Quantifying the Accuracy of LiDAR-Derived DEM in Deciduous Eastern Forests of the Cumberland Plateau

ISSN Print: 2151-1950
ISSN Online: 2151-1969
www.scirp.net/journal/jgis
E-mail: [email protected]

Citations

"Quantifying the Accuracy of LiDAR-Derived DEM in Deciduous Eastern Forests of the Cumberland Plateau"
written by Marco A. Contreras, Wesley Staats, Jian Yiang, David Parrott,
published by Journal of Geographic Information System, Vol.9 No.3, 2017

has been cited by the following article(s):

[1]	Evaluating the performance of various interpolation techniques on digital elevation models in highly dense forest vegetation environment
	Ecological Informatics, 2024

[2]	Synthetic Forest Stands and Point Clouds for Model Selection and Feature Space Comparison
	Remote Sensing, 2023

[3]	Development of Digital Terrain Model Under High Dense Forest Cover Using USGS and Drone Lidar Data
	IGARSS 2023-2023 IEEE …, 2023

[4]	A Quantitative Assessment of LIDAR Data Accuracy. Remote Sens. 2023, 15, 442
	2023

[5]	A Quantitative Assessment of LIDAR Data Accuracy
	Remote Sensing, 2023

[6]	Predicting and mapping Plethodontid salamander abundance using LiDAR-derived terrain and vegetation characteristics. Forest Systems, Volume 29, Issue 2 …
	2020

[7]	Predicting and mapping Plethodontid salamander abundance using LiDAR-derived terrain and vegetation characteristics
	2020

[8]	PIXEL SIZE EFFECTS ON DAM WATER STORAGE CAPACITY ESTIMATION USING GIS: CASE STUDY OF BUYUK KARACAY DAM, TURKEY
	2020

[9]	Accuracy Analysis of Digital Elevation Models from very High Resolution Satellite Imagery
	2019

[10]	Quality assessment of DEM derived from topographic maps for geomorphometric purposes
	2019

[11]	An Assessment of a LiDAR-Based Approach for Estimating Hydraulic Geometry Regional and Regime Relationship Curves for the Southern Driftless Area of the …
	2019

[12]	Potential of Very High Resolution Satellite Imagery for 3D Reconstruction and Classification

[1]	Application of a mixed additive and multiplicative random error model to generate DTM products from LiDAR data Open Geosciences, 2025 DOI:10.1515/geo-2025-0809

[2]	Spatial assessment of surface water vulnerability through MCDM and open-source data Environmental Monitoring and Assessment, 2025 DOI:10.1007/s10661-025-14357-z

[3]	Analyzing vegetation effects on snow depth variability in Alaska's boreal forests with airborne lidar The Cryosphere, 2025 DOI:10.5194/tc-19-3477-2025

[4]	Development of Digital Terrain Model Under High Dense Forest Cover Using USGS and Drone Lidar Data IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023 DOI:10.1109/IGARSS52108.2023.10282409

[5]	Predicting and mapping Plethodontid salamander abundance using LiDAR-derived terrain and vegetation characteristics Forest Systems, 2020 DOI:10.5424/fs/2020292-16074

[6]	Quality assessment of DEM derived from topographic maps for geomorphometric purposes Open Geosciences, 2019 DOI:10.1515/geo-2019-0066