water
Article
A Deterministic Topographic Wetland Index Based on
LiDAR-Derived DEM for Delineating Open-Water Wetlands
Linlong Bian
1,
*, Assefa M. Melesse
2
, Arturo S. Leon
1
, Vivek Verma
1
and Zeda Yin
1
Citation: Bian, L.; Melesse, A.M.;
Leon, A.S.; Verma, V.; Yin, Z. A
Deterministic Topographic Wetland
Index Based on LiDAR-Derived DEM
for Delineating Open-Water Wetlands.
Water 2021, 13, 2487. https://
doi.org/10.3390/w13182487
Academic Editor: Thomas Meixner
Received: 12 August 2021
Accepted: 7 September 2021
Published: 10 September 2021
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4.0/).
1
Department of Civil and Environmental Engineering, Florida International University, Miami, FL 33199, USA;
arleon@fiu.edu (A.S.L.); vverm002@fiu.edu (V.V.); zyin005@fiu.edu (Z.Y.)
2
Department of Earth and Environment, Florida International University, Miami, FL 33199, USA;
melessea@fiu.edu
* Correspondence: lbian003@fiu.edu; Tel.: +1-305-674-6754
Abstract: Wetlands play a significant role in flood mitigation. Remote sensing technologies as an
efficient and accurate approach have been widely applied to delineate wetlands. Supervised classifi-
cation is conventionally applied for remote sensing technologies to improve the wetland delineation
accuracy. However, performing supervised classification requires preparing the training data, which
is also considered time-consuming and prone to human mistakes. This paper presents a deterministic
topographic wetland index to delineate wetland inundation areas without performing supervised
classification. The classic methods such as Normalized Difference Vegetation Index, Normalized
Difference Water Index, and Topographic Wetness Index were chosen to compare with the proposed
deterministic topographic method on wetland delineation accuracy. The ground truth sample points
validated by Google satellite imageries from four different years were used for the assessment of
the delineation overall accuracy. The results show that the proposed deterministic topographic
wetland index has the highest overall accuracy (98.90%) and Kappa coefficient (0.641) among the
selected approaches in this study. The findings of this paper will provide an alternative approach for
delineating wetlands rapidly by using solely the LiDAR-derived Digital Elevation Model.
Keywords: wetland delineation; supervised classification; LiDAR-derived DEM; deterministic topo-
graphic approach; TWI; NDVI; NDWI
1. Introduction
It has been well-documented that wetlands are significantly effective in alleviating
floods [1,2]. They can perform as a water storage unit to detain part of peak runoff during
a rainfall event. For example, it is estimated that the 8500 acres of wetlands along the
Charles River in Massachusetts used for natural flood storage have a present value for
flood prevention of $33,370 per acre [3]. Another study indicated that only 13 million acres
of wetlands (3% of the upper Mississippi watershed) would have been required in the
upper Mississippi watershed to avoid a devastating flood in 1993 [4]. A study conducted
by Nivitzki [5] concluded that a watershed with as little as 5% lake and wetland area might
lead to a 40–60% lower flood peak. The research conducted by Leon et al. [6] and Tang
et al. [7,8] indicated that by dynamically releasing water from upland wetlands, 3.5% of
the hypothetical wetland areas in the Cypress Creek watershed located in the northwest of
Houston TX could significantly eliminate the flooded area by around 75%. Since wetlands
perform a vital function to detain runoff, it is necessary and critical to comprehensively
understand the spatial distribution, the inundation area, and the maximum storage capacity
of the wetlands in a watershed for the flood mitigation study.
From the perspective of identifying the location and delineating the inundation extent
for wetlands, the ground-based survey is considered the most accurate method. How-
ever, aside from the need for specific experts on-site, the traditional method can be time-
consuming and costly as it involves detailed on-site surveys such as extraction of soil
Water 2021, 13, 2487. https://doi.org/10.3390/w13182487 https://www.mdpi.com/journal/water