the Colletto village

(1277 m above sea level), the path has to descend fast

toward Croce (1179 m a.s.l) crossing the riverbed and

climb the slope to Campofei (1542 m a.s.l.)

Figure 1: UAV orthophoto of the test area; the arrows show

three villages to be connected by the railway rack.

First of all, the challenge to foresee a possible and

sustainable path of the railway rack, need a very

detailed DTM (Digital terrain Model), more accurate

than the regional 1:10000 scale DTM. Next

paragraphs are devoted to describe a DTM generation

from UAV DSM, using open source techniques. Then

a best routing search is presented in the last

paragraph.

DEM Generation based on UAV Photogrammetry Data in Critical Areas

3.2 DSM to DEM Conversion

The aim of the first step of the test is the use of UAV data

to obtain a morphological model of the project area,

starting from the DSM, analysing and eliminating objects

surfaces, and finally generating a DEM. The difficulties

are attributed to the complex mountain context in with a

forestry covering very diffuse was in many zones very

thick. Furthermore, the steep gradient of the mountain

slope added a robust bond to the raster analysis based on

simple available algorithms distance range based.

Figure 2: The DSM of the test area, compared with the

orthoimage from the drone flight: it is distinct the assorted

presence of vegetation cover in a very slope terrain.

3.2.1 Managing UAV Data in DSM

Filtering: Different Approaches

The operational approach to derive a DEM from the

DSM calculated from the UAV images was based on

processing raster data by filtering algorithms.

The test was planned on the Open-Source platform

QGIS (QGIS 2.10 Pisa, http://www.qgis.org/en).

The software offers many simplified and advanced

processing tools, also with algorithms extension from

GRASS Gis and SAGA Gis. In the test both of them

have been used to setting up the DSM analysis.

The two raster approach proposed started from a

base-objective, that is to recognise and eliminate non-

coherent objects like buildings and wooden covering on

the soil. It can be achieved with direct application of

Raster filters, but not easily suitable because of the slope

or, indirectly operating a multiple-step workflow of

raster calculation and modelling (Cimmery, 2010)

DTM Filter Slope-based on SAGA GIS, allows

recognizing object according to input data of search radius

and terrain approx. slope. After several attempts, the best

combination of values for the area have been: terrain

slope: 30%. Search radius: 20. The output is a double

divided raster data, with detection of Bare Earth (figure

3). This result is not enough appreciate, despite high input

values, because of the internal area of removed object

profiles that are still tree and building mass.

Morphological Filter on SAGA GIS, manages to

smooth the raster DSM according to a search mode

(circle or square) and according to 4 algorithms

(dilation, erosion, closing, opening). The best fitting

algorithm to model the area have been the erosion

filter on circle mode with radius 50.

Gaussian Filter on SAGA GIS allows a filtering of

the raster data according to the Gaussian histogram,

imputing the Standard deviation.

Figure 3: Example of Removed objects and Bare-Earth, the

output from a DTM filter slope-based.

Figure 4: (Left) One of morphological filter outputs applied

in test area with erosion 50 rad in circle searching mode

(right) Gaussian filter STDEV 20, radius 70.

3.2.2 Helpful Approach for DEM

Conversion

The proposed workflow tries to integrate some

procedures of raster management in order to identify

and remove trees and building, understood as

discontinuity in the trend of mountainous terrain

sloping. In this sense the Ruggedness Index have been

applied to the threshold suitable to maximize the

finding of objects on the area. Then a buffer area from

3 to 5 meters have been identified, that tries to include

all the items to be deleted from the model.

Afterwards a cutting mask have been created to

remove from the DSM incongruous elements. After

this step, the following actions have been directed to

fill hole after the cut and compare and assess the result

of final DEM with the original DSM. (Fig.10). Even

if some few residuals of final DEM points close to

trees and buildings are still high, we can consider the

valuable result of the surface interpolation and objects

removing, taking into account the critical situation of

the soil morphology.

GISTAM 2016 - 2nd International Conference on Geographical Information Systems Theory, Applications and Management

Figure 5: Applying the Terrain Ruggedness Index

algorithm to de DSM: best-input value 0.05.

Reclassification of the raster with binary values (0-1) to

perform buffer analysis on a unique value.

Figure 6: (Left) Creating a buffer area around objects by

using the Proximity (Raster Distance) analysis tool. (Right)

Identification of trees and buildings and vectorialization of

raster in shape file layer.

Figure 7: Recognized objects after raster cut on the DSM.

Figure 8: The closing gaps filters on SAGA GIS according

to tension threshold 0.1.

Figure 9: Comparison between the DSM generated from

UAV image processing and the final DEM obtained from

GIS raster analysis and filtering.

Figure 10: Residuals of DSM/DEM from GCP. The

elaborated DEM, differs from DSM mainly on rich

vegetation and built-up areas.

Figure 11: DEM residuals of on each GCP measured by GPS

survey, clustered by their position in the area. Higher residuals

between DEM and GCP are near buildings and vegetation.

3.3 Path Hypothesis

3.3.1 First Shortest Path Proposal

Based on an edited and evaluated DEM, the first aim

of the has been the assessment of suitability of the

shortest distance route, that correspond in a first

approximation to the cheapest.

DEM Generation based on UAV Photogrammetry Data in Critical Areas

Figure 12: Slope map in red range color with firstly designed

route of railway rack. (green). (right) Comparison of elevation

differences (black) and slope values (green) of the straight path

connecting the villages.

Safety first this straight path hypothesis has been

compared with the regional map of landslide risk.

Fortunately, the presence of a ridge submit to risk a

face immediately next to slope of designed path, in

the west direction.

The slope map generation, derived from the

available high scale and accurate DEM, has brighten

the presence of very precipitous slopes, in fact very

often the hamlets have a medioeval or XVI- XVIIth

foundation, so they are grasped to stone walls that are

typical of the geo-morphological characterisation of

the Valle Grana.

3.3.2 A Simple Multicriteria Analysis to

Search a More Suitable Path

The abilities offered by the continuously expanding GIS

technology and by the increasing availability of digital

georeferenced data have been highly develop the use of

multi-criteria spatial analysis to support land planning.

(Botequilha-Leitão, Ahern, 2002).

Close to the riverbed, the slope reach to 43% and even

worse many railway rack system are not able to divert the

slope.

Indeed some innovative systems in use in alpine

environment are able to reach very high slopes, even

40%. (Regis, 2015). The graph of figure 12, show the

terrain profile highlighting the level differences

among villages, contemporary with the slope values

that reaches 43% close to the river.

Moreover, the GIS-Multi-criteria Decision

Analysis is largely used to support best location

analyses in very many fields of application. In this

paper, we are going to use an example of a so called

weighted overlay performed by raster grids, with the

purpose of providing a test for the achieved UAV

DEM.

Surely, the stronger constrain for searching a

sustainable and best route is the slope, and we know

that ordinary types of railway rack systems are able

to face slopes around 20%, but some innovative types

provide equipment with a successful power facing

slopes higher than 40%. This last type will be taken

into account for the best route assessment.

The slope raster map has been reclassified

imposing four class of slope: from 0% to 20, from

21% to 35% , from 35% to 40%, and more than 40%.

(fig. 13). The last class will be considered highly

adverse.

The shortest route cross the valley using almost

the steepest path, and the change of slope direction

close to the riverbed is particularly difficult. Another

considered parameter is the inclination the railway

rack route chasing contours direction; the DEM grid

has been reclassified in four classes, selecting the

breaks value in order to obtain an area near the river

to be excluded, or considered as highly adverse area.

Figure 13: a. four classes of slopes grid map. b. five classes of elevation interval c. Parcel whose owner participate to the railway rack

project.

GISTAM 2016 - 2nd International Conference on Geographical Information Systems Theory, Applications and Management

(Orange in fig. 13b). The last parameter involved in

the process are parcels whose owner has agreed and

participated to the projects or not.

In the weighted overlay analysis, the three maps

have been different level of influence. The slope

classes had been an influence of 70%, the grid map

connected with contours had a 20% influence, and the

last one has been considered with low influence

(since the administrative institution could give some

benefits for the project acceptance).

The final result of weighted overlay is shown in

figure 14, where green pixels show a highly suitable

area to accommodate the railway rack, the dark

yellow area are on average suitable, and the last class,

in red pixel correspond to unfavorable area for the

railway rack.

In Figure 14 the shortest and steepest path (red)

has been compared with a manually traced route

(green), avoiding unfavorable areas.

Figure 14: The grid maps visualize by different color the different

suitability of areas to host the railway rack passage.

4 CONCLUSIONS

The increasingly studies as well as diversified

applications of UAV photogrammetry survey make

consider it a very suitable method for high scale quick

and low cost mapping. Many processing techniques

and platforms can manage today DSM derived from

UAV processed images; and we are witnessing to a

strong effort in order to adapt strengthened tools

manage this kind of data in critical areas.

This paper is aimed to prove that the use open

source tools to achieve the analyses and can be a

significant step toward that knowledge circulation

and sharing about geospatial data overall. Surely,

some more enhancements need to be implemented in

terms of big objects filtering tools. Some uses

promise to offer further developments, especially in

benefit that the GIS-based landscape modeling can

offer to the analysis and decision-making phases in

the ever more topical background of land use

planning and heritage.

ACKNOWLEDGEMENTS

The UAV flights have been performed by the DiRecT

Team (Disaster Recovery Team), involving Aicardi, I..

Chiabrando, F. Donadio, E. Lingua, A. Maschio, P.

Noardo, G. Sammartano, F. Spanò.

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GISTAM 2016 - 2nd International Conference on Geographical Information Systems Theory, Applications and Management