SCShores: A comprehensive shoreline dataset of Spanish sandy beaches from a citizen-science monitoring programme

Sandy beaches are ever-changing environments, as they experience constant reshaping due to the external forces of tides, waves, and winds. The shoreline position, which marks the boundary between water and sand, holds great significance in the fields of coastal geomorphology, coastal engineering, and coastal management. It is crucial to understand how beaches evolve over time, but high-resolution shoreline datasets are scarce, and establishing monitoring systems can be costly. To address this, we present a new dataset of the shorelines of five Spanish sandy beaches located in contrasting environments that is derived from the CoastSnap citizen-science shoreline monitoring programme. The use of citizen science within environmental projects is increasing, as it allows both community awareness and the collection of large amounts of data that are otherwise difficult to obtain. This dataset includes a total of 1721 individual shorelines composed of 3 m spaced points alongshore, accompanied by additional attributes, such as elevation value and acquisition date, allowing for easy comparisons. Our dataset offers a unique perspective on how citizen science can provide reliable datasets that are useful for management and geomorphological studies

SCShores: a comprehensive shoreline dataset of Spanish sandy beaches from a citizen-science monitoring programme

Sandy beaches are ever-changing environments, as they experience constant reshaping due to the external forces of tides, waves, and winds. The shoreline position, which marks the boundary between water and sand, holds great significance in the fields of coastal geomorphology, coastal engineering, and coastal management. It is crucial to understand how beaches evolve over time, but high-resolution shoreline datasets are scarce, and establishing monitoring systems can be costly. To address this, we present a new dataset of the shorelines of five Spanish sandy beaches located in contrasting environments that is derived from the CoastSnap citizen-science shoreline monitoring programme. The use of citizen science within environmental projects is increasing, as it allows both community awareness and the collection of large amounts of data that are otherwise difficult to obtain. This dataset includes a total of 1721 individual shorelines composed of 3 m spaced points alongshore, accompanied by additional attributes, such as elevation value and acquisition date, allowing for easy comparisons. Our dataset offers a unique perspective on how citizen science can provide reliable datasets that are useful for management and geomorphological studies. The shoreline dataset, along with relevant metadata, is available at https://doi.org/10.5281/zenodo.8056415 (González-Villanueva et al., 2023b).</p

SCShores: a comprehensive shoreline dataset of Spanish sandy beaches from a citizen-science monitoring programme

Sandy beaches are ever-changing environments, as they experience constant reshaping due to the external forces of tides, waves, and winds. The shoreline position, which marks the boundary between water and sand, holds great significance in the fields of coastal geomorphology, coastal engineering, and coastal management. It is crucial to understand how beaches evolve over time, but high-resolution shoreline datasets are scarce, and establishing monitoring systems can be costly. To address this, we present a new dataset of the shorelines of five Spanish sandy beaches located in contrasting environments that is derived from the CoastSnap citizen-science shoreline monitoring programme. The use of citizen science within environmental projects is increasing, as it allows both community awareness and the collection of large amounts of data that are otherwise difficult to obtain. This dataset includes a total of 1721 individual shorelines composed of 3 m spaced points alongshore, accompanied by additional attributes, such as elevation value and acquisition date, allowing for easy comparisons. Our dataset offers a unique perspective on how citizen science can provide reliable datasets that are useful for management and geomorphological studies. The shoreline dataset, along with relevant metadata, is available at https://doi.org/10.5281/zenodo.8056415Agencia Estatal de Investigación | Ref. PID2019-109143RB-I00Fundación Española para la Ciencia y la Tecnología | Ref. FCT-20-15835Xunta de GaliciaUniversidad de Cádiz | Ref. PR2019-02

Guidance note on the application of coastal monitoring for small island developing states : Part of the NOC-led project “Climate Change Impact Assessment: Ocean Modelling and Monitoring for the Caribbean CME states”, 2017-2020; under the Commonwealth Marine Economies (CME) Programme in the Caribbean.

Small Island Developing States (SIDS) are a diverse group of 51 countries and territories vulnerable to human-induced climate change, due to factors including their small size, large exclusive economic zones and limited resources. They generally have insufficient critical mass in scientific research and technical capability to carry out coastal monitoring campaigns from scratch and limited access to data. This guidance report will go some way to addressing these issues by providing information on monitoring methods and signposting data sources. Coastal monitoring, the collection, analysis and storage of information about coastal processes and the response of the coastline, provides information on how the coast changes over time, after storm events and due to the effects of human intervention. Accurate and repeatable observational data is essential to informed decision making, particularly in light of climate change, the impacts of which are already being felt. In this report, we review the need for monitoring and the development of appropriate strategies, which include good baseline data and long-term repeatable data collection at appropriate timescales. We identify some of the methods for collection of in situ data, such as tide gauges and topographic survey, and highlight where resources in terms of data and equipment are currently available. We then go on to explore the range of remote sensing methods available from satellites to smart phone photography. Both in situ and remotely sensed data are important as inputs into models, which in turn feed in to visualisations for decision-making. We review the availability of a wide range of datasets, including details of how to access satellite data and links to international and regional data banks. The report concludes with information on the use of Geographical Information Systems (GIS) and good practice in managing data

O uso de geotecnologias para análise da variabilidade temporal da linha de costa do arco praial Pântano do Sul - Açores, ilha de Santa Catarina, SC

TCC(graduação) - Universidade Federal de Santa Catarina. Centro de Físicas e Matemáticas. OceanografiaThe coastline is naturally a mobile feature, reflecting several natural and anthropic processes. Monitoring the coastline is a key activity for understanding coastal processes, providing basic data that support planning and coastal management. In this sense, technological advances in research tools and analysis methods have enabled a diversification of coastal monitoring. Coastline variations occur on several time scales, in the short, medium, and long term. The tools CoastSat and CoastSnap were used to obtain and analyze the variation of the coastline of the beach arc Pântano do Sul - Açores, between 1986 and 2021. CoastSnap, a citizen science approach, consists of a method for mapping the coastline using photographs taken by beach visitors using their cell phones, which are then shared on social media or sent to e-mail addresses. A structure was built to support the cell phone, low cost and easy to install, to standardize the angle at which the photos are taken, and to guide the user-participants in sharing them. Subsequently, the images are rectified and the coastline mapped. CoastSat is a set of tools enabled by the Google Earth Engine (GEE) to extract coastlines from available satellite images. In this work, images from Landsat 5, Landsat 8, and Sentinel-2 were used. Since the images are collected at random stages of the tidal cycle, a 0.1 m range of variation between the mean sea level over the study period was set for direct comparison of the collected beach width, trend calculation, in different images at a similar sea level range. The maximum shoreline variation was calculated as the difference between the maximum and minimum limits between the shorelines. The greatest variation in beach width obtained by CoastSnap occurred between February 14, 2019, and March 03, 2020, was quantified in the order of 50 m, showing a trend of increasing width in the order of +0.05 m/month. The shorelines extracted by CoastSat, for the period between January 10, 2019, and August 02, 2020, obtained a maximum shoreline variation of 75 m, and the trend of beach width of - 0.82 m/month. For the period between 2013 and 2020, the maximum variation of the coastline was 80 m, while the trend of beach width variation, from northeast to southwest, reached the values of -4.3 m/year, -3.96 m/year, -3.96 m/year, -2.88 m/year, and -1.44 m/year. The 35-year analysis obtained a maximum shoreline variation of 80 m while the beach width trend was -0.7 m/yr, -0.6 m/yr, -0.4 m/yr, -0.1 m/yr, +0.2 m/yr along the beach arc, indicating a lower erosional trend in the northeastern sector of the beach arc. The values found indicate that the choice of different time scales has a direct influence on the values of erosion rates. The erosion rates found among the analyzed periods showed that the magnitude of the identified trend values intensifies the smaller the time scale is. The geotecnologies showed to be efficient and promising for shoreline variability analysis.A linha de costa é uma feição naturalmente móvel, reflexo de diversos processos naturais e antrópicos. O monitoramento da linha de costa é uma atividade primordial para a compreensão acerca dos processos costeiros fornecendo dados básicos que servem de suporte ao planejamento e ao gerenciamento costeiro. Nesse sentido, avanços tecnológicos em instrumentos de pesquisa e métodos de análise possibilitaram uma diversificação acerca do monitoramento costeiro. As variações da linha de costa ocorrem em diversas escalas temporais, em curto, médio e longo termo. As ferramentas CoastSat e CoastSnap foram utilizadas para a obtenção e análise da variação da linha de costa do arco praial Pântano do Sul - Açores, entre 1986 e 2021. O CoastSnap, uma abordagem de ciência cidadã, consiste em um método de mapeamento da linha de costa utilizando fotografias obtidas por visitantes da praia através de seus aparelhos celulares, sendo posteriormente compartilhadas em mídias sociais ou enviadas para endereços eletrônicos. Foi construída uma estrutura para apoio do celular, de baixo custo e fácil instalação, a fim de padronizar o ângulo de tomada das fotos e orientar os usuários-participantes quanto ao compartilhamento das mesmas. Posteriormente, é feita a retificação das imagens e o mapeamento da linha de costa. Já o CoastSat é um conjunto de ferramentas habilitado com o recurso Google Earth Engine (GEE) para extrair linhas de costa a partir de imagens disponíveis de satélites. Neste trabalho, foram utilizadas imagens do Landsat 5, Landsat 8 e Sentinel-2. Uma vez que as imagens são coletadas em estágios aleatórios do ciclo das marés, foi definido um intervalo de variação de 0,1 m entre o nível médio do nível do mar ao longo do período de estudo para a comparação direta da largura de praia coletada, cálculo de tendência, em diferentes imagens num intervalo semelhante de nível do mar. A máxima variação da linha de costa foi calculada como a diferença entre os limites máximos e mínimos entre as linhas de costa. A maior variação da largura da praia, obtida pelo CoastSnap ocorreu entre 14 de fevereiro de 2019 e 03 de março de 2020, foi quantificada na ordem de 50 m, apresentando uma tendência de aumento da largura na ordem de +0,05 m/mês. As linhas de costa extraídas pelo CoastSat, para o período entre 10 de janeiro de 2019 e 02 de agosto de 2020, obtiveram uma variação máxima da linha de costa de 75 m, e a tendência da largura da praia de - 0,82 m/mês. Já para o período entre 2013 e 2020 a variação máxima da linha de costa foi de 80 m, enquanto a tendência de variação da largura da praia, de nordeste para sudoeste, atingiu os valores de -4,3 m/ano, -3,96 m/ano, -3,96 m/ano, -2,88 m/ano e -1,44 m/ano. A análise de 35 anos obteve uma variação máxima da linha de costa de 80 m enquanto que a tendência da largura da praia foi de -0,7 m/ano, -0,6 m/ano, -0,4 m/ano, -0,1 m/ano, +0,2 m/ano ao longo do arco praial, indicando uma menor tendência erosional no setor nordeste do arco praial. Os valores encontrados indicam que a escolha de diferentes escalas temporais tem influência direta nos valores das taxas de erosão. As taxas de erosão encontradas entre os períodos analisados mostraram que a magnitude dos valores de tendência identificados se intensifica quanto menor a escala temporal. As ferramentas se mostraram eficientes e promissoras para a análises de variabilidade da linha de costa

Understanding coastal social values through citizen science: The example of Coastsnap in Western Australia

The coast is socially, economically, and environmentally vital to humanity, yet at risk due to population growth, development, and climate change. Coastal managers are required to make complex decisions regarding the trade-offs that may arise because of these threats, hence evidence-based policy is essential. Advances in biophysical data have improved understanding of coastal change, yet comparative social data is limited. Innovations are required to generate social values data that: (i) links with biophysical data; (ii) is consistent, representative, and long-term; and (iii) requires low resource investment. This paper reports on a pilot program that sought to address these needs by linking with an established citizen science program, CoastSnap, to collect information on community use and values in the Peron Naturaliste region, south-west Western Australia. The program successfully monitored community use and values uncovering the importance of nature-based activities and the mental/emotional health benefits of interacting with the coast. It highlights spatial differences in use and value that can support regional coastal planning. In the longer-term, the approach could enable decision-makers to monitor change in use and values resulting from, for example, infrastructure investments or physical coastal change. Limitations include little control over respondent sample and lack of knowledge regarding barriers to participation. Further research into the factors that motivate users and their preferences for interacting with the remote survey technologies, along with an expanded network of CoastSnap Social Survey sites, would facilitate regional, national, and global comparison of use and values. The approach provides a valuable addition to coastal managers’ data collection toolbox, generating social data that are temporal, integrates with biophysical data, and supports regional coastal planning, whilst increasing opportunities to interact with the public to enhance awareness, interest and support for coastal management

How effective is the community science initiative CoastSnap, and what are the barriers to engagementin Christchurch, New Zealand?

The Christchurch City Council has implemented the community science initiative CoastSnap to aid in both the collection of shoreline monitoring data and to help increase engagement and education around coastal processes and hazards in the community. This research assesses community awareness and understanding of coastal processes and hazards, the effectiveness of the CoastSnap project, and the barriers to engagement with the CoastSnap project. This aims to gain a better understanding of the current awareness in the community and determine how participation in community science could be made more effective in the future by overcoming different barriers. The assessment was carried out using an in-person survey conducted at New Brighton and Taylors Mistake in Christchurch, New Zealand. It was found that overall community awareness and understanding of coastal processes and hazards in survey respondents was higher than the national average. Most people agree or strongly agree that climate change will affect the area in 50to100 years which aligns with global and national beliefs that the climate is changing and that itis a top global threat, however, this did vary depending on some demographic factors, peoples past knowledge and motivations to learn and teach. The effectiveness of the CoastSnap project was tested throughout five different categories. It was seen that effectiveness within these categories depended on participants’ awareness of the existence of the project, gender, age, lifestyle, past engagement, and motivations to learn. The main barriers to participation were seen to be a lack of knowledge of the existence of the project, a lack of interest in CoastSnap, the perception that it may be too hard, the lack of a device to take pictures on, and a lack of time to contribute. Awareness and participation could be increased through more targeted advertising and engagements, making the photo points more visually appealing, and showing people the direct impact of their images

Análise do comportamento da porção sul da praia do Morro das Pedras, Florianópolis, SC, através do CoastSnap

TCC (graduação) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas, Oceanografia.As praias arenosas oceânicas são ambientes dinâmicos, continuamente moldados por processos hidrodinâmicos e influenciados por atividades humanas, como urbanização e obras costeiras, que impactam significativamente esses sistemas. Este estudo analisou a variabilidade costeira entre 2022 a 2024, no extremo sul da praia do Morro das Pedras, Florianópolis (SC). A metodologia combina o uso do CoastSnap, um projeto de ciência cidadã que investiga a dinâmica da linha de costa com imagens coletadas pela população e a análise de dados de ondas (direção, altura e período). Adicionalmente, o CoastSat, uma ferramenta de código aberto com imagens de satélite, foi usado para determinar variações na linha de costa e integrar dados com o CoastSnap avaliando a correlação de Pearson entre os conjuntos de dados. Também foram avaliadas as evidências de geoindicadores de erosão costeira para identificar os setores mais suscetíveis a tendência erosiva de largura de praia, bem como, a presença de escarpas sazonalmente como indicador de processo erosivo. Como resultado observou-se que as maiores frequências de direções de ondas foram de Leste e Sudeste, no inverno comparativo entre 2022 e 2023, percebeu-se que no inverno de 2022, as ondas predominantes foram Sul e Sudeste, resultando em maior erosão de largura da praia em comparação com 2023, que teve ondas predominantes Leste e Sul. Na primavera de 2022, as ondas predominantes foram Leste e Sudeste, e em 2023, também predominou Leste, com menor frequência de Sudeste e menores alturas de ondas, além de uma praia mais larga. No outono de 2023, as ondas foram principalmente Sudeste e Sul, enquanto em 2024, as direções das ondas foram mais variadas e a praia mais larga. No verão, houve uma predominância de ondas Leste em 2022 e Sudeste e Sul em 2023, explicando o aumento da largura da praia em 2023. A análise geral da linha de costa mostrou uma tendência acrescional geral de +1,95m/ano. Os padrões das ondas e sua direção influenciaram a dinâmica da linha de costa, com direções predominantes Sul e Sudeste associadas a maiores períodos de ondas e energia. A comparação entre os dados de CoastSat e CoastSnap mostrou um coeficiente de Correlação de Pearson (r) de 0.76 indicado com uma correlação positiva forte. A presença de escarpas variou com as condições energéticas e intervenções antrópicas apresentando maior tendência erosiva no setor mais ao sul da praia.Ocean sandy beaches are dynamic environments continuously shaped by hydrodynamic processes and influenced by human activities such as urbanization and coastal engineering, which significantly impact these systems. This study analyzed coastal variability between 2022 and 2024 at the southernmost stretch of Morro das Pedras beach, Florianópolis (SC). The methodology combines the use of CoastSnap, a citizen science project investigating shoreline dynamics through images collected by the public, with wave data analysis (direction, height, and period). Additionally, CoastSat, an open-source tool using satellite imagery, was employed to determine shoreline variations and integrate data with CoastSnap by evaluating the Pearson correlation between the datasets. Coastal erosion geoindicators were also assessed to identify the most erosion-prone beach sectors, along with the seasonal presence of scarps as indicators of erosive processes. Results revealed that the highest wave direction frequencies were from East and Southeast during the winters of 2022 and 2023. In the winter of 2022, predominant waves from South and Southeast caused greater beach width erosion compared to 2023, when waves were primarily from East and South. During spring 2022, the predominant waves were from East and Southeast, while in 2023, East predominated, with lower Southeast frequencies and smaller wave heights, resulting in a wider beach. In the autumn of 2023, waves were mainly Southeast and South, whereas in 2024, wave directions were more varied, accompanied by a wider beach. During the summer, East waves predominated in 2022, while Southeast and South waves dominated in 2023, explaining the increased beach width in 2023. Overall shoreline analysis indicated a general accretion trend of +1.95 m/year. Wave patterns and directions influenced shoreline dynamics, with South and Southeast directions associated with longer wave periods and higher energy. The comparison between CoastSat and CoastSnap data showed a strong positive Pearson correlation coefficient (r) of 0.76. The presence of scarps varied according to energetic conditions and anthropogenic interventions, with the southernmost sector of the beach showing a greater erosive tendency