Sentinel-2 Data for Land Cover/Use Mapping: A Review

Remote Sensing, Journal Year: 2020, Volume and Issue: 12(14), P. 2291 - 2291

Published: July 16, 2020

The advancement in satellite remote sensing technology has revolutionised the approaches to monitoring Earth’s surface. development of Copernicus Programme by European Space Agency (ESA) and Union (EU) contributed effective surface producing Sentinel-2 multispectral products. satellites are second constellation ESA Sentinel missions carry onboard scanners. primary objective mission is provide high resolution data for land cover/use monitoring, climate change disaster as well complementing other such Landsat. Since launch instruments 2015, there have been many studies on classification which use images. However, no review dedicated application monitoring. Therefore, this focuses two aspects: (1) assessing contribution classification, (2) exploring performance different applications (e.g., forest, urban area natural hazard monitoring). present shows that a positive impact specifically crop, forests, areas, water resources. contemporary adoption can be attributed higher spatial (10 m) than medium images, temporal 5 days availability red-edge bands with multiple applications. ability integrate remotely sensed data, part analysis, improves overall accuracy (OA) when working free access policy drives increasing especially developing countries where financial resources acquisition limited. literature also produces accuracies (>80%) machine-learning classifiers support vector machine (SVM) Random forest (RF). maximum likelihood analysis common. Although offers opportunities challenges include mismatching Landsat OLI-8 lack thermal bands, differences among Sentinel-2. show promise potential contribute significantly towards

Language: Английский

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Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

Remote Sensing, Journal Year: 2020, Volume and Issue: 12(22), P. 3690 - 3690

Published: Nov. 10, 2020

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, global scales is not only necessary to conserve geodiversity, but also preserve biodiversity, well improve biodiversity conservation ecosystem management. Numerous remote sensing (RS) approaches platforms have been used the past enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, objective of characteristics their traits. This contribution provides state-of-the-art review RS-based these traits, by presenting examples aeolian, fluvial, coastal landforms. Different crucial discipline geodiversity using RS are provided, discussing implementation technologies such LiDAR, RADAR, multi-spectral hyperspectral sensor technologies. Furthermore, data products that could future introduced. use spectral traits (ST) trait variation (STV) with geomorphic diversity monitored. We focus on requirements specifically aimed overcoming some key limitations ecological modeling, namely: linking in-situ, close-range, air- spaceborne technologies, science components better understanding impacts complex ecosystems. paper aims impart multidimensional information obtained improved utilization monitoring.

Language: Английский

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New capabilities of Sentinel-2A/B satellites combined with in situ data for monitoring small harmful algal blooms in complex coastal waters

Scientific Reports, Journal Year: 2020, Volume and Issue: 10(1)

Published: May 26, 2020

Abstract The increased frequency of harmful algal blooms (HABs) is a major environmental concern worldwide, resulting not only in treatment costs for drinking water but also impacts on tourism, commercial fishing and aquaculture risks to human animal health. Traditional strategies with ship-based approaches based field sampling laboratory analysis have been adopted assess HABs. However, these methods are labour intensive costly do provide synoptic views the bloom conditions. Here, we show that Sentinel-2 twin satellite mission Copernicus programme, combination situ data, powerful tool can offer valuable spatiotemporal information about dinoflagellate Lingulodinium polyedra occurred SW Iberian Peninsula. Using robust ACOLITE atmospheric correction processor combined normalized difference chlorophyll index (NDCI), enhanced mapping small be performed at 10 m spatial resolution, revealing surface patches heterogeneous distribution. This research demonstrates improved capabilities compared those Landsat-8 Sentinel-3 continuous monitoring. missions ecosystem observations allow community managers evaluate changes quality distribution facilitate field-based measurements. Therefore, value added by products terms paramount importance ecological management purposes regional national scales.

Language: Английский

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An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery

Water, Journal Year: 2021, Volume and Issue: 13(12), P. 1647 - 1647

Published: June 11, 2021

Surface water bodies, such as rivers, lakes, and reservoirs, play an irreplaceable role in global ecosystems climate systems. Sentinel-2 imagery provides new high-resolution satellite remote sensing data. Based on the analysis of spectral characteristics satellite, a novel index called (SWI) that is based vegetation-sensitive red-edge band (Band 5) shortwave infrared 11) bands was developed. Four representative body types, namely, Taihu Lake, Yangtze River, Chaka Salt Chain were selected study areas to conduct extraction performance comparison with normalized difference (NDWI). We found (1) contrast value SWI larger than NDWI terms various including purer water, turbid salt floating ice, which suggested could achieve better enhancement for bodies. (2) An effective method proposed by integrating Otsu algorithm, accurately extract types high overall accuracy. (3) The effectively extracted large bodies wide river channels suppressing shadow noise urban areas. Our results can efficient rapidly extracting from data has application potential larger-scale surface mapping.

Language: Английский

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Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe

Natural hazards and earth system sciences, Journal Year: 2022, Volume and Issue: 22(8), P. 2473 - 2489

Published: Aug. 2, 2022

Abstract. Inundation is one of the major natural hazards in Europe. The evaluation flood hazard and risk not straightforward mainly due to monitoring system that poor or uniformly distributed territory. ESA Earth Observation Program, including a series satellites, Sentinels, for operative observation phenomenon, e.g. inundations, can potentially reduce gap. Sentinel-1 (SAR: synthetic aperture radar) Sentinel-2 (optical) have been demonstrated be suitable mapping flooded areas, but despite medium–high spatial temporal resolution sensors, inundated territories often partial missing. objective this study evaluate through effectiveness systematic assessment floods Europe, where events durations ranging from some hours few days. To reach target, we analysed 10 years river discharge data over almost 2000 sites extracted established thresholds as proxies riverine inundations. Based on revisit time satellite constellations cloud coverage, derived percentage potential inundation could able observe. Results show assuming configuration constellation two satellites each mission considering ascending descending orbit, average 58 % are observable by only 28 coverage.

Language: Английский

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The role of seagrass meadows in the coastal trapping of litter

Marine Pollution Bulletin, Journal Year: 2022, Volume and Issue: 174, P. 113299 - 113299

Published: Jan. 1, 2022

The accelerated discard and mismanagement of human-made products are resulting in the continued input litter into oceans. Models field observations show how floating can accumulate remote areas throughout global ocean, but far less is known about non-floating fraction. Seagrass meadows play an important role sediment natural-debris dynamics, likely also storage processing litter. In this work, was studied across six Posidonia oceanica meadows. Litter accumulated mainly around landside edge meadow. outer margin predominantly trapped macro-litter, whilst microplastics along inner margin. On average, macro-litter concentrations increased 3-fold after heavy rainfall. Retention by coastal facilitates recurrent landward-seaward conveyance easily-transportable (mainly plastic items) its fragmentation before it buried or transferred to deeper areas.

Language: Английский

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OmbriaNet—Supervised Flood Mapping via Convolutional Neural Networks Using Multitemporal Sentinel-1 and Sentinel-2 Data Fusion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2022, Volume and Issue: 15, P. 2341 - 2356

Published: Jan. 1, 2022

Regions around the world experience adverse climate-change-induced conditions that pose severe risks to normal and sustainable operations of modern societies. Extreme weather events, such as floods, rising sea levels, storms, stand characteristic examples impair core services global ecosystem. Especially floods have a impact on human activities, hence, early accurate delineation disaster is top priority since it provides environmental, economic, societal benefits eases relief efforts. In this article, we introduce OmbriaNet, deep neural network architecture, based convolutional networks, detects changes between permanent flooded water areas by exploiting temporal differences among flood events extracted different sensors. To demonstrate potential proposed approach, generated OMBRIA, bitemporal multimodal satellite imagery dataset for image segmentation through supervised binary classification. It consists total number 3.376 images, synthetic aperture radar from Sentinel-1, multispectral Sentinel-2, accompanied with ground-truth images produced data derived experts provided Emergency Management Service European Space Agency Copernicus Program. The covers 23 globe, 2017 2021. We collected, co-registrated preprocessed in Google Earth Engine. validate performance our method, performed benchmarking experiments OMBRIA compared several competitive state-of-the-art techniques. experimental analysis demonstrated formulation able produce high-quality maps, achieving superior over state-of-the-art. provide dataset, well OmbriaNet code at: https://github.com/geodrak/OMBRIA .

Language: Английский

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Water quality monitoring with Sentinel-2 and Landsat-8 satellites during the 2021 volcanic eruption in La Palma (Canary Islands)

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 822, P. 153433 - 153433

Published: Jan. 29, 2022

In this study, seawater quality was monitored with high-resolution satellite imagery during the 2021 volcanic eruption (September-December) on La Palma Island (Spain), longest recorded in history of island, and most destructive last century Europe. The Sentinel-2A/B twin satellites Landsat-8 were jointly used as an optical constellation, which allowed us to successfully characterize short- medium-term evolution new lava delta subsequent impact seawater. Robust atmospheric sunglint correction approaches applied thoroughly quantify environmental changes caused adjacent coastal waters. cloud ash coverage remained very high over coast event, so restricted information 14 images (45% total scenes) retrieved from multi-sensor approach. Nevertheless, availability pre-, syn-, post-eruption products map detect main water variations marine environment. On one hand, eruption, a change properties observed, markedly increased turbidity western side island near due deposition material. other chlorophyll-a concentration did not significantly increase, algal blooms oligotrophic conditions swiftly altered towards eutrophic conditions. This offered excellent opportunity emplacement its environment Palma. present strategy is highlight potential remote sensing technology relevant powerful tool for future hazard monitoring assessment catastrophes better interpretation their

Language: Английский

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Using Copernicus Sentinel-2 and Sentinel-3 data to monitor harmful algal blooms in Southern Chile during the COVID-19 lockdown

Marine Pollution Bulletin, Journal Year: 2020, Volume and Issue: 161, P. 111722 - 111722

Published: Oct. 8, 2020

Language: Английский

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Near-Real-Time Flood Mapping Using Off-the-Shelf Models with SAR Imagery and Deep Learning

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(12), P. 2334 - 2334

Published: June 14, 2021

Timely detection of flooding is paramount for saving lives as well evaluating levels damage. Floods generally occur under specific weather conditions, such excessive precipitation, which makes the presence clouds very likely. For this reason, radar-based sensors are most suitable near-real-time flood mapping. The public dataset Sen1Floods11 recently released by Cloud to Street one example ongoing beneficial initiatives employ deep learning with synthetic aperture radar. present study used improve using well-known segmentation architectures, SegNet and UNet, networks. In addition, provided a deeper understanding set polarized band combination more distinguishing permanent water, flooded areas from SAR image. overall performance models various kinds labels bands detect all surface water were also assessed. Finally, trained tested on completely different location at Kerala, India, during 2018 verifying their in real-world situation event outside given test dataset. results prove that can be off-the-shelf achieve an intersection over union (IoU) high 0.88 comparison optical images. omission commission error less than 6%. However, important result processing time whole satellite image was 1 min. This will help significantly providing analysis mapping services first responder organizations disasters.

Language: Английский

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