Next Article in Journal
Determining the Suitable Number of Ground Control Points for UAS Images Georeferencing by Varying Number and Spatial Distribution
Previous Article in Journal
Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model
Previous Article in Special Issue
Airborne Electromagnetic and Radiometric Peat Thickness Mapping of a Bog in Northwest Germany (Ahlen-Falkenberger Moor)
Article

The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data

Department of Geodetic Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jalan Grafika No. 2, Yogyakarta 55284, Indonesia
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(5), 875; https://doi.org/10.3390/rs12050875
Received: 31 December 2019 / Revised: 4 March 2020 / Accepted: 5 March 2020 / Published: 9 March 2020
(This article belongs to the Special Issue Remote Sensing of Peatlands II)
High-accuracy peat maps are essential for peatland restoration management, but costly, labor-intensive, and require an extensive amount of peat drilling data. This study offers a new method to create an accurate peat depth map while reducing field drilling data up to 75%. Ordinary least square (OLS) adjustments were used to estimate the elevation of the mineral soil surface based on the surrounding soil parameters. Orthophoto and Digital Terrain Models (DTMs) from LiDAR data of Tebing Tinggi Island, Riau, were used to determine morphology, topography, and spatial position parameters to define the DTM and its coefficients. Peat depth prediction models involving 100%, 50%, and 25% of the field points were developed using the OLS computations, and compared against the field survey data. Raster operations in a GIS were used in processing the DTM, to produce peat depth estimations. The results show that the soil map produced from OLS provided peat depth estimations with no significant difference from the field depth data at a mean absolute error of ±1 meter. The use of LiDAR data and the OLS method provides a cost-effective methodology for estimating peat depth and mapping for the purpose of supporting peat restoration. View Full-Text
Keywords: peat depth prediction; soil properties estimation; least square adjustment; sub-stratum elevation; LiDAR DTM peat depth prediction; soil properties estimation; least square adjustment; sub-stratum elevation; LiDAR DTM
Show Figures

Graphical abstract

MDPI and ACS Style

Cahyono, B.K.; Aditya, T.; Istarno. The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data. Remote Sens. 2020, 12, 875. https://doi.org/10.3390/rs12050875

AMA Style

Cahyono BK, Aditya T, Istarno. The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data. Remote Sensing. 2020; 12(5):875. https://doi.org/10.3390/rs12050875

Chicago/Turabian Style

Cahyono, Bambang K., Trias Aditya, and Istarno. 2020. "The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data" Remote Sensing 12, no. 5: 875. https://doi.org/10.3390/rs12050875

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop