Vertical Accuracy and Calibration of Digital Elevation Models (DEMs) for the Piranhas-Assu River Basin, Rio Grande do Norte, Brazil

Abstract

ResumoA crescente demanda em uso de dados altimétricos de alta precisão vertical, para o uso em trabalhos ambientais, vem aumentando de forma significativa nos últimos anos. Entretanto, cuidados especiais devem ser tomados para a utilização desse tipo de produto, principalmente na verificação do seu erro vertical. Esse trabalho teve como objetivo avaliar a qualidade vertical e desenvolver uma metodologia de calibração de Modelos Digitais de Elevação (MDEs) obtidos a partir dos levantamentos realizados pela Shuttle Radar Topographic Mission e de sensores aerotransportados Light Detection And Ranging na Bacia Hidrográfica Piranhas-Açú, região norte do Estado do Rio Grande de Norte, Brasil. Essa avaliação e calibração foi realizada para duas porções dentro da área de estudo: uma regional e outra local. Na área regional foi utilizado apenas o MDE SRTM, enquanto que na área local, foram utilizados os MDEs SRTM e LiDAR aerotransportado. Para calibração foi utilizada uma malha com pontos de controle altimétrico de alta precisão vertical. Os resultados demonstraram que nas áreas de estudo, o MDE SRTM apresentou uma avaliação satisfatória de precisão vertical, melhorada (de 26 a 29%), após sua calibração. Na área local, o uso do MDE LiDAR aerotransportado se mostrou com melhor precisão vertical em comparação ao MDE SRTM, e também foi melhorado (15%) após sua calibração com pontos de controle. Esta pesquisa demonstra a necessidade de avaliação e calibração regional/local do erro vertical de qualquer MDE, antes do seu uso, em trabalhos que necessitem de informações verticais. AbstractThere is a growing need for high resolution altimetry data to use in environmental research in the last years. Therefore, addition criteria must be applied for this data usage, especially due to vertical error. This paper focuses on vertical error evaluation and calibration methodology of Digital Elevation Models (DEM) obtained with Shuttle Radar Topographic Mission and with airborne Light Detection and Ranging in the Piranhas-Açu river basin; north part of Rio Grande do Norte State, Brazil. The evaluation and calibration was conducted in two sectors of the study area: regional and local. The regional sector was evaluated with SRTM data only and the local sector with DEM from SRTM and airborne LiDAR. The calibration used a network of high vertical accuracy altimetric control points data. The results show that the in the study area the SRTM DEM accuracy is satisfactory and was improved by 26-29% after calibration. In the local area, airborne LiDAR is more accurate than SRTM and was also enhanced by control points calibration (15%). This paper demonstrates the need for vertical error analysis and calibration in DEM prior to topographic use.

Delimitation of flood areas based on a calibrated a DEM and geoprocessing: case study on the Uruguay River, Itaqui, southern Brazil

“…However, it was submitted to the calibration process for adjustment to the local reference geodetic system. The DEM calibration is a mandatory pre-processing adoption that provides improvement of both DEM vertical accuracy and linking to the geodetic system (Araújo et al, 2018). This study adopted the SRTM calibration method suggested by Araújo et al (2018).…”

“…The DEM calibration is a mandatory pre-processing adoption that provides improvement of both DEM vertical accuracy and linking to the geodetic system (Araújo et al, 2018). This study adopted the SRTM calibration method suggested by Araújo et al (2018). These authors used control points of high vertical accuracy linked to the Brazilian Geodetic System (in Portuguese Sistema Geodésico Brasileiro -SGB) for calibrating the DEMs.…”

“…Then, the DEM obtained from the SRTM image was calibrated using the model proposed by the linear regression. Subsequently, both DEMs (the original and calibrated) were subjected to descriptive statistical analysis and comparison between the mean of orthometric height variation ( H ) and the root mean square error (RMSE) value, as proposed by Araújo et al (2018). In all statistical analyses, a significance value of 5 % (Zar, 2010) was adopted and they were performed on R software v.3.4.1 (R Development Core Team, 2017).…”

“…Comparing the error evaluators, it was already expected that the calibrated SRTM mean of the orthometric height variation ( H ) would be zero (Table 4). According to Araújo et al (2018) this happens due to the DEM plan being perfectly adjusted to the GCP network plan after calibration, linking the MDE calibration to the Brazilian Geodetic System (SGB). In relation to the RMSE of the original SRTM (non-calibrated SRTM), a RMSE of 3.14m was found from comparison to the GCPs.…”

“…The modeling of a flood hazard map is linked to the local geodetic reference system, corroborated with the identification and monitoring of flood situations, and construction of realistic predictive scenarios (operational level) for risk management and adaptation (governmental agencies, such as the local civil defense) (Joshi et al, 2012;Gallien et al, 2018;Jongman, 2018). It is extremely important to do the calibration of the digital elevation model (DEM) using high-accuracy ground control point (GCP) data, aimed at improving the vertical accuracy, and applied to regional or local studies about floods (Araújo et al, 2018). Therefore, this study aims to conduct a robust mapping of flood hazard delimitation areas influenced by the Uruguay River, using the case study of Itaqui in the state of Rio Grande do Sul, southern Brazil, through a calibration of DEM from Shuttle Radar Topography Mission (SRTM) images, historical fluviometric level data collected at Itaqui station, and geoprocessing techniques.…”