Evaluation of digital elevation models for hydrological analysis in forest environments: a case study of the Parque Estadual do Turvo, Rio Grande do Sul

Authors

DOI:

https://doi.org/10.5902/2236499485914

Keywords:

Forest resources, Topography, Remote sensing

Abstract

Digital elevation models have proven efficient in obtaining altimetric measurements of the terrain; however, in forested areas, their effectiveness decreases by canopy interference. This study aimed to assess the performance of three digital elevation models in extracting the drainage network of Parque Estadual do Turvo. The acquisition included FABDEM, SRTM, and ASTER GDEM models, alongside measurements obtained through topographic survey as field reference. Altimetric measurements were graphically and statistically analyzed to characterize the vertical error of each model. The results indicated differences in vertical precision due to canopy sensitivity, although statistical tests did not reveal statistical significance. The greatest discrepancies occurred in valley areas with steep slopes, challenging for topographic data acquisition. Drainage network delineation showed that all models effectively distinguish main channels, although ASTER GDEM and SRTM models exhibit higher spatial inaccuracies. The FABDEM model was highlighted because of its greater spatial correspondence with the existing drainage network in the park area.

Downloads

Download data is not yet available.

Author Biographies

William Gaida, Universidade Federal de Santa Maria

He holds a Bachelor's degree in Geography from the Federal University of Santa Maria, a Master's degree and a PhD in Geography from the same institution. She is currently studying for a post-doctorate in the Environmental Science and Technology Graduate Program at the Federal University of Santa Maria - Frederico Westphalen Campus. She is a member of the Geoprocessing and Remote Sensing Laboratory. She develops research projects in the areas of remote sensing, geoprocessing, cartography and analysis of aquatic and forest environments.

Daniele Arendt Erthal, Universidade Federal de Santa Maria

She holds a PhD in Geography from the Federal University of Santa Maria, Frederico Westphalen Campus, a Master's degree in Agronomy - Agriculture and Environment from the Federal University of Santa Maria, Frederico Westphalen Campus and graduated as a Forest Engineer in 2014, also from the Federal University of Santa Maria, Frederico Westphalen Campus. She took part in the research project SPECTRUM AND ANGLE STUDIES IN FOREST AND AGRICULTURAL ENVIRONMENTS at the Geoprocessing and Remote Sensing Laboratory, in which she received a grant, as well as other research in the same area. She was a tutor in Remote Sensing. She also took part in the research project Quantifying biomass in subtropical forest ecosystems. She worked as an Environmental Analyst at Saltus Consultoria Ambiental e Florestal, and is currently an Environmental Analyst at CMPC Celulose Rio Grandense.

Fábio Marcelo Breunig, Universidade Federal de Santa Maria

He has a degree in Geography from the Federal University of Santa Maria, a Master's and PhD in Remote Sensing from the National Institute for Space Research. In 2015 and 2019 he did postdoctoral work on remote sensing applications in the study of inland waters and precision agriculture, respectively. He currently coordinates two CNPQ research groups, and participates in research and extension projects related to Remote Sensing of the Environment (agriculture, forest, water), GIS, Error Analysis and Environmental Modeling.

Tony Vinicius Moreira Sampaio, Universidade Federal de Santa Maria

He holds a bachelor's degree in Geography and a specialist degree in Ecology and Natural Resources from the Federal University of Espírito Santo (1993, 1996), a master's degree in Geography in the area of Human Organization of Space and a PhD in the area of Environmental Analysis, both from the Federal University of Minas Gerais (2001, 2008). A professor at the Federal University of Paraná (UFPR), he teaches Thematic Cartography and Digital Cartography at the undergraduate level and Information Quality in Geospatial Data and Geostatistics at the Master's and Doctorate levels (since 2008). She supports projects in the areas of Thematic Mapping, the preparation of studies for the implementation and recovery of the road network (railroads, highways and waterways). He has experience in the field of Education, with an emphasis on curriculum development for Geography courses and textbook analysis. He has developed research in the areas of thematic mapping, UAVs (drones), quality of information in geospatial data, mapping of drainage networks, geostatistics and spatial statistics, and environmental impact analysis.

Renato Beppler Spohr, Universidade Federal de Santa Maria

He holds a degree in Agronomy from the Federal University of Santa Maria (1999), a master's degree and a doctorate in Agricultural Engineering from the Federal University of Santa Maria. He is currently an associate professor in the Department of Forestry Engineering at the Federal University of Santa Maria, Frederico Westphalen campus. He develops research projects on topics related to research and development of tools and the use of geoinformation in the areas of water resources and soil and water conservation and forestry.

References

ABDEL-MAGUID, R. H. Evaluation of vertical accuracy of different digital elevation models sources for Buraydah city. Applied Geomatics, v. 13, p. 919-924, 2021.

ABRAMS, M.; BAILEY, B.; TSU, H.; HATO, M. The ASTER Global DEM. Photogrammetric Engineering and Remote Sensing, v. 76, p. 344-348, 2010.

ABRAMS, M.; CRIPPEN, R.; FUJISADA, H. ASTER global digital elevation model (GDEM) and ASTER global water body dataset (ASTWBD). Remote Sensing, v. 12, n. 7, 2020.

ANDERSEN, K. M.; TURNER, B. L.; DALLING, J. W. Seedling performance trade-offs influencing habitat filtering along a soil nutrient gradient in a tropical forest. Ecology, v. 95, n. 2, p. 3399-3413, 2014.

ATTEMA, E.; CAFFORIO, C.; GOTTWALD, M.; GUCCIONE, P.; GUARNIERI, A. M.; ROCCA, F.; SNOEIJ, P. Flexible dynamic block adaptative quantization for Sentinel-1 SAR missions. IEEE Geoscience and Remote Sensing Letters, v. 7, n. 4, p. 766-770, 2010.

BULFE, N. M. L. Dinâmica de clareiras originadas de exploração seletiva de uma floresta estacional semidecidual na Provincia de Misiones, nordeste da Argentina. Tese de Doutorado. Universidade Federal do Paraná (UFPR) – Curitiba, 73 p., 2008.

CHADWICK, K. D.; ASNER, G. P. Tropical soil nutrient distributions determined by biotic and hillslope processes. Biogeochemistry, v. 127, p. 273-289, 2016.

FARR, T. G.; ROSEN, P. A.; CARO, E.; CRIPPEN, R.; DUREN, R.; HENSLEY, S.; KOBRICK, M.; PALLER, M.; RODRIGUEZ, E.; ROTH, L.; SEAL, D.; SHAFFER, S.; SHIMADA, J.; UMLAND, J.; WERNER, M.; OSKIN, M.; BURBANK, D.; ALSDORF, D. The Shuttle Radar Topography Mission. Reviews of Geophysics, v. 45, n. 2, p. 1-33, RG2004, 2007.

GAIDA, W.; BREUNIG, F. M.; GALVÃO, L. S.; TELES, T. S.; BALBINOT, R. Variações da reflectância e dos índices de vegetação em função dos parâmetros da modelagem topográfica no Parque Estadual do Turvo, Rio Grande do Sul, Brasil. Investigaciones Geográficas, Boletín del Instituto de Geografía, v. 2016, n. 91, p. 105-123, 2016.

GROHMANN, C. H. Evaluation of TanDEM-X DEMs on selected brazilian sites: comparison with SRTM, ASTER GDEM and ALOS AW3D30. Remote Sensing, v. 212, p. 121-133, 2018.

GUADAGNIN, D. L. Zonificación del Parque Estadual do Turvo, RS, Brasil, y directivas para el plan de manejo. Tese de Doutorado. Universidad Nacional de Córdoba – Córdoba, Argentina. 1994.

HAWKER, L.; UHE, P.; PAULO, L.; SOSA, J.; SAVAGE, J.; SAMPSON, C.; NEAL, J. A 30 m global map of elevation with forests and buildings removed. Environmental Research Letters, v. 17, n. 2, 2022.

INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA (IBGE). Folhas SH 22 Porto Alegre e parte das folhas SH 21 e SI 22 Lagoa Mirim: levantamento de recursos naturais. Geologia, geomorfologia, pedologia, vegetação, uso potencial da terra. Rio de Janeiro; 1986. v. 33.

JUCKER, T.; BONGALOV, B.; BURSLEM, D. F. R. P.; NILUS, R.; DALPONTE, M.; LEWIS, S. L.; PHILLIPS, O. L.; QIE, L.; COOMES, D. A. Topography shapes the structure, composition and function of tropical forest landscapes. Ecology Letters, v. 21, n. 7, p. 989-1000, 2018.

HUNG, M. N. W. B., SAMPAIO, T. V. M., SCHULTZ, G. B., SIEFERT, C. A. C., LANGE, D. R., MARANGON, F. H. S., & SANTOS, I. DOS. (2018). Levantamento Com Veículo Aéreo Não Tripulado Para Geração De Modelo Digital Do Terreno Em Bacia Experimental Com Vegetação Florestal Esparsa. Raega, v. 43, n. 215. 2018.

LI, Y.; LI, L.; CHEN, C.; LIU, Y. Correction of global digital elevation models in forested areas using an artificial neural network-based method with the consideration of spatial autocorrelation. International Journal of Digital Earth, v. 16, n. 1, p. 1568-1588, 2023.

LIANG, Y.; QU, Y.; GUO, D.; CUI, T. Vertical accuracy evaluation of ASTER GDEM2 over a mountainous area based on UAV photogrammetry. In: ISPRS TC II Mid-term Symposium, Riva del Garda, 2018. Proceedings… International Society for Photogrammetry and Remote Sensing, v. XLII-2, p. 579-584, 2018.

MOGES, D. M.; VIRRO, H.; KMOCH, A.; CIBIN, R.; ROHITH, A. N.; MARTÍNEZ-SALVADOR, A.; CONESA-GARCÍA, C.; UUEMAA, E. How does the choice of DEMs affect catchment hydrological modeling? Science of the Total Environment, v. 892, 2023.

MUÑOZ, V. A.; VALERIANO, M. M.; BISPO, P. C. Surveying the topographic height from SRTM data for canopy mapping in the Brazilian Pantanal. Geografia, v. 38, n. especial, p. 139-155, 2013.

MUSCARELLA, R.; KOLYAIE, S.; MORTON, D. C.; ZIMMERMAN, J. K.; URIARTE, M. Effects of topography on tropical forest structure depend on climate context. Journal of Ecology, v. 108, n. 1, p. 145-159, 2020.

NEUMAN, Gisele; SILVEIRA, Claudinei Taborda Da; SAMPAIO, Tony Vinicius Moreira. Análise Da Influência Da Escala Na Obtenção Dos Atributos Topográficos Derivados De Mde. Raega - O Espaço Geográfico em Análise, [s. l.], v. 43, p. 179, 2018.

NI, W.; SUN, G.; RANSON, K. J. Characterization of ASTER GDEM elevation data over vegetated area compared with lidar data. International Journal of Digital Earth, v. 8, n. 3, p. 198-211, 2015.

O'LOUGHLIN, F. E.; PAIVA, R. C. D.; DURAND, M.; ALSDORF, D. E.; BATES, P. D. A multi-sensor approach towards a global vegetation corrected SRTM DEM product. Remote Sensing of Environment, v. 182, p. 49-59, 2016.

PREETY, K.; PRASAD, A. K.; VARNA, A. K.; EL-ASKARY, H. Accuracy assessment, comparative performance, and enhancement of public domain digital elevation models (ASTER 30 m, SRTM 30 m, CARTOSAT 30 m, SRTM 90 m, MERIT 90 m, and TanDEM-X 90 m) using DGPS. Remote Sensing, v. 14, 1334, 2022.

RIO GRANDE DO SUL. Decreto n° 17.432, de 11 de agosto de 1965. Retifica os limites da Reserva Florestal Estadual, situada no Município de Tenente Portela. Constituição do Estado do Rio Grande do Sul: Porto Alegre, 1965.

SAHOO, R.; JAIN, V. Sensitivity of drainage morphometry based hydrological response (GIUH) of a river basin to the spatial resolution of DEM data. Computers & Geosciences, v. 111, p. 78-86, 2018.

SAMPAIO, T. V. M.; ROCHA, J. On the quality of the drainage network cartographic representation. Ecological Indicators, [s. l.], v. 143, 2022.

SATGÉ, F.; BONNET, M. P.; TIMOUK, F.; CALMANT, S.; PILLCO, R.; MOLINA, J.; LAVADO-CASIMIRO, W.; ARSEN, A.; CRÉTAUX, J. F.; GARNIER, J. Accuracy assessment of SRTM v4 and ASTER GDEM v2 over the Altiplano watershed using ICESat/GLAS data. International Journal of Remote Sensing, v. 36, n. 2, p. 465-488, 2015.

SCHLUND, M.; BARON, D.; MAGDON, P.; ERASMI, S. Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests. ISPRS Journal of Photogrammetry and Remote Sensing, v. 147, p. 232-241, 2019.

SECRETARIA ESTADUAL DO MEIO AMBIENTE DO ESTADO DO RIO GRANDE DO SUL (SEMA/RS). Plano de Manejo do Parque Estadual do Turvo - RS. Porto Alegre: SEMA, 2005. Disponível em: <https://www.sema.rs. gov.br/upload/arquivos/201610/241724 30-plano-manejo-peturvo.pdf>. Acesso em 16 out. 2021.

SHERMAN, G. QGIS - A Free and Open Source Geographic Information System. Viena GNU - Free Software Foundation, Inc., , 2002. Disponível em: http://www.qgis.org/en/site/

SOUZA, G. M.; MATRICARDI, E . A. T. Análise comparativa dos modelos de elevação SRTM, ASTER GDEM e TOPODATA para estimar o fator topográfico (LS) da USLE. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 16, 2013, Foz do Iguaçu. Anais... São José dos Campos: INPE, 2013. p. 4435-4442.

SOUSA, M. S.; SAMPAIO, T. V. M. Avaliação da acurácia de bases cartográficas: um estudo de caso da rede de drenagem do estado do Paraná na escala 1:50.000 para a carta MI 2818-4. Anais... XVII Simpósio Brasileiro de Sensoriamento Remoto - SBSR, João Pessoa-PB, Brasil, 25 a 29 de abril de 2015, INPE, [s. l.], n. 1, p. 6381–6388, 2015.

SU, Y.; GUO, Q.; MA, Q.; LI, W. SRTM DEM correction in vegetated mountain areas through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery. Remote Sensing, v. 7, p. 11202-11225, 2015.

TVEITE, H.; LANGAAS, S. An accuracy assessment method for geographical line data sets based on buffering. International Journal of Geographical Information Science, v. 13, n. 1, p. 27-47, 1999.

WERNER, F. A.; HOMEIER, J. Is tropical montane forest heterogeneity promoted by a resource-driven feedback cycle? Evidence from nutrient relations, herbivory and litter decomposition along a topographical gradient. Functional Ecology, v. 29, n. 3, p. 430-440, 2015.

WOODROW, K.; LINDSAY, J. B.; BERG, A. A. Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction. Journal of Hydrology, v. 540, p. 1022–1029, 2016.

XIA, S. -W.; CHEN, J.; SCHAEFER, D.; GOODALE, U. M. Effect of topography and litterfall input on fine-scale patch consistency of soil chemical properties in a tropical rainforest. Plant and Soil, v. 404, p. 385-398, 2016.

Downloads

Published

2024-10-18

How to Cite

Gaida, W., Erthal, D. A., Breunig, F. M., Sampaio, T. V. M., & Spohr, R. B. (2024). Evaluation of digital elevation models for hydrological analysis in forest environments: a case study of the Parque Estadual do Turvo, Rio Grande do Sul. Geografia Ensino & Pesquisa, 28, e85914. https://doi.org/10.5902/2236499485914

Issue

Vol. 28 (2024): Dossiê Parque Estadual do Turvo ( PET) - Yucumã

Section

Special Edition

License

Copyright (c) 2024 Geografia Ensino & Pesquisa

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The journal Geografia – Ensino & Pesquisa will obtain the auctorial rights for all published texts. This also implies that the text can be published anywhere in the world, including all rights on renewal, expansion and dissemination of the contribution, as well as other subsidiary rights. The author’s get permission to publish the contribution in other medias, printed or digital, may be in Portuguese or translation, since the publication is credited to Revista Geografia – Ensino & Pesquisa.The journal Geografia – Ensino & Pesquisa will obtain the auctorial rights for all published texts. This also implies that the text can be published anywhere in the world, including all rights on renewal, expansion and dissemination of the contribution, as well as other subsidiary rights. The author’s get permission to publish the contribution in other medias, printed or digital, may be in Portuguese or translation, since the publication is credited to Revista Geografia – Ensino & Pesquisa.

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.