Analysis and correction of digital elevation models for plain areas
; Vives, Luis Sebastián ; Zimmermann, Erik Daniel
; Masson, Ignacio ; Fajardo, Luisa ; Scioli, Carlos Otros responsables
Fecha
03/2019
Editorial
Amer Soc Photogrammetry
Revista
Photogrammetric Engineering And Remote Sensing
Título del libro
Nombre del evento
Fecha del evento
Institución organizadora
ISSN
0099-1112
eISSN
ISBN
Idioma
Inglés
Tipo del evento
Clasificación temática
Palabras clave
Resumen
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.
Colecciones
Aprobación
Revisión
Complementado por
Referenciado por
Licencia Creative Commons
Excepto donde se indique lo contrario, la licencia de este ítem se describe como by-nc-sa
