Teh Hee Min

Bio: Teh Hee Min is an academic researcher from Universiti Teknologi Petronas. The author has contributed to research in topics: Tide gauge & Shore. The author has an hindex of 1, co-authored 2 publications receiving 7 citations.

Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites

Abstract: Rising sea level is generally assumed and widely reported to be the significant driver of coastal erosion of most low-lying sandy beaches globally. However, there is limited data-driven evidence of this relationship due to the challenges in quantifying shoreline dynamics at the same temporal scale as sea-level records. Using a Google Earth Engine (GEE)-enabled Python toolkit, this study conducted shoreline dynamic analysis using high-frequency data sampling to analyze the impact of sea-level rise on the Malaysian coastline between 1993 and 2019. Instantaneous shorelines were extracted from a test site on Teluk Nipah Island and 21 tide gauge sites from the combined Landsat 5–8 and Sentinel 2 images using an automated shoreline-detection method, which was based on supervised image classification and sub-pixel border segmentation. The results indicated that rising sea level is contributing to shoreline erosion in the study area, but is not the only driver of shoreline displacement. The impacts of high population density, anthropogenic activities, and longshore sediment transportation on shoreline displacement were observed in some of the beaches. The conclusions of this study highlight that the synergistic use of multi-sensor remote-sensing data improves temporal resolution of shoreline detection, removes short-term variability, and reduces uncertainties in satellite-derived shoreline analysis compared to the low-frequency sampling approach.

Long Term and Recent Changes in Sea Level in the Falkland Islands

Abstract: [1] Mean sea level measurements made at Port Louis in the Falkland Islands in 1981–1982, 1984, and 2009, together with values from the nearby permanent tide gauge at Port Stanley, have been compared to measurements made at Port Louis in 1842 by James Clark Ross. The long-term rate of change of sea level is estimated to have been +0.75 ± 0.35 mm/yr between 1842 and the early 1980s, after correction for air pressure effects and for vertical land movement due to glacial isostatic adjustment (GIA). The 2009 Port Louis data set is of particular importance due to the availability of simultaneous information from Port Stanley. The data set has been employed in two ways, by providing a short recent estimate of mean sea level itself, and by enabling the effective combination of measurements at the two sites. The rate of sea level rise observed since 1992, when the modern Stanley gauge was installed, has been larger at 2.51 ± 0.58 mm/yr, after correction for air pressure and GIA. This rate compares to a value of 2.79 ± 0.42 mm/yr obtained from satellite altimetry in the region over the same period. Such a relatively recent acceleration in the rate of sea level rise is consistent with findings from other locations in the Southern Hemisphere and globally.

A new atmospheric proxy for sea level variability in the southeastern North Sea: observations and future ensemble projections

Abstract: Atmosphere–ocean interactions are known to dominate seasonal to decadal sea level variability in the southeastern North Sea. In this study an atmospheric proxy for the observed sea level variability in the German Bight is introduced. Monthly mean sea level (MSL) time series from 13 tide gauges located in the German Bight and one virtual station record are evaluated in comparison to sea level pressure fields over the North Atlantic and Europe. A quasi-linear relationship between MSL in the German Bight and sea level pressure over Scandinavia and the Iberian Peninsula is found. This relationship is used (1) to evaluate the atmospheric contribution to MSL variability in hindcast experiments over the period from 1871–2008 with data from the twentieth century reanalysis v2 (20CRv2), (2) to isolate the high frequency meteorological variability of MSL from longer-term changes, (3) to derive ensemble projections of the atmospheric contribution to MSL until 2100 with eight different coupled global atmosphere–ocean models (AOGCM’s) under the A1B emission scenario and (4) two additional projections for one AOGCM (ECHAM5/MPI-OM) under the B1 and A2 emission scenarios. The hindcast produces a reasonable good reconstruction explaining approximately 80 % of the observed MSL variability over the period from 1871 to 2008. Observational features such as the divergent seasonal trend development in the second half of the twentieth century, i.e. larger trends from January to March compared to the rest of the year, and regional variations along the German North Sea coastline in trends and variability are well described. For the period from 1961 to 1990 the Kolmogorov-Smirnow test is used to evaluate the ability of the eight AOGCMs to reproduce the observed statistical properties of MSL variations. All models are able to reproduce the statistical distribution of atmospheric MSL. For the target year 2100 the models point to a slight increase in the atmospheric component of MSL with generally larger changes during winter months (October–March). Largest MSL changes in the order of ~5–6 cm are found for the high emission scenario A2, whereas the moderate B1 and intermediate A1B scenarios lead to moderate changes in the order of ~3 cm. All models point to an increasing atmospheric contribution to MSL in the German Bight, but the uncertainties are considerable, i.e. model and scenario uncertainties are in the same order of magnitude.

Assessment of the Coastal Vulnerability to the Ongoing Sea Level Rise for the Exquisite Rhodes Island (SE Aegean Sea, Greece)

Abstract: The foreseeable acceleration of global sea level rise could potentially pose a major threat to the natural charm and functional integrity of the world-renowned tourist coastal attractions of Rhodes Island, as a result of the anticipated increasing frequency of flooding and erosion events. Hence, this study aims to determine the most vulnerable segments (in terms of physical impact) of the Rhodes coastline through the widely accepted coastal vulnerability index (CVI), applying a combination of well-known, broadly used approaches and methods. The frequency distribution of the current CVI along the island’s coastline suggests a rather worrying high to very high vulnerability of 40%. In addition, a CVI projection to the end of the 21st century (based on the Intergovernmental Panel on Climate Change predictive scenarios) indicates an enhancement of the total vulnerability by 48%, mainly focused on the majority of the western coastline. Hence, a considerable number of popular coastal destinations in the island shall remain under unignorable threat and, therefore, coastal managers and decision-makers need to hatch an integrated plan to minimize economic and natural losses, private property damage and tourism infrastructure deterioration from flooding and erosion episodes, which will most likely be intensified in the future.

Monitoring Coastline Changes of the Malay Islands Based on Google Earth Engine and Dense Time-Series Remote Sensing Images

Abstract: The use of remote sensing to monitor coastlines with wide distributions and dynamic changes is significant for coastal environmental monitoring and resource management. However, most current remote sensing information extraction of coastlines is based on the instantaneous waterline, which is obtained by single-period imagery. The lack of a unified standard is not conducive to the dynamic change monitoring of a changeable coastline. The tidal range observation correction method can be used to correct coastline observation to a unified climax line, but it is difficult to apply on a large scale because of the distribution of observation sites. Therefore, we proposed a coastline extraction method based on the remote sensing big data platform Google Earth Engine and dense time-series remote sensing images. Through the instantaneous coastline probability calculation system, the coastline information could be extracted without the tidal range observation data to achieve a unified tide level standard. We took the Malay Islands as the experimental area and analyzed the consistency between the extraction results and the existing high-precision coastline thematic products of the same period to achieve authenticity verification. Our results showed that the coastline data deviated 10 m in proportion to a reach of 40% and deviated 50 m within a reach of 89%. The overall accuracy was kept within 100 m. In addition, we extracted 96 additional islands that have not been included in public data. The obtained multi-phase coastlines showed the spatial distribution of the changing hot regions of the Malay Islands’ coastline, which greatly supported our analysis of the reasons for the expansion and retreat of the coastline in this region. These research results showed that the big data platform and intensive time-series method have considerable potential in large-scale monitoring of coastline dynamic change and island reef change monitoring.

Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

Abstract: Estuarine degradation is a major concern worldwide, and is rapidly increasing due to anthropogenic pressures. The Mediterranean Guadiaro estuary, located in San Roque (Cadiz, Spain), is an example of a highly modified estuary, showing severe negative effects of eutrophication episodes and beach erosion. The migration of its river mouth sand spit causes the closure of the estuary, resulting in serious water quality issues and flora and fauna mortality due to the lack of water renewal. With the aim of studying the Guadiaro estuary throughout a 4-year period (2017–2020), the Sentinel-2 A/B twin satellites of the Copernicus programme were used thanks to their 5-day and 10 m temporal and spatial resolution, respectively. Sea–land mapping was performed using the Normalized Difference Water Index (NDWI) in the Google Earth Engine (GEE) platform, selecting cloud-free Sentinel-2 Level 2A images and computing statistics. Results show a closure trend of the Guadiaro river mouth and no clear sand spit seasonal patterns. The study also reveals the potential of both Sentinel-2 and GEE for estuarine monitoring by means of an optimized processing workflow. This improvement will be useful for coastal management to ensure a continuous and detailed monitoring in the area, contributing to the development of early-warning tools, which can be helpful for supporting an ecosystem-based approach to coastal areas.