A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Chang Huang,Wolfgang Wagner,Ba Duy Nguyen,Senmao Cao,Shiqiang Zhang

doi:10.3390/ijgi6050140

Abstract

The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well.

Highlights

Water contributes to all aspects of economic and social development
Surface water bodies are dynamic in nature as they shrink, expand, or change their appearance with time, owing to different natural and human-induced factors
Interferometric Wide (IW) Swath mode Sentinel-1 data for these study sites on the selected dates were downloaded from the European Space Agency (ESA) Scientific hub website

Summary

Introduction

Water contributes to all aspects of economic and social development. Water supply, sanitation, and a healthy environment form the basis of successful poverty reduction and shared-growth strategies, especially in developing countries [1]. Other popular methods include active contour models [9], texture-based segmentations [10], and grey-level thresholding [11] Among all these methods, grey-scale thresholding is still the most commonly used approach to detect water areas using SAR imagery [12], due to its efficiency and acceptable accuracy. Mountains and hills may block the transmission and reception of microwave pulses, and introduce shadows and blind areas on SAR images This usually impacts the water detection algorithms, especially when using grey-scale thresholding method, because the blocked areas have low backscatter just as water surfaces do [14]. There are many studies that have employed Digital Elevation Models (DEMs), digital representations of ground surface topography or relief, in detecting water bodies from remote sensing imagery [15,16,17].

SAR Data

DEM Data

Calculation of MrVBF Index

Findings

Optimal Thresholds and Their Performance