Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010,
SRTM and Topodata Digital Elevation Models
Zuleide Alves Ferreira
1,2 a
and Pedro Cabral
1b
1
NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide,
1070-312 Lisbon, Portugal
2
Instituto Federal de Educação, Ciência e Tecnologia do Tocantins, Campus Palmas, Brazil
Keywords: DEM, Evaluation, Precision, Altitude, Brazilian Cartographic Accuracy Standard.
Abstract: Three-dimensional data of the Earth's surface can support several types of studies, such as hydrological,
geomorphological, environmental monitoring, among many others. But, due to the difficulty of acquiring
these data in the field, freely available Digital Elevation Models (DEM) have been widely used, and therefore,
it is increasingly necessary to check their accuracy to ensure their correct applicability according to the
appropriate scale. However, there are no studies which have assessed specifically the vertical accuracy of the
ALOS PALSAR, GMTED2010, SRTM and Topodata DEMs according to Brazilian Cartographic Accuracy
Standard (PEC). In this sense, this paper aims to evaluate the quality of the above-mentioned DEMs by using
the official high accuracy altimetric network data of the Brazilian Geodetic System. Statistical analysis of
errors results demonstrated that the DEMs have applications compatible with 1:100,000 scales or smaller than
this, and although the GMTED2010 presented a lower accuracy than the other DEMs, it also could be
classified in the same accuracy category according to the Brazilian PEC. We conclude that DEMs assessment
is very important to ensure their correct application as they can be used in many researches since these data
are available for practically all areas of the planet.
1 INTRODUCTION
Digital Elevation Model (DEM) is a generic term that
comprises both the Digital Terrain Model (DTM),
which represents the ground surface, and the Digital
Surface Model (DSM), which represents the upper
surface above the ground level, including trees,
buildings and other natural or artificial objects
(Polidori and El Hage, 2020). DEM consists of the
terrestrial surface representation supposedly free of
vegetation, buildings and other non-ground objects,
despite this term is often used in a generic way to refer
to DSM and DTM (Liu et al., 2015).
In the last years, several DEMs elaborated using
various techniques have been made freely available to
the community, thereby for better use of these
products, it is important to analyse their accuracy
aiming to identify their possible applications (Moura
et al., 2014). The assessment of DEMs quality is a
subject that requires further attention, and despite the
a
https://orcid.org/0000-0001-5283-5200
b
https://orcid.org/0000-0001-8622-6008
importance of DEMs applications in several fields,
there are no specific standardized guidelines
concerning their accuracy assessment, which
represents a challenge for this kind of geospatial
technology users (Mesa-Mingorance and Ariza-
López, 2020).
DEMs quality has been studied frequently to
assess their wide range of applications and most of
these studies consist of comparing the obtained data
from DEMs and a set of reference data generally
called control points (Polidori et al., 2014).
According to these authors, this comparison, that is
based on accuracy statistical indicators such as mean
difference, standard deviation or root mean square
error, is very important to evaluate the DEM
positional accuracy and contributes to improving the
mapping methods. Moreover, to ensure the reliability
of the data extracted from a DEM, it is necessary to
have very clear information about its coordinate
system, its cartographic projection and its datum, as
116
Ferreira, Z. and Cabral, P.
Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010, SRTM and Topodata Digital Elevation Models.
DOI: 10.5220/0010404001160124
In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2021), pages 116-124
ISBN: 978-989-758-503-6
Copyright
c
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
well it is necessary to consider that horizontal
positional accuracy errors can result in relevant
vertical errors in the DEM, mainly in areas of steep
slopes (Yap et al., 2019).
In Brazil, the quality of the cartographic products
is regulated by the Decree n° 89,817 published in the
year 1984, that establishes regulatory instructions for
the technical standards of national cartography.
Conforming to this decree, the cartographic products
must be classified observing the Cartographic
Accuracy Standard (Padrão de Exatidão Cartográfica
- PEC), which is a dispersion statistical indicator
relative to 90% probability and corresponds to 1.6449
times the Root Mean Square Error (RMSE). Thus,
90% of the collected points errors in the cartographic
product must present values equal to or less than those
predicted in the PEC when compared to its
coordinates surveyed in the field by a high accuracy
method (Brazil, 1984; 2016).
Many studies addressed DEMs accuracy
assessment (Hu et al., 2017; Jain et al., 2018;
Mouratidis and Ampatzidis, 2019; Varga and Bašić,
2015; Wessel et al., 2018); however, there are no
studies which assessed specifically the vertical
accuracy of the ALOS PALSAR, GMTED2010,
SRTM and Topodata DEMs according to Brazilian
Cartographic Accuracy Standard (PEC). In this sense,
this paper aims to evaluate the vertical quality of the
above-mentioned DEMs by using the official high
accuracy altimetric network data of the Brazilian
Geodetic System. Therefore, it is expected that the
obtained results from this comparison contribute to
the correct applicability of the analysed DEMs
according to an appropriate use scale in the country.
2 METHODOLOGY
2.1 Study Area
The Balsas River watershed is inserted in thirteen
municipalities and occupies an area of 12,352.5 km²,
that corresponds to about 4.5% of the total area of the
State of Tocantins (Figure 1) (Brazil, 2012). This
watershed altitudes are approximately between 200
and 800 meters considering the average sea level, that
represents more than 600 meters of altimetric
amplitude as can be seen in Figure 2. Inside Balsas
River watershed area were identified 105 stations of
the official Brazilian altimetric network which are
located along the main roads of the region (Figure 2).
Figure 1: Geographical location of the study area.
To evaluate the DEMs, we used the official high
accuracy altimetric network data of the Brazilian
Geodetic System available as orthometric altitudes.
Composed by altimetric geodesic stations implanted
along with the road network throughout the Brazilian
territory, this network was established in 1945 by
using the high accuracy geometric levelling method.
In order to ensure the integrity, consistency, and
reliability of the Geodetic Database information, level
references altitudes are recalculated periodically due
to the incorporation of new levelling lines and the
development of new data measurement and
processing techniques. According to these altimetric
data last quality assessment carried out in 2018,
87.5% of the adjusted geopotential values showed
standard deviations between 6 and 10 centimeters
(IBGE, 2019).
2.2 Data
The satellite observation program Advanced Land
Observing Satellite (ALOS) was created to support
mapping of land coverage, disaster monitoring, and
resource surveying (JAXA, 2020a). In 2006, ALOS
satellite was launched from the Tanegashima Space
Center with three sensors onboard: Panchromatic
Remote-sensing Instrument for Stereo Mapping
(PRISM), Advanced Visible and Near Infrared
Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010, SRTM and Topodata Digital Elevation Models
117
Figure 2: Hypsometric maps of Balsas River watershed elaborated from the DEMs: (a) ALOS PALSAR, (b) GMTED2010,
(c) SRTM and (d) Topodata.
Radiometer type 2 (AVNIR-2), and Phased Array
type L-band Synthetic Aperture Radar (PALSAR)
(JAXA, 2020a). The PRISM sensor is a panchromatic
radiometer with 2.5 meters spatial resolution at nadir
and is composed of a set of three optical systems
which produces stereoscopic images providing a high
accuracy digital surface model (JAXA 2020b).
AVNIR-2 sensor is a visible and near-infrared
radiometer aimed at mapping land use and coverage
that provides images with 10 meters spatial
resolution, and PALSAR is an active microwave
sensor capable of obtaining daytime and night-time
terrestrial observation without cloud interference
(JAXA, 2020b).
The PALSAR images acquired during the ALOS
mission were corrected geometrically and
radiometrically (Laurencelle et al., 2015). The
geometric distortions were first corrected with the use
of a DEM and, later, the radiometry adjustment was
executed in the affected foreshortening and layover
regions. After radiometric terrain correction, the
products were distributed using two resolutions.
Some products generated from high-resolution DEM
(NED13) were distributed with a 12.5 meters pixel
size, and others generated from mid resolution
DEMs (SRTM 30 m, NED1 and NED2) have a 30
meters pixel size (Laurencelle et al., 2015).
The Shuttle Radar Topography Mission (SRTM)
was executed onboard of the Space Shuttle
Endeavour during 10 days in February 2000 by using
two radar antennas to collect topographic data over
nearly 80 percent of Earth's land surface. The SRTM
international project was developed with the
partnership of the National Geospatial-Intelligence
Agency (NGA) and the National Aeronautics and
Space Administration (NASA) providing the first-
ever near-global data set of land elevations (NASA,
2020). In 2003, the SRTM data were made available
for many parts of the world with an accuracy of 3 arc-
seconds which corresponds to about 90 meters. But,
in 2014, all global SRTM data have been released
with the original measurements full resolution
equivalent to 1 arc-second, or 30 meters (NASA,
2020).
The Topodata project consists of a topographic
database elaborated through the refinement of the
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
118
SRTM data resolution from 3 arc seconds (90 meters)
to 1 arc second (30 meters) by kriging techniques
(Valeriano and Rossetti, 2012). This project was
developed to provide geomorphometric data from all
over the Brazilian territory due to the unavailability
of cartographic products in scales suitable for some
regions.
Released in 2008 and after being successively
inspected and revised, the Topodata project offers
local geomorphometric variables corresponding to
basic elements based on techniques of interpretation
and relief analysis. Thus, this project presents
variables such as slope, slope orientation, horizontal
curvature, vertical curvature and inputs for the design
of the drainage structure resulting in the generation of
an extensive database structured for free use by the
scientific community (Valeriano, 2008).
The Global Multi-resolution Terrain Elevation
Data 2010 (GMTED2010) is a digital terrain model
developed with the collaboration between the United
States Geological Survey (USGS) and the National
Geospatial-Intelligence Agency (NGA) providing
global coverage of all land areas from latitude 84°N
to 56°S for most products (Danielson and Gesch,
2011). This model is based on data derived from 11
raster elevation sources (Table 1) and it has been
generated at three different resolutions of
approximately 250, 500, and 1,000 meters, that equal
to 7.5, 15 and 30 arc-seconds, respectively (Danielson
and Gesch, 2011). Table 2 shows the original main
characteristics of each DEM evaluated in this paper.
Table 1: GMTED2010 - Input source data characteristics adapted from Danielson and Gesch (2011).
Dataset Resolution Horizontal unit
Horizontal
datum
SRTM DTED® 2 1 Arc-second WGS 84
DTED® 1 3 Arc-second WGS 84
CDED1 0.75 Arc-second NAD 83
CDED3 3 Arc-second NAD 83
15-arc-second SPOT 5 Reference3D 0.00416666 Decimal degree WGS 84
NED 0.00027777 Decimal degree NAD 83
NED – Alaska 0.00055555 Decimal degree NAD 83
GEODATA 9 second DEM version 2 0.0025 Decimal degree GDA 94
Greenland satellite radar altimeter DEM 1,000 Meter WGS 84
Antarctica satellite radar and laser altimeter DEM 1,000 Meter WGS 84
GTOPO30 0.00833333 Decimal degree WGS 84
(DTED®, Digital Terrain Elevation Data; WGS 84, World Geodetic System 1984; CDED, Canadian Digital Elevation
Data; NAD 83, North American Datum of 1983; SPOT, Satellite Pour l’Observation de la Terre; NED, National
Elevation Dataset; DEM, digital elevation model; GDA 94, Geocentric Datum of Australia 1994; GTOPO30, Global
30-Arc-Second Elevation Dataset).
Table 2: Original characteristics of the evaluated Digital Elevation Models.
DEM
Coordinate
System
Horizontal
Datum
Vertical
Reference
Spatial
Resolution
Radiometric
Resolution
ALOS
PALSAR
UTM
WGS 84 Ellipsoid*
12.5 meters
16 bits
(signed integer)
GMTED2010 Geographic WGS 84
Geoid
(EGM96)
231 meters
(7.5 arc-seconds)
16 bits
(signed integer)
SRTM Geographic WGS 84
Geoid
(EGM96)
30 meters
(1 arc-second)
16 bits
(signed integer)
Topodata Geographic WGS 84
Geoid
(EGM96)
30 meters
(1 arc-second)
32 bits
(floating point)
*The orthometric heights with EGM96 vertical datum were converted to ellipsoid heights using the ASF MapReady
tool named “geoid_adjust” (Laurencelle et al., 2015).
Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010, SRTM and Topodata Digital Elevation Models
119
Figure 3: Flowchart of methodology.
Table 3: Statistical analysis of the altitude difference between control points and DEMs.
ALOS PALSAR GMTED2010 SRTM Topodata
Mean Error (m) 12.70 13.31 12.82 12.87
RMSE (m) 4.95 7.48 4.76 5.38
H
E
min (m) -3.58 -14.22 -3.21 -6.17
H
E
max (m) 22.04 39.78 20.93 23.60
Error Amplitude (m) 25.62 54.00 24.14 29.77
2.3 Methods
Figure 3 shows the flow chart of the methodology used
in this study. The first step was to download the data
from the study area, such as raster DEMs and points
official Brazilian altimetric network. To standardize
the data, it was necessary to convert the radiometric
resolution of the Tododata DEM from 32 bits (floating
point) to 16 bits (signed integer). The next step
consisted of extracting the altitudes of the ALOS
PALSAR, GMTED2010, SRTM and Topodata DEMs
at the coordinates of the reference points (official
altimetric network). But as GMTED2010, SRTM and
Topodata models were available with altitudes
referenced to the geoid (EGM96), then it was
necessary to convert the ellipsoidal altitudes of the
ALOS PALSAR DEM to orthometric altitudes (geoid)
using the MAPGEO2015 software (IBGE, 2015),
which is developed by Brazilian Institute of Geography
and Statistics in partnership with Polytechnic School of
the University of São Paulo.
Subsequently, as well as in previous studies (Jain
et al., 2018; Varga and Bašić, 2015; Wessel et al.,
2018), statistical analysis of the errors was performed,
where were calculated some accuracy statistical
indicators such as Altimetric Error (HE) (1), Mean
Error (ME) (2), and Root Mean Square Error (RMSE)
(3). We also used the Brazilian Cartographic Accuracy
Standard (PEC) to evaluate each DEM and to identify
their best application scale. It is important to highlight
that this methodology has been used in several similar
studies such as Moura et al. (2014) and Iorio et al.
(2012).
H
E
= H
REF
- H
DEM
(1)
ME
H𝑅𝐸𝐹  H𝐷𝐸𝑀
𝑛

(2)
RMSE
  

(3)
Where H
E
= altimetric error; H
REF
= reference point
altitude from Brazilian geodetic system official
altimetric network; H
DEM
= altitude extracted from
DEM at reference point coordinates; ME = Mean
Error; RMSE = Root Mean Square Error; and n =
number of reference points.
3 RESULTS
Table 3 shows the main results of the statistical
analysis performed in this study where it is possible to
verify that regarding the mean error, the values did not
differ much. ALOS PALSAR DEM was the one with
the lowest RMSE (4.76 m) and GMTED2010 was the
one with the worst RMSE (7.48 m). As for the
amplitude of the altimetric error, given by the differen-
ce between the minimum and maximum altimetric
errors, SRTM presented the smallest result (24.14 m)
whilst GMTED2010 presented the largest amplitude
(54.00 m). Figure 4 shows the altimetric error
distribution of each DEM where it is possible to notice
a positive distortion in all DEMs, as well as a higher
variability of errors in the GMTED2010 product.
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
120
Figure 4: Histogram of the altimetric error for ALOS PALSAR (a), GMTED2010 (b), SRTM (c) and Topodata (d).
Table 4: Altimetric Cartographic Accuracy Standard of the Quoted Points and the Digital Terrain Model, Digital Elevation
Model and Digital Surface Model for Digital Cartographic Products production (Brazil, 2016).
SCALE 1:25,000 1:50,000 1:100,000 1:250,000
PEC
Class
PEC*
(m)
RMSE
(m)
PEC*
(m)
RMSE
(m)
PEC*
(m)
RMSE
(m)
PEC*
(m)
RMSE
(m)
A
2.70 1.67 5.50 3.33 13.70 8.33 27.00 16.67
B
5.00 3.33 10.00 6.66 25.00 16.66 50.00 33.33
C
6.00 4.00 12.00 8.00 30.00 20.00 60.00 40.00
D
7.50 5.00 15.00 10.00 37.50 25.00 75.00 50.00
*90% of point errors collected in the cartographic product, when compared with its coordinates surveyed in the field
by a high precision method, must present the same values or less than the predicted in this table.
Table 5: Extracted points from the DEMs (quantity and percentage) which showed altimetric errors below 15 and 25 meters.
DEM
H
E
< 15m H
E
< 25m
Points % Points % RSME (m)
ALOS PALSAR 71 67.6 105 100 4.95
SRTM 69 65.7 105 100 4.76
Topodata 63 60.0 105 100 5.38
GMTED2010 62 59.0 101 96.2 6.54
Table 4 presents the altimetric cartographic accuracy
standard for digital cartographic products production
and Table 5 shows the quantity and percentage of
extracted points from the DEMs which presented
altimetric errors below 15 and 25 meters.
Analysing the obtained results, it can be observed
that the DEMs assessed in this study may be included
in Class B for the 1:100,000 scale and in Class A for
the 1:250,000 scale (Table 6), since more than 90%
of the extracted points from DEMs assessed showed
altimetric errors less than 25 meters when compared
to the reference points. In this sense, these DEMs can
satisfactorily support studies that need a level of
detail compatible with scales 1:100,000 or smaller
than this considering the national cartographic
standard specifications.
Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010, SRTM and Topodata Digital Elevation Models
121
Table 6: DEMs classification according to Altimetric Cartographic Accuracy Standard for Digital Cartographic Products.
Scale ALOS PALSAR GMTED2010 SRTM Topodata
1:100,000 B B B B
1:250,000 A A A A
4 DISCUSSION
This study assessed the vertical accuracy of the
ALOS PALSAR, GMTED2010, SRTM and
Topodata DEMs according to Brazilian Cartographic
Accuracy Standard aiming to contribute to the correct
applicability of the analysed DEMs in the study area
and in similar areas. It was possible to verify that all
DEMs analysed here presented satisfactory accuracy
to supply mappings in 1:100,000 scales or smaller
than this, and although the GMTED2010 presented a
lower accuracy than the other DEMs, it also could be
classified in the same accuracy category according to
the Brazilian PEC, but it should be emphasized that
studies carried out in other areas may present
different results.
Previous studies have shown that ALOS
PALSAR DEM performed better when compared to
other DEMs, such as SRTM and the Advanced
Spaceborne Thermal Emission and Reflection
Radiometer (ASTER) (Arabameri et al., 2019; Rabby
et al., 2020). However, Andrades Filho and Rossetti
(2012) stated that SRTM products have a higher
potential for delineating morpho-structural
lineaments when compared to ALOS PALSAR.
Thomas et al. (2014) also attested a relatively higher
accuracy of SRTM when compared to ASTER and
GMTED2010, where it was also found that
GMTED2010 showed the worst results due to its
larger pixel size (Thomas et al., 2015). Nonetheless,
the results presented by Mantelli et al. (2011)
demonstrated a better quality of the Topodata product
in relation to SRTM and ASTER in the
characterization of drainage networks and watershed
vectors due to its refined resolution.
Regarding the Brazilian cartographic accuracy
standard, the results presented by Moura et al. (2014)
showed compatibility with the scale of 1:50,000 for
the Topodata, SRTM, ASTER and HydroSHEDS
DEMs for watersheds with little rugged relief, but for
watersheds with higher slopes and higher drainage
density, the results showed compatibility with scales
of 1:100,000 and smaller than this.
The present study demonstrated that the evaluated
DEMs have applications compatible with 1:100,000
scales since more than 90% of the extracted points
from them showed differences less than 25 meters in
the altitudes when compared to the reference points
extracted from the high accuracy altimetric network
of the Brazilian Geodetic System. In fact, ALOS
PALSAR, SRTM and Topodata DEMs presented
100% of altimetric errors less than 25 meters and only
GMTED2010 DEM presented 3.8% of altimetric
errors higher than 25 meters.
5 CONCLUSIONS
After analysing several DEMs comparative studies,
we conclude that this kind of assessment is very
important to ensure their correct applicability
regarding the appropriate scale since these data are
available for practically all areas of the planet.
Although, there are often no precise data available for
free that can make these comparisons possible, such
as, for instance, the control points of the high
accuracy altimetric network used in this study, thus
making fieldwork indispensable.
Indeed, one of the limitations in this research was
the small number of points located within the area of
the Balsas River watershed which were not evenly
distributed as they were implanted linearly along the
banks of the Brazilian highways. But it is worth
mentioning that the availability of these data from the
Brazilian altimetric network facilitates the DEMs
assessment since it enables an accurate data analysis
without the need for fieldwork.
Particularly in this study, we found that all four
assessed DEMs can support several types of
researches provided they do not require a high level
of detail and can be represented in scales up to 1:
100,000. However, future DEMs assessments should
be based on the accuracy of a specific application,
such as hydrodynamics modelling as well as they
should investigate the correlation between altimetric
error and slope (or altitude) in the study area.
GISTAM 2021 - 7th International Conference on Geographical Information Systems Theory, Applications and Management
122
ACKNOWLEDGEMENTS
This study was supported by national funds through
FCT (Fundação para a Ciência e a Tecnologia)
under the project UIDB/04152/2020 - Centro de
Investigação em Gestão de Informação (MagIC) and
the Instituto Federal de Educação, Ciência e
Tecnologia do Tocantins (Campus Palmas).
REFERENCES
Andrades Filho, C. d. O., and Rossetti, D. d. F. (2012).
Effectiveness of SRTM and ALOS-PALSAR data for
identifying morphostructural lineaments in
northeastern Brazil. International Journal of Remote
Sensing, 33(4), 1058-1077.
Arabameri, A., Pradhan, B., Rezaei, K., and Lee, C.-W.
(2019). Assessment of landslide susceptibility using
statistical-and artificial intelligence-based FR–RF
integrated model and multiresolution DEMs. Remote
Sensing, 11(9), 999.
Brazil. (1984). Decreto n° 89.817 de 20 de Junho de 1984.
Normas Técnicas da Cartografia Nacional. Presidência
da República. Casa Civil - Subchefia para Assuntos
Jurídicos.
Brazil. (2012). Secretaria do Planejamento e da
Modernização da Gestão Pública (SEPLAN).
Superintendência de Pesquisa e Zoneamento Ecológico
Econômico. Diretoria de Zoneamento Ecológico-
Econômico. Atlas do Tocantins: subsídios ao
Planejamento da Gestão Territorial. Palmas: Seplan,
80.
Brazil. (2016). Norma da Especificação Técnica para
Aquisição de Dados Geoespaciais Vetoriais de Defesa
da Força Terrestre (ET ADGV Defesa F Ter).
Edição. Diretoria de Serviço Geográfico (DSG) -
Geoportal do Exército Brasileiro.Edição. Brasília.
Danielson, J. J., and Gesch, D. B. (2011). Global multi-
resolution terrain elevation data 2010 (GMTED2010).
US Department of the Interior, US Geological Survey.
Hu, Z., Peng, J., Hou, Y., and Shan, J. (2017). Evaluation
of recently released open global digital elevation
models of Hubei, China. Remote Sensing, 9(3), 262.
IBGE. (2015). Instituto Brasileiro de Geografia e
Estatística. Modelo de ondulação geoidal -
MAPGEO2015: Sobre a publicação. Diretoria de
Geociências – DGC. Coordenação de Geodésia –
CGED. Retrieved 28 November 2020 from
https://www.ibge.gov.br/geociencias/modelos-digitais-
de-superficie/modelos-digitais-de-superficie/10855-
modelo-de-ondulacao-geoidal.html?=&t=sobre
IBGE. (2019). Instituto Brasileiro de Geografia e
Estatística. Reajustamento da Rede Altimétrica com
Números Geopotenciais. Diretoria de Geociências –
DGC. Coordenação de Geodésia – CGED. Retrieved
14 July 2020 from https://biblioteca.ibge.gov.br/
visualizacao/livros/liv101666.pdf
Iorio, M. M., Lastoria, G., Mioto, C. L., Albrez, E. d. A.,
and Paranhos Filho, A. C. (2012). Avaliação de
modelos digitais de elevação extraídos de imagem
ALOS/PRISM e comparação com os modelos
disponibilizados gratuitamente na web. Geociências
(São Paulo), 31(4), 650-664.
Jain, A. O., Thaker, T., Chaurasia, A., Patel, P., and Singh,
A. K. (2018). Vertical accuracy evaluation of SRTM-
GL1, GDEM-V2, AW3D30 and CartoDEM-V3. 1 of
30-m resolution with dual frequency GNSS for lower
Tapi Basin India. Geocarto International, 33(11),
1237-1256.
JAXA. (2020a). Japan Aerospace Exploration Agency.
Advanced Land Observing Satellite "DAICHI"
(ALOS). Advanced Land Observing Satellite
"DAICHI" (ALOS). Retrieved 16 July 2020 from
https://global.jaxa.jp/projects/sat/alos/
JAXA. (2020b). Japan Aerospace Exploration Agency.
About ALOS - Overview and Objectives. Retrieved 16
July 2020 from https://www.eorc.jaxa.jp/ALOS/en/
about/about_index.htm
Laurencelle, J., Logan, T., and Gens, R. (2015). ASF
Radiometrically Terrain Corrected ALOS PALSAR
Products. Alaska Satellite Facility: Fairbanks, Alaska.
Liu, J. K., Chang, K. T., Lin, C., and Chang, L. C. (2015).
Accuracy evaluation of ALOS DEM with airborne
LiDAR data in southern Taiwan. IEEE International
Geoscience and Remote Sensing Symposium (IGARSS),
3025-3028.
Mantelli, L. R., Barbosa, J. M., and Bitencourt, M. D.
(2011). Assessing ecological risk through automated
drainage extraction and watershed delineation.
Ecological Informatics, 6(5), 325-331.
Mesa-Mingorance, J. L., and Ariza-López, F. J. (2020).
Accuracy Assessment of Digital Elevation Models
(DEMs): A Critical Review of Practices of the Past
Three Decades. Remote Sensing, 12(16), 2630.
Moura, L. Z., Bias, E. d. S., and Brites, R. (2014). Avaliação
da acurácia vertical de modelos digitais de elevação
(MDEs) nas bacias do Paranoá e São Bartolomeu.
Revista Brasileira de Cartografia, 66(1).
Mouratidis, A., and Ampatzidis, D. (2019). European
digital elevation model validation against extensive
global navigation satellite systems data and comparison
with SRTM DEM and ASTER GDEM in Central
Macedonia (Greece). ISPRS International Journal of
Geo-Information, 8(3), 108.
NASA. (2020). National Aeronautics and Space
Administration. Shuttle Radar Topography Mission.
Retrieved 16 July from https://www2.jpl.nasa.gov/
srtm/index.html
Polidori, L., and El Hage, M. (2020). Digital Elevation
Model Quality Assessment Methods: A Critical
Review. Remote Sensing, 12(21), 3522.
Polidori, L., El Hage, M., and Valeriano, M. D. M. (2014).
Digital elevation model validation with no ground
control: application to the Topodata DEM in Brazil.
Boletim de Ciências Geodésicas, 20(2), 467-479.
Rabby, Y. W., Ishtiaque, A., and Rahman, M. (2020).
Evaluating the Effects of Digital Elevation Models in
Vertical Accuracy Assessment of ALOS PALSAR, GMTED2010, SRTM and Topodata Digital Elevation Models
123
Landslide Susceptibility Mapping in Rangamati
District, Bangladesh. Remote Sensing, 12(17), 2718.
Thomas, J., Joseph, S., Thrivikramji, K., and Arunkumar,
K. (2014). Sensitivity of digital elevation models: The
scenario from two tropical mountain river basins of the
Western Ghats, India. Geoscience Frontiers, 5(6), 893-
909.
Thomas, J., Prasannakumar, V., and Vineetha, P. (2015).
Suitability of spaceborne digital elevation models of
different scales in topographic analysis: an example
from Kerala, India. Environmental Earth Sciences,
73(3), 1245-1263.
Valeriano, M. d. M. (2008). Topodata: guia para utilização
de dados geomorfológicos locais. São José dos
Campos: Instituto Nacional de Pesquisas Espaciais, 72.
Valeriano, M. d. M., and Rossetti, D. d. F. (2012).
Topodata: Brazilian full coverage refinement of SRTM
data. Applied Geography, 32(2), 300-309.
https://doi.org/10.1016/j.apgeog.2011.05.004
Varga, M., and Bašić, T. (2015). Accuracy validation and
comparison of global digital elevation models over
Croatia. International Journal of Remote Sensing,
36(1), 170-189.
Wessel, B., Huber, M., Wohlfart, C., Marschalk, U.,
Kosmann, D., and Roth, A. (2018). Accuracy
assessment of the global TanDEM-X Digital Elevation
Model with GPS data. ISPRS Journal of
Photogrammetry and Remote Sensing, 139, 171-182.
Yap, L., Kandé, L. H., Nouayou, R., Kamguia, J., Ngouh,
N. A., and Makuate, M. B. (2019). Vertical accuracy
evaluation of freely available latest high-resolution (30
m) global digital elevation models over Cameroon
(Central Africa) with GPS/leveling ground control
points. International Journal of Digital Earth, 12(5),
500-524.
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