University of Oulu

Bhattacharjee, J., Marttila, H., Haghighi, A. T., Saarimaa, M., Tolvanen, A., Lepistö, A., Futter, M. N., & Kløve, B. (2021). Development of Aerial Photos and LIDAR Data Approaches to Map Spatial and Temporal Evolution of Ditch Networks in Peat-Dominated Catchments. Journal of Irrigation and Drainage Engineering, 147(4), 04021006. https://doi.org/10.1061/(asce)ir.1943-4774.0001547

Development of aerial photos and LIDAR data approaches to map spatial and temporal evolution of ditch networks in peat-dominated catchments

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Author: Bhattacharjee, Joy1; Marttila, Hannu1; Haghighi, Ali Torabi1;
Organizations: 1Water, Energy and Environmental Engineering Research Unit, Univ. of Oulu, Oulu FI-90014, Finland
2Leading Natural Science Expert, Finnish Forest Center, Oulu FI-90400, Finland
3Natural Resources Institute Finland (Luke), Univ. of Oulu, Oulu FI-90014, Finland
4Finnish Environment Institute (SYKE), Helsinki FI-00251, Finland
5Dept. of Aquatic Sciences and Assessment, Swedish Univ. of Agricultural Sciences SLU, Uppsala SE-75007, Sweden
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021081743446
Language: English
Published: American Society of Civil Engineers, 2021
Publish Date: 2021-08-17
Description:

Abstract

Spatiotemporal information on historical peatland drainage is needed to relate past land use to observed changes in catchment hydrology. Comprehensive knowledge of historical development of peatland management is largely unknown at the catchment scale. Aerial photos and light detection and ranging (LIDAR) data enlarge the possibilities for identifying past peatland drainage patterns. Here, our objectives are (1) to develop techniques for semiautomatically mapping the location of ditch networks in peat-dominated catchments using aerial photos and LIDAR data, and (2) to generate time series of drainage networks. Our approaches provide open-access techniques to systematically map ditches in peat-dominated catchments through time. We focused on the algorithm in such a way that we can identify the ditch networks from raw aerial images and LIDAR data based on the modification of multiple filters and number of threshold values. Such data are needed to relate spatiotemporal drainage patterns to observed changes in many northern rivers. We demonstrate our approach using data from the Simojoki River catchment (3,160  km²) in northern Finland. The catchment is dominated by forests and peatlands that were almost all drained after 1960. For two representative locations in cultivated peatland (downstream) and peatland forest (upstream) areas of the catchment; we found total ditch length density (km/km²), estimated from aerial images and LIDAR data based on our proposed algorithm, to have varied from 2% to 50% compared with the monitored ditch length available from the National Land survey of Finland (NLSF) in 2018. A different pattern of source variation in ditch network density was observed for whole-catchment estimates and for the available drained-peatland database from Natural Resources Institute Finland (LUKE). Despite such differences, no significant differences were found using the nonparametric Mann-Whitney U test with a 0.05 significance level based on the samples of pixel-identified ditches between (1) aerial images and NLSF vector files and (2) LIDAR data and NLSF vector files.

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Series: Journal of irrigation and drainage engineering
ISSN: 0733-9437
ISSN-E: 1943-4774
ISSN-L: 0733-9437
Volume: 147
Issue: 4
Article number: 04021006
DOI: 10.1061/(ASCE)IR.1943-4774.0001547
OADOI: https://oadoi.org/10.1061/(ASCE)IR.1943-4774.0001547
Type of Publication: A1 Journal article – refereed
Field of Science: 218 Environmental engineering
1172 Environmental sciences
1171 Geosciences
Subjects:
Funding: This work was part of the Nordic Centre of Excellence BIOWATER, funded by Nordforsk under project number 82263.
Copyright information: © 2021 American Society of Civil Engineers. The final authenticated version is available online at https://doi.org/10.1061/(asce)ir.1943-4774.0001547.