Analysis and correction of digital elevation models for plain areas

Water movement modeling in plain areas requires digital elevation models (DEMs) adequately representing the morphological and geomorphological land patterns including the presence of civil structures that could affect water flow patterns. This has a direct effect on water accumulation and water flow...

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Detalles Bibliográficos
Autores: Guevara Ochoa, Cristian, Vives, Luis Sebastián, Zimmermann, Erik Daniel, Masson, Ignacio, Fajardo, Luisa, Scioli, Carlos
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/151841
Acceso en línea:http://hdl.handle.net/11336/151841
Access Level:acceso abierto
Palabra clave:ASTER GDEM2
SRTM
ALOS PALSAR
DEMs
https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
Descripción
Sumario:Water movement modeling in plain areas requires digital elevation models (DEMs) adequately representing the morphological and geomorphological land patterns including the presence of civil structures that could affect water flow patterns. This has a direct effect on water accumulation and water flow direction. The objectives of this work were to analyze, compare and improve DEMs so surface water movement in plain areas could be predicted. In order to do that, we evaluated the accuracy of a digital elevation data set consisting in 4,064 points measured with a differential GPS in a plain area of central Buenos Aires province. Three DEMs were analyzed: (1) the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), (2) the Shuttle Radar Topography Mission (SRTM) and (3) the Advanced Land Observing Satellite with the Phased Array Type L-Band Synthetic Aperture Radar (ALOS PALSAR). Several topographic attributes (i.e., height, surface area, land slope, delimitation of geomorphological units, civil structures, basin boundaries and streams network) and different interpolation methods were analyzed. The results showed that both the SRTM and the ALOS PALSAR DEMs had a ± 4.4 m root mean square error (RMSE) in contrast to the ASTER DEM which had a ± 9 m RMSE. Our analysis proved that the best DEM representing the study area is the SRTM. The most suitable interpolation methods applied to the SRTM were the inverse distance weighting and the ANUDEM, whereas the spline method displayed the lowest vertical accuracy. With the proposed method we obtained a DEM for the study area with a ± 3.2 m RMSE, a 33% error reduction compared to the raw DEM.