1. INTRODUCTION
'Where the Land meets the Sea...'
This phrase has a distinct poetic connotation - it invoked the memory of a pristine beach for me - perhaps for you too, just as well.
Where does the Land actually meet the Sea, though?
The exact spot is called the Shoreline and its position and shape is in a continuous state of flux -influenced by Natural factors such as Waves, Winds and Currents as well as Anthropogenic factors such as Coastal Infrastructure Development, Sand Mining and other human causes. A way to categorize the natural influencers is based on their temporal (time) characteristics - for example, Tides occur daily and are cyclical in nature, a Storm Surge is a sporadic phenomenon, and the effects of Transgression (rise in sea level due to melting glaciers etc.) becomes evident over a longer time horizon. Together, these contribute to the dynamic nature of the coast.
The photo of Gibson Beach above was captured during Low Tide - the illustration below depicts a basic anatomy of a coastal environment.
"Some 37 per cent of the world's population lives within 100 kilometers of the coast, at a population density twice the global average" - United Nations Environment Programme
Coupled with the growing threat from Coastal Erosion (loss of coastal sediments to the sea) and Marine Transgression (rise in sea level due to climate change among other factors), this aspect (population density) is what triggers the need for regular and accurate monitoring of the shoreline position as well as its evolution over time.
India, by virtue of having 7000+ kilometers of coastline (18th longest in the world), also conducts extensive research in this field spearheaded by the National Centre for Coastal Research under Ministry of Earth Sciences. Here's a snippet -
"(Based on Shoreline Change Surveys done from 1990-2018), it is observed that 33.6% of the Indian Coastline was vulnerable to erosion, 26.9% was under accretion (growing) and 39.6% was in stable state" - Press Information Bureau (PIB) Media Release in December 2023
Besides sharing India-specific data, through this release I also wanted to highlight an interesting aspect which the readers of this article should become aware of-
Q. The terms Shoreline and Coastline are often used interchangeably. Are they one and the same?
A. No, they aren't.
It took me a while to figure this out but here's what I've understood - while the exact definition could vary from country to country, there are two distinct interpretations of the word Coastline - one is the geopolitical version and the other is the geological version. The 'geopolitical' coastline is the predetermined boundary of a nation / region located adjacent to a water body (do not confuse this with a nation's maritime boundary). The Indian Ministry's use of the word Coastline in the media release above is in the geopolitical context.
Just in case you are wondering, I presume that the precise location of this 'geopolitical' Coastline is demarcated from the Littoral Zone boundary i.e. the edge of the Nearshore / the end of the Continental Plate - labelled as Low-tide breaker line in Figure 1 above.
The 'geological' interpretation of Coastline is distinctly different - refer the more detailed Beach Anatomy diagram below -
An easy way to grasp this is while a Shoreline is where the Sea meets the Shore, the Coastline is, geologically speaking, where the Shore meets the Land. Just in case you are wondering, distinguishing Shore from Land is straightforward - a shore comprises of Sand - formed from the deterioration of rocky structures upon millennia of action by waves and winds - and / or other accumulated Coastal Sediments - deposited by the sea via its Currents and Tides (difference between the two simply explained here).
What should strike you, however, is that in neither of these two interpretations - geopolitical or geological - does the definition of Coastline match the definition of Shoreline. This delineation is important to understand - because while both are often used interchangeably casually, all scientific references pertaining to the detection of the precise location where the land meets the sea (technically the 'physical interface of land and water' - Dolan et al., 1980) that I've come across involves the use of the word Shoreline only and not of Coastline. You may re-read the Ministry of Earth Sciences' Media Release snippet above once again if you'd like...😉.
Hence, this article is about 'Shoreline' Delineation & Monitoring.
SECTION HYPERLINKED TABLE OF CONTENTS
1. Introduction
2. Scope
Video 1: Shoreline Monitoring, Delineation & Measurement using Remote Sensing (All 7 Combined)
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2. SCOPE
As it turns out, there are multiple ways to detect / estimate Shorelines - from Photographs, Drone Imagery, Beach Surveys, Vehicle-mounted GPS, Remote Sensing, and more.
Some of the major aspects to consider while selecting an appropriate method are - desired spatial & temporal resolution, data frequency & accuracy needs, and the cost of acquiring and processing data.
In this article, I'll present seven video walkthroughs on some of the ways in which Satellite-based Remote Sensing can be, and is being used, to detect Shorelines and monitor its evolution through a passage of time. The techniques range from rudimentary monitoring using Google Earth to more technical shoreline extraction methods such as Radar Reflectance Thresholding, NDVI+Tasseled Cap transformation, SAET and EPR4Q algorithms. While this is not an exhaustive list, it is diverse in terms of methodology. I've use two sources of Satellite imagery - Landsat (NASA, USA) & Sentinel (ESA, Europe) - both have a spatial and temporal coverage suitable for Earth Observation purposes and are commonly used by researchers for a variety of related workflows.
Besides knowledge-sharing with enthusiasts, through my work I hope to encourage the adoption of Open-Source Intelligence. Given the diversity and magnitude of Climate Change-related threats that we face today, it is imperative that there are aware, informed and trained personnel who can keep an eye on the developments and even pre-empt disasters.
2.1 Viewing Shoreline Evolution Using Google Earth
Area of Interest: Someswar - Batapady Beach (South-West India)
This technique entails using Google Earth - Google's Satellite Imagery rendering platform - to visually monitor the Shoreline through time using the Historical Optical Imagery feature available on its platform. Additionally, the basic Measurement tool in the software aids in obtaining an estimate about the rate of erosion / accretion too.
While being just a rudimentary technique, it does give a quick, macro-level perspective about the state and evolution of shoreline for a given Area of Interest. I was able to ascertain which stretches of the Someswar - Batapady coast alongside the Arabian Sea were ravaged by erosion over a period of time. Google also has an advanced imagery processing platform of its own - Google Earth Engine - but I've not demonstrated it in this series.
Video 2: Viewing Shoreline Evolution using Historical Optical Imagery tool on Google Earth
(V1 of 7)
TIMESTAMPS:
00:00 - Video #.1 Headline
00:04 - 1.1 Exploring the Area of Interest on Google Maps
02:30 - 1.2 Visually monitoring the Shoreline using Google Earth Pro
2.2 Viewing Shoreline Evolution Using EO Browser
Area of Interest: Marina Beach, Chennai - Tamil Nadu (South-East India)
EO Browser surpasses Google Earth for Shoreline Monitoring on a few counts, namely - a) it has a steady stream of historical imagery from a variety of sources to choose from, b) it allows for on-the-fly Cloud Processing with preset and custom Band Combinations and c) it has handy tools such as Histogram and Time-Lapse Video Creation which allows for appropriate thresholding and better visualization. These allowed me to clearly observe when the Adyar river was blockaded (Accretion) by the Marina beach over a period of time which prevented the water pollution inland to drain and dilute into the Bay of Bengal.
Video 3: Viewing Shoreline Evolution from Time-Lapse Video of Water Indexed Sentinel-2 Optical Imagery using EO Browser. (V2 of 7)
TIMESTAMPS:
00:00 - Video #.2 Headline
00:04 - 2.1 Exploring Area of Interest and Band Combinations on EO Browser
02:48 - 2.2 Creating a Time-Lapse Video of the Area of Interest using EO Browser
2.3 Extracting Shoreline by Thresholding Radar Reflectances
Area of Interest: Visakhapatnam / Vizag - Andhra Pradesh (South-East India)
While the previous two workflows allowed me to visually monitor shorelines from online satellite imagery and observe its evolution through time, this is the first workflow where I've demonstrated the actual 'extraction' / 'delineation' of a shoreline from downloaded Raw Satellite Imagery. The Area of Interest - the popular tourist destination of Visakhapatnam - is home to several beaches that have undergone rampant erosion in the recent past thereby impacting footfall.
Radar Imagery (SAR) has a couple of notable advantages over Optical Imagery - it has an active electromagnetic emitter which allows a) the satellite to obtain readings even in zero-light conditions such as during night-time and b) the longer wavelengths it emits bypasses clouds and rain, thereby allowing the satellite to remain unaffected by weather conditions and obtain accurate readings of the surface features. However, this technique suffers from limitations such as low spatial resolution of SAR imagery and outdated DEMs which make it difficult to mask out water pixels and delineate the shoreline. Nonetheless, this method can be combined with other shoreline extraction techniques that involve the use of Optical Imagery for better validation.
Video 4: Extracting Shoreline by using Thresholding technique on Sentinel-1 Radar Imagery on SNAP (V3 of 7)
TIMESTAMPS:
00:00 - Video #.3 Headline
00:04 - 3.1 Exploring Area of Interest using Google Maps
03:08 - 3.2 Downloading SAR (Synthetic Aperture Radar) Imagery using Copernicus Browser
08:48 - 3.3 Post-Processing the Raw Radar Imagery using SNAP Software
25:25 - 3.4 Post-Processing the SNAP-processed Radar Imagery using ArcGIS Pro
2.4 Extracting Shoreline by using Water Radiometric Index
Area of Interest: Anjuna - Goa (South-West India)
Out of the 41 beaches surveyed by National Centre for Sustainable Coastal Management (NCSCM) in the popular beach state of Goa, 21 beaches, including my selected Area of Interest - Anjuna Beach, were found to be suffering from sand erosion.
How the electromagnetic spectrum, in particular visible light, interacts with objects (spectral signature) is the defining characteristic deployed in Remote Sensing to differentiate one surface feature from the other and it is no different when it comes to Shoreline delineation. Water has a low reflectance percentage in Visible Light range and an almost zero reflectance in Near Infrared range (NIR), for example. This is in stark contrast to Vegetation & Soil - both of which have a very high reflectance percentage in NIR. Hence, a particular type of Water Index - Modified Normalized Difference Water Index (MNDWI) in this instance - has been used to demarcate Land from Sea thereby making it possible to extract the shoreline from Optical Imagery over different timelines. Because Optical Imagery relies on passive source of illumination - Sunlight - it is important to select cloud-free satellite images, especially over the Area of Interest, in order to perform the imagery post-processing accurately.
Video 5: Extracting Shoreline by using a Water Radiometric Index on Sentinel-2 Optical Imagery using SNAP (V4 of 7)
TIMESTAMPS:
00:00 - Video #.4 Headline
00:04 - 4.1 Exploring Area of Interest and Band Combinations on EO Browser
06:48 - 4.2 Downloading Optical Imagery from Copernicus Browser
10:13 - 4.3 Post-Processing the Raw Optical Imagery using SNAP Software
24:15 - 4.4 Post-Processing the SNAP-processed Optical Imagery on ArcGIS Pro
35:59 - 4.5 Determining Land-Sea Threshold using EO Browser
2.5 Extracting Shoreline by using Vegetation Index + Tasseled Cap transformation technique
Area of Interest: Anjuna - Goa (South-West India)
Just as water features were first identified and then subsequently the edge where it met non-water features was demarcated as the shoreline in the previous workflow, a similar logic albeit with an opposing method has been used in this workflow. Here, a Vegetation Index - Normalized Difference Vegetation Index (NDVI) - has been used to identify non-water features and subsequently the edge where it meets water features has been demarcated as the shoreline. I've deliberately kept the Area of Interest the same - Anjuna and its surroundings in Goa - in both these workflows as well as tried to keep the timeline of Imagery Acquisition similar - this allowed me to compare the output from both the methods (Water and Vegetation Index) and draw some interesting insights! Check out the video below-
Video 6: Extracting Shoreline by using Vegetation Index + Tasseled Cap transformation on Landsat 8 Optical Imagery using ArcGIS Pro (V5 of 7)
TIMESTAMPS
00:00 - Video #.5 Headline
00:04 - 5.1 Landsat 8 vs Sentinel-2 Optical Imagery
01:44 - 5.2 Downloading Landsat 8 Imagery from USGS Earth Explorer
07:20 - 5.3 Deploying NDVI+Tasseled Cap technique using Landsat toolbox on ArcGIS Pro
27:28 - 5.4 Visualizing Landsat 8-derived shoreline on Google Earth and comparing it with the Sentinel 2-derived shoreline
2.6 Automatic Extraction of Shoreline using SAET algorithm and performing Change Analysis
Area of Interest: Satabhaya - Odisha (East India)
If you've seen the previous videos, you'd know how tedious it could sometimes be to extract Shoreline from Satellite Imagery - particularly if the coast is not linear. Moreover, the landscape around the shore is dynamic and ever-evolving - a complex interplay of factors such as tides, waves, floods, winds and shape of the beach sometimes makes it difficult to extract a contiguous agglomeration of edge pixels or line segments which one can demarcate as 'shoreline'.
The Shoreline Analysis and Extraction tool - SAET - developed by European Coastal Flood Awareness System (ECFAS) and released only recently in July 2023 is a blessing in this regard. Not only is the method of Optical Imagery search, download and processing 'automated' but also the resulting shoreline extracted is 'contiguous' over the Area of Interest as it should be. The erosion-ravaged Satabhaya region in the eastern Indian state of Odisha has a tricky terrain - rugged coast with floods and tiny water bodies interspersed with the landmass. But the SAET algorithm proved to be a boon and was able to process the imagery and extract a contiguous shoreline in a matter of minutes.
While setting up SAET could be complicated for the first time, you'll surely find using it a breeze!
This is the first time where I have demonstrated Shoreline Change Analysis as well. Have a look-
Video 7: Automated Shoreline Extraction using ECFAS' SAET algorithm on Landsat 8 Optical Imagery and Temporal Change Analysis (V6 of 7)
TIMESTAMPS
00:00 - Video #.6 Headline
00:04 - 6.1 Getting to know and preparing the SAET tool
10:54 - 6.2 Downloading Landsat 8 Optical Imagery for Area of Interest using SAET tool
16:02 - 6.3 Extracting Shoreline from Downloaded Landsat 8 Imagery using SAET
19:26 - 6.4 Observing the extracted shoreline on ArcGIS Pro
20:41 - 6.5 Using Google Earth Pro to validate the accuracy of the extracted shoreline
23:39 - 6.6 Using the Raw Landsat 8 Imagery itself to validate the accuracy of the extracted shoreline 28:16 - 6.7 Quantitative Analysis of Temporal Shoreline Movement using QGIS
49:51 - 6.8 Symbolizing Results on ArcGIS Pro
2.7 Granular Shoreline Change Analysis and Forecasting using EPR4Q Model
Area of Interest: Satabhaya - Odisha (East India) and Juhu Beach, Mumbai - Maharashtra (West India)
The End Point Rate Tool for QGIS (EPR4Q) has been developed by Dr. Lucas Terres de Lima and his researcher colleagues at CESAM—Centre for Environmental and Marine Studies, Department of Geoscience, University of Aveiro in Portugal. It has been technically validated and stacks favorably when compared to DSAS and AMBUR - two highly technical and popular methods for performing Research-grade Shoreline Change Analysis. As admitted by Dr. Lima himself in one of our conversations, he did not get a chance to develop the model further after performing his initial research - hence the model does not work well on recent QGIS software versions. Nonetheless, I've outlined the preparatory aspects that one must consider while using Dr. Lima's model, in the video.
While I had performed Quantitative Analysis on the Satabhaya shoreline in my previous workflow, I was left highly impressed by the granularity of the output over the same Area of Interest using the EPR4Q model which is based on the principle of casting numerous evenly-spaced Transects over the selected region and subsequently measuring the distance between the shoreline and baseline. The model, like other popular research-grade Shoreline Change Analysis tools, has trouble generating high-quality output for 'embayed' / curved shorelines - there are workarounds though which I've elaborated in the latter half of the video below - the popular Juhu Beach in Mumbai, India is a typical example of an embayed shoreline which I grappled with for several days which eventually led me to contact Dr. Lima who was kind enough to advise workarounds to deal with the situation.
Give EPR4Q a try!
Video 8: Granular Temporal Shoreline Change Analysis and Forecasting using EPR4Q tool on QGIS. (V7 of 7)
TIMESTAMPS
00:00 - Video #.7 Headline
00:04 - 7.1 Rewinding the previous six workflows
05:31 - 7.2 Overview of some of the Advanced Tools for Quantitative Analysis of Temporal Shoreline Movement
08:10 - 7.3 Introducing EPR4Q tool for Temporal and Predictive Shoreline Analysis and Prerequisites to run the tool without errors
18:31 - 7.4 Running the EPR4Q model on QGIS and Interpreting the results over the Area of Interest on ArcGIS Pro
36:18 - 7.5 Challenges faced while running EPR4Q tool over Embayed Shorelines and how to address it
3. Concluding Remarks
What eventually turned out as a detailed Video Series on Shoreline Detection and Monitoring actually began as a research endeavor in Coastal Erosion a couple of years ago. But I put the project on the backburner due to lack of suitable output and storyline, other projects taking centerstage, besides a myriad of reasons. Only around four months ago, after weeks of material-scouring, did I finally feel confident in my ability to weave a compelling narrative on the topic of Shoreline Delineation and Monitoring. If I had a chance to restart this project, I would ensure that the temporal analysis would be comparable across the timelines selected - for that to happen, I'd have to have a better understanding of the Tidal System. Currently, I've ignored this aspect and selected imagery six months or a year apart in most workflows.
I do realize that it is taking me half-a-year or so to come up with new content, but I do believe that the output is qualitatively richer than before. That being said, it has dawned on me that I have added ONE MORE article related to Water Research. It was not exactly deliberate though as I had began with the intention to add a piece in the Remote Sensing category as it has been quite sometime since I did my OSINT stuff in this space - but it was meant to end up in Water Research just as well!
I am happy that my work is being accessed by students, researchers and enthusiasts around the globe and I do try to address all queries on email and YouTube comments as soon as possible / as soon as it comes to my attention. Climate Change and Earth Observation are macro-level Operations problems that are close to my heart and I'll be happy to collaborate with individuals and institutes in this space trying to remedy Human response to Nature before it becomes irretrievable.
Below is my / my firm's full-range of capabilities in the 'Mapping for Operations' space - I encourage you to review it and share it among your network. Thank you.
Article & Video Credits: RUS Copernicus, NASA USGS, GeographyRealm, Esri ArcGIS Pro, QGIS, ESA SNAP, ECFAS, Dr. Lucas Terres De Lima besides several other individual researchers, organizations and institutes who have contributed towards development of shoreline models.