Google Earth Engine Application on CoastSat for Shoreline Extraction DOI

Ponthip Limlahapun,

Pinmukda Thongua,

Kanyanat Phaithaisong

et al.

Published: Oct. 1, 2022

Coastal areas are subject to dynamic threats due nature, e.g., wind, waves, coastal storms, sea-level rise, and human activity. The consequences may interfere with activities such as aquaculture, tourism, infrastructure. shoreline along the Krachai subdistrict of Chantaburi Province in Thailand was monitored using satellite-based images from 2014-2022. aim this research is apply CoastSat Google Earth Engine monitor shorelines. Using satellite imagery, we can observe analyze coastlines over time actual, reliable context. To save time, methodology applied Python software programming based on automatically search datasets study avoid downloading a whole image. Accuracy verified visual interpretation distance differences were calculated showing an average 0.25 meters. detected clear gave positive results, compensating for operational starting received detection. approach be anywhere detectable by satellite. Slight changes cause difficulty these printed material; therefore, web-based solution developed allow users select interest.

Language: Английский

Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review DOI Creative Commons
Rosa Maria Cavalli

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(3), P. 446 - 446

Published: Jan. 23, 2024

Since 1971, remote sensing techniques have been used to map and monitor phenomena parameters of the coastal zone. However, updated reviews only considered one phenomenon, parameter, data source, platform, or geographic region. No review has offered an overview that can be accurately mapped monitored with data. This systematic was performed achieve this purpose. A total 15,141 papers published from January 2021 June 2023 were identified. The 1475 most cited screened, 502 eligible included. Web Science Scopus databases searched using all possible combinations between two groups keywords: geographical names in areas platforms. demonstrated that, date, many (103) (39) (e.g., coastline land use cover changes, climate change, urban sprawl). Moreover, authors validated 91% retrieved parameters, 39 1158 times (88% combined together other parameters), 75% over time, 69% several compared results each available products. They obtained 48% different methods, their 17% GIS model techniques. In conclusion, addressed requirements needed more effectively analyze employing integrated approaches: they data, merged

Language: Английский

Citations

11
MANGLEE: A Tool for Mapping and Monitoring MANgrove Ecosystem on Google Earth Engine—A Case Study in Ecuador DOI Creative Commons
Lorena Caiza Morales, Cristina Gómez, Rodrigo Torres

et al.

Journal of Geovisualization and Spatial Analysis, Journal Year: 2024, Volume and Issue: 8(1)

Published: May 13, 2024

Abstract Mangroves, integral to ecological balance and socioeconomic well-being, are facing a concerning decline worldwide. Remote sensing is essential for monitoring their evolution, yet its effectiveness hindered in developing countries by economic technical constraints. In addressing this issue, paper introduces MANGLEE (Mangrove Mapping Monitoring Tool Google Earth Engine), an accessible, adaptable, multipurpose tool designed address the challenges associated with sustainable mangrove management. Leveraging remote data, machine learning techniques (Random Forest), change detection methods, consists of three independent modules. The first module acquires, processes, calculates indices optical Synthetic Aperture Radar (SAR) enhancing tracking capabilities presence atmospheric interferences. second employs Random Forest classify non-mangrove areas, providing accurate binary maps. third identifies changes between two-time maps, categorizing alterations as losses or gains. To validate MANGLEE’s effectiveness, we conducted case study mangroves Guayas, Ecuador, region historically threatened shrimp farming. Utilizing data from 2018 2022, our findings reveal significant loss over 2900 hectares, 46% occurring legally protected areas. This corresponds rapid expansion Ecuador’s industry, confirming tool’s efficacy despite cloud cover challenges. demonstrates potential valuable monitoring, offering insights conservation, management plans, decision-making processes. Remarkably, it facilitates equal access optimal utilization resources, contributing significantly preservation coastal ecosystems.

Language: Английский

Citations

10
Trends in marine pollution mitigation technologies: Scientometric analysis of published literature (1990-2022) DOI
Damsara Anthony, Hasitha Siriwardana,

Sanduni Ashvini

et al.

Regional Studies in Marine Science, Journal Year: 2023, Volume and Issue: 66, P. 103156 - 103156

Published: Aug. 21, 2023

Language: Английский

Citations

17
National-scale spatial prediction of soil organic carbon and total nitrogen using long-term optical and microwave satellite observations in Google Earth Engine DOI
Tao Zhou, Wenhao Lv,

Yajun Geng

et al.

Computers and Electronics in Agriculture, Journal Year: 2023, Volume and Issue: 210, P. 107928 - 107928

Published: May 23, 2023

Language: Английский

Citations

13
Detecting Shoreline Changes on the Beaches of Hainan Island (China) for the Period 2013–2023 Using Multi-Source Data DOI Open Access
Rui Yuan, Ruiyang Xu, Hezhenjia Zhang

et al.

Water, Journal Year: 2024, Volume and Issue: 16(7), P. 1034 - 1034

Published: April 3, 2024

This study presents an in-depth analysis of the dynamic beach landscapes Hainan Island, which is located at southernmost tip China. Home to over a hundred natural and predominantly sandy beaches, Island confronts significant challenges posed by frequent marine disasters human activities. Addressing urgent need for long-term studies dynamics, this research involved use CoastSat extract analyze shoreline data from 20 representative beaches calculate slopes 119 around island period 2013 2023. The objective was delineate patterns evolution that contribute prevention sediment loss, mitigation coastal hazards, promotion sustainable zone management. By employing multi-source remote sensing imagery tool, investigation validated slope measurements across selected demonstrating consistency between calculated actual distances despite minor anomalies. effective finite element solution (FES) in 2014 global tidal model corrections further aligned coastlines with mean shoreline, underscoring CoastSat’s utility enabling precise studies. revealed seasonal variations positions, approximately half monitored sites showing seaward progression summer retreat winter, were linked wave height. southern exhibited distinct variations, contrasted general trend due differing impacts. western shores showed erosion, while northern eastern displayed accretion. indicated had steeper slopes, areas more pronounced These findings highlight critical role integrated management erosion control strategies safeguarding Island’s beaches. understanding mechanisms driving regional changes, measures can be developed mitigate impacts enhance resilience ecosystems amidst changing environmental conditions. provides foundational basis future efforts aimed development utilization resources on Island.

Language: Английский

Citations

4
Aslantaş Barajı Göl Alanının Mevsimsel Değişiminin Google Earth Engine ve Uzaktan Algılama Teknikleri İle Belirlenmesi DOI Creative Commons
Kamil Karataş, Celal Bıçakcı, Selim Serhan YILDIZ

et al.

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Journal Year: 2025, Volume and Issue: 8(1), P. 100 - 115

Published: Jan. 15, 2025

Yaşamın devamlılığı için en önemli unsurlardan biri sudur. Artan nüfusa rağmen yeryüzündeki su kaynaklarının sabit kalması suya olan ihtiyacı her geçen gün artırmaktadır. Türkiye'deki sürdürülebilirliği etkin bir yönetimi büyük önem arz etmektedir. Su kaynaklarında ve rezervlerinde zaman içinde meydana gelen değişikliklerin incelenmesi yönetimine katkı sağlamaktadır. Sulak alanların dinamiklerinin haritalanması analizi uzaktan algılama (UA) teknikleri coğrafi bilgi sistemleri (CBS) hızlı etkili yöntemlerdir. Yüksek zamansal konumsal çözünürlüğe sahip uydu görüntüleri ile bu yöntemler başarılı şekilde kullanılmaktadır. Bu çalışmada; Osmaniye ili sınırları içerisinde bulunan Aslantaş Baraj Gölü alanının mevsimsel değişiminin belirlenmesi için, 2022 yılı Mayıs, Ağustos, Kasım Şubat aylarına ait Sentinel-2 kullanılmıştır. gölüne yüzeyi alanlarının belirlenmesinde literatürde de sıklıkla kullanılan sonuçlar elde edilen, normalleştirilmiş fark indeksi (NDWI) Uydu görüntülerine NDWI uygulaması Google Earth Engine (GEE) platformunda gerçekleştirilmiştir. Daha sonra yüzeyindeki alansal değişim ENVI programı Analizler sonucunda edilen bulgulara göre; ilkbahar mevsiminden yaz mevsimine geçişte fazla azalışa uğramıştır. iki mevsim arasında göl yüzey alanı 7,51 km² azalmıştır. En artış ise sonbahar kış gerçekleşerek 5,41 km2 artmıştır. Sonbahar mevsiminde baraj gölü 43,27 olarak yıl içerisindeki düşük seviyede olduğu sonucuna ulaşılmıştır.

Citations

0
Comparing Cloud Mask Products for Seagrass Mapping Over Sentinel‐2 Imagery: Toward a First National Seagrass Map for Venezuela DOI Creative Commons
Chengfa Benjamin Lee,

Ana Carolina Peralta Brichtova,

Mar Roca

et al.

Journal of Geophysical Research Machine Learning and Computation, Journal Year: 2025, Volume and Issue: 2(2)

Published: April 22, 2025

Abstract Despite providing many valuable ecosystem services, seagrasses are a threatened habitat and their global distribution is not fully known. For example, Venezuela lacks national seagrass map. An established regional mapping approach for exists the Google Earth Engine (GEE) platform, but requires long time window to obtain sufficient data overcome cloud other challenges. Recently, GEE has released Cloud Score+ quality band product purpose of masking. masking could potentially reduce needed representative multitemporal composite, which would allow temporal analyses. We compare performance derived products against previously image composites acquired in different ranges, ACOLITE‐processed single composite. The Sentinel‐2 (S2) Level‐1C (L1C) imagery whole Venezuelan coastline was processed following three approaches: (a) using composition full S2 L1C archive available Dark Object Subtraction; (b) integrating set into previous approach; (c) single‐image offline applying ACOLITE atmospheric correction. Additional raster features were generated two‐step classification performed with five classes, namely sand, seagrass, turbid water, deep coral, bootstrapped 20 times. Quantitatively, within largely similar. While had best quantitative results, produced maps qualitatively. With this, we first map Venezuela.

Language: Английский

Citations

0
Morphological evolution of paired sand spits at the Fudu river mouth: Wave effects and anthropogenic factors DOI

Shanhang Chi,

Chi Zhang, Ping Wang

et al.

Marine Geology, Journal Year: 2023, Volume and Issue: 456, P. 106991 - 106991

Published: Jan. 13, 2023

Language: Английский

Citations

9
Mapping the National Seagrass Extent in Seychelles Using PlanetScope NICFI Data DOI Creative Commons
Chengfa Benjamin Lee, L. D. Martin, Dimosthenis Traganos

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(18), P. 4500 - 4500

Published: Sept. 13, 2023

Seagrasses provide ecosystem services worth USD 2.28 trillion annually. However, their direct threats and our incomplete knowledge hamper capabilities to protect manage them. This study aims evaluate if the NICFI Satellite Data Program basemaps could map Seychelles’ extensive seagrass meadows, directly supporting country’s ambitions this ecosystem. The Seychelles archipelago was divided into three geographical regions. Half-yearly from 2015 2020 were combined using an interval mean of 10th percentile median before land deep water masking. Additional features produced Depth Invariant Index, Normalised Differences, segmentation. With 80% reference data, initial Random Forest followed by a variable importance analysis performed. Only top ten contributing retained for second classification, which validated with remaining 20%. best overall accuracies across regions ranged between 69.7% 75.7%. biggest challenges are its four-band spectral resolution uncertainties owing sampling bias. As part nationwide extent blue carbon mapping project, estimates herein will be ancillary satellite data contribute full national estimate in near-future report. numbers reported showcase broader potential at scale.

Language: Английский

Citations

9
Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach DOI Creative Commons
Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi

et al.

GIScience & Remote Sensing, Journal Year: 2024, Volume and Issue: 62(1)

Published: Dec. 16, 2024

The seagrass ecosystems are among the most important organic carbon sinks on Earth, having a key role as climate change buffers. Among all seagrasses, Posidonia oceanica, an endemic species in Mediterranean Sea, has been observed to feature highest stock and sequestration rate seagrasses. We developed satellite-based workflow complement situ monitoring efforts Balearic Islands (Western Mediterranean), reducing field expenses while covering regional spatial scales. Our synoptic tool uses Sentinel-2 A/B satellite imagery at 10 m resolution generate multi-temporal composite (2016–2022) of Islands' coastal waters within Google Earth Engine cloud computing platform, optimizing image processing highlighting importance high-resolution bathymetric dataset increase mapping accuracies. Machine learning algorithms have applied perform detection, obtaining cartography up 30 depth, estimating 505.6 km2 habitat extent. Using existing soil (Cstock) data, we estimated mean Cstock value 12.27 ± 2.1 million megagram (Mg) Corg, total annual C fixation (Cfix) (Cseq) rates P. oceanica 1,116.3 Mg Corg 227 according depth. methodology highlights using large archive optical optimized bathymetry better map account blue across showing integrate this Observation approach ensure ecosystem This information aims support development strategies with time- cost-efficient Sea.

Language: Английский

Citations

2