Automated Inundation Mapping Over Large Areas Using Landsat Data and Google Earth Engine

Victoria L Inman,Mitchell B Lyons

doi:10.3390/rs12081348

Abstract

Accurate inundation maps for flooded wetlands and rivers are a critical resource for their management and conservation. In this paper, we automate a method (thresholding of the short-wave infrared band) for classifying peak inundation in the Okavango Delta, northern Botswana, using Landsat imagery and Google Earth Engine. Inundation classification in the Okavango Delta is complex owing to the spectral overlap between inundated areas covered with aquatic vegetation and dryland vegetation classes on satellite imagery, and classifications have predominately been implemented on broad spatial resolution imagery. We present the longest time series to date (1990–2019) of inundation maps for the peak flood season at a high spatial resolution (30 m) for the Okavango Delta. We validated the maps using image-based and in situ data accuracy assessments, with overall accuracy ranging from 91.5% to 98.1%. Use of Landsat imagery resulted in consistently lower (on average, 692 km2) estimates of inundation extent than previous studies that used Moderate Resolution Imaging Spectroradiometer (MODIS) and National Oceanic and Atmospheric Administration Advanced Very-High-Resolution Radiometer (NOAA AVHRR) imagery, likely owing to the increased number of mixed pixels that occur when using broad spatial resolution imagery, which can lead to overestimations of the size of inundated areas. We provide the inundation maps and Google Earth Engine code for public use. This classification method can likely be adapted for inundation mapping in other regions.

Highlights

The Okavango Delta in northern Botswana is a wetland of international and domestic significance [1,2,3], yet pressures on its water resources from water abstraction, damming for power generation, and climate change are growing [1,4,5]
Broad spatial resolution imagery increases the number of mixed pixels, and can lead to overestimations of the size of the inundated areas [4,29], which we reduced by using Landsat images
Wolski et al [9] developed a simple method to accurately classify inundation in the Okavango Delta using broad spatial resolution (500 m) satellite imagery, noting the method was suitable for automation, and cautioning that creating inundation maps using Landsat imagery was “laborious . . . making creation of a consistent, long time series of inundation maps difficult”

Summary

Introduction

The Okavango Delta (the delta) in northern Botswana is a wetland of international and domestic significance [1,2,3], yet pressures on its water resources from water abstraction (for agriculture and human consumption), damming for power generation, and climate change are growing [1,4,5] This large wetland consists of a panhandle region; a channel system surrounded by permanent swamps; and a large, low gradient alluvial fan [4,6,7]. The hydrology of the delta, including temporal and spatial changes in its inundation history, has been investigated through inundation maps [1] These maps can be used to study the past and present state of the delta; to predict its future transformations; and to understand how it is affected by natural processes, climate change, and human resource use [13]. As well as its accuracy, the advantage of this method is its relative simplicity, meaning it is automated, which reduces the time (and cost) of implementation compared with more complex methods

Methods

Results

Discussion

Conclusion