Multispectral Sentinel-2 and SAR Sentinel-1 Integration for Automatic Land Cover Classification

Land, Journal Year: 2021, Volume and Issue: 10(6), P. 611 - 611

Published: June 7, 2021

The study of land cover and use dynamics are fundamental to understanding the radical changes that human activity is causing locally globally analyse continuous metamorphosis landscape. In Europe, Copernicus Program offers numerous territorial monitoring tools users decision makers, such as Sentinel data. This research aims at developing implementing a mapping change detection methodology through classification Sentinel-1 Sentinel-2 satellite goal create versatile economically sustainable algorithm capable rapidly processing large amounts data, allowing creation national-scale products with high spatial resolution update frequency for operational purposes. Great attention was paid compatibility main activities planned in near future national European level. this sense, system consistent specifications EAGLE group has been adopted. involves definition distinct sets rules each macro-classes classes. refers pixels’ spectral backscatter characteristics, exploiting multi-temporal indices while proposing two new ones: NDCI distinguish between broad-leaved needle-leaved trees, Burned Index (BI) identify burned areas. allowed production map 2018 related forest disturbances consumption 2017–2018, reaching an overall accuracy 83%.

Language: Английский

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Cloud-Based Remote Sensing for Wetland Monitoring—A Review

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(6), P. 1660 - 1660

Published: March 19, 2023

The rapid expansion of remote sensing provides recent and developed advances in monitoring wetlands. Integrating cloud computing with these techniques has been identified as an effective tool, especially for dealing heterogeneous datasets. In this study, we conducted a systematic literature review (SLR) to determine the current state-of-the-art knowledge integrating results SLR revealed that platform-as-a-service was only service model implemented practice wetland monitoring. Remote applications included prediction, time series analysis, mapping, classification, change detection. Only 51% reviewed literature, focused on regional scale, used satellite data. Additionally, found technologies are not integrated enough benefit from their potential Despite gaps, analysis economic benefits could be achieved by implementing To address gaps pave way further research, propose Internet Things (IoT) monitor wetlands effectively.

Language: Английский

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An Analysis of the Rice-Cultivation Dynamics in the Lower Utcubamba River Basin Using SAR and Optical Imagery in Google Earth Engine (GEE)

Agronomy, Journal Year: 2024, Volume and Issue: 14(3), P. 557 - 557

Published: March 8, 2024

One of the world’s major agricultural crops is rice (Oryza sativa), a staple food for more than half global population. In this research, synthetic aperture radar (SAR) and optical images are used to analyze monthly dynamics crop in lower Utcubamba river basin, Peru. addition, study addresses need obtain accurate timely information on areas under cultivation order calculate their production. To achieve this, SAR sensor Sentinel-2 remote sensing were integrated using computer technology, analyzed through mapping geometric calculation surveyed areas. An algorithm was developed Google Earth Engine (GEE) virtual platform classification Sentinel-1 combination both, result which improved ArcGIS Pro software version 3.0.1 spatial filter reduce “salt pepper” effect. A total 168 96 obtained, corrected, classified machine learning algorithms, achieving average accuracy 96.4% 0.951 with respect overall (OA) Kappa Index (KI), respectively, year 2019. For 2020, averages 94.4% OA 0.922 KI. Thus, data offer excellent integration address gaps between them, great importance obtaining robust products, can be applied improving production planning management.

Language: Английский

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Monthly Monitoring of Inundated Areas and Water Storage Dynamics in China's Large Reservoirs Using Multisource Remote Sensing

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(8)

Published: Aug. 1, 2024

Abstract High‐frequency monitoring of reservoir inundation and water storage changes is crucial for functionality assessment hydrological model calibration. Although the integration optical data with synthetic aperture radar (SAR) backscattering coefficients (backscatters) offers an effective approach, conventional methods struggle to consistently provide accurate retrievals over diverse regions seasons. In this study, we introduce reservoir‐ monthly‐specific classification models enhance Sentinel‐1 SAR backscatters optical‐based dynamics. Our method covers 721 reservoirs a capacity greater than 0.1 km 3 in China during 2017–2021. Furthermore, leverage multisource satellite altimetry records (e.g., ICESat‐2, CryoSat‐2, GEDI) digital elevation derive hypsometry relationship (i.e., level–water area relationship) reservoirs, enabling transformation inundated areas into monthly 662 representing 93% total large reservoirs. Validation against in‐situ measurements at 80 reveals improved compared existing sets. Additionally, our change estimates exhibit average R 2 0.79 mean relative root square error (rRMSE) 21%. findings highlight increases from May/June November declines winter–spring most regions. However, inter‐annual patterns vary among regions, Northeast China, Yellow River basin (YR), Southwest contrasted by Eastern Northwest China. Inter‐ intra‐annual variability mainly influenced natural inflow while anthropogenic factors dominate YR, Eastern,

Language: Английский

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From Land Cover Map to Land Use Map: A Combined Pixel-Based and Object-Based Approach Using Multi-Temporal Landsat Data, a Random Forest Classifier, and Decision Rules

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(9), P. 1700 - 1700

Published: April 28, 2021

It is essential to produce land cover maps and use separately for different purposes. This study was conducted generate such in Binh Duong province, Vietnam, using a novel combination of pixel-based object-based classification techniques geographic information system (GIS) analysis on multi-temporal Landsat images. Firstly, the connection between identified; thereafter, map function regions were extracted with random forest classifier. Finally, generated by combining set decision rules. The results showed that linked spectral, spatial, temporal characteristics, this helped effectively convert into map. final attained an overall accuracy (OA) = 93.86%, producer’s (PA) user’s (UA) its classes ranging from 73.91% 100%. Meanwhile, achieved OA 93.45%, UA PA ranged 84% demonstrated it possible create high-accuracy based entirely free satellite imagery promote reproducibility proactivity research as well cost-efficiency time savings.

Language: Английский

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Detecting the environmental risk on the archaeological sites using satellite imagery in Basilicata Region, Italy

The Egyptian Journal of Remote Sensing and Space Science, Journal Year: 2022, Volume and Issue: 25(1), P. 181 - 193

Published: Feb. 1, 2022

Floods, along with coastal erosion, are among the most dangerous events that threaten heritage sites worldwide. Space agencies (e.g. NASA and ESA) create new platforms applications can help for providing time in studying changes occurring land use/land cover besides flood such as Google Earth Engine platform. This study aims to use up-to-date data, methods, its impacts on archaeological of Metaponto Policoro areas Basilicata Region, southern Italy. In this study, Sentinel-1 (C-band) Landsat time-series data used detecting effects weather regions Ionian coastal, While, (MSS, TM, ETM) downloaded from USGS site, Sentienl1 imported analysed using As well, Digital Shoreline Analysis System (DSAS) statically software through End Point Rate (EPR) Linear Regression (LRR) models estimating shoreline rate change over long-time period. Also, historical topographic maps returning 1941 detect ancient area. ArcMap 10.5 is analysing Optical data. The results showed flooding during 2014, 2016, 2018, 2019, total period between 2014 2021 respectively covered by km2 based space non-water area about 8.3, 1.7, 0.5, 0.6, 39.17. Such decrease risk around affected across changes, previous events.

Language: Английский

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A comprehensive comparison of data fusion approaches to multi-source precipitation observations: a case study in Sichuan province, China

Environmental Monitoring and Assessment, Journal Year: 2022, Volume and Issue: 194(6)

Published: May 11, 2022

Language: Английский

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Assessing surface water pollution in Hanoi, Vietnam, using remote sensing and machine learning algorithms

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(34), P. 82230 - 82247

Published: June 15, 2023

Language: Английский

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Intra- and Inter-annual Spatiotemporal Variations and Climatic Driving Factors of Surface Water Area in the Irtysh River Basin During 1985-2022

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101455 - 101455

Published: Jan. 1, 2025

Language: Английский

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Large-scale flood mapping using Sentinel-1 and Sentinel-2 imagery: Spatio-temporal analysis of the 23·7 Haihe basin-wide extreme flood

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132777 - 132777

Published: Jan. 1, 2025

Language: Английский

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