Towards global long-term water transparency products from the Landsat archive

Remote Sensing of Environment, Год журнала: 2023, Номер 299, С. 113889 - 113889

Опубликована: Ноя. 1, 2023

Secchi Disk Depth (Zsd) is one of the most fundamental and widely used water-quality indicators quantifiable via optical remote sensing. Despite decades research, development, demonstrations, currently, there no operational model that enables retrieval Zsd from rich archive Landsat, long-standing civilian Earth-observation program (1972 – present). Devising a robust requires comprehensive in situ dataset for testing validation, enabling consistent mapping across optically varying global aquatic ecosystems. This study utilizes Mixture Density Networks (MDNs) trained with large (N = 5689) 300+ water bodies to formulate implement algorithm Landsat sensors, including Thematic Mapper (TM), Enhanced Plus (ETM+), Operational Land Imager (OLI) aboard Landsat-5, -7, -8, -9, respectively. Through an extensive Monte Carlo cross-validation data, we showed MDNs improved when compared other commonly machine-learning (ML) models recently developed semi-analytical algorithms, achieving median symmetric accuracy (ε) ∼29% bias (β) ∼3%). A fully MDN was then applied atmospherically corrected data (i.e., sensing reflectance; Rrs) both further validate our MDN-estimated products using independent satellite-to-in matchup 3534) demonstrate their utility time-series analyses (1984 present) selected lakes coastal estuaries. The quality Rrs rigorously assessed sensors indicated sensor-/band-dependent ε ranging 8% 37%. For products, found ∼ 39% β Landsat-8/OLI matchups. We observed higher errors biases TM ETM+, which are explained by uncertainties induced atmospheric correction instrument calibration. Once these sources uncertainty are, extent possible, characterized accounted for, can be employed evaluate long-term trends transparency unprecedented spatiotemporal scales, particularly poorly studied regions world manner.

Язык: Английский

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Cross-comparison of Landsat-8 and Landsat-9 data: a three-level approach based on underfly images

GIScience & Remote Sensing, Год журнала: 2024, Номер 61(1)

Опубликована: Фев. 16, 2024

The recently launched Landsat-9 has an important mission of working together with Landsat-8 to reduce the revisit period Landsat Earth observations eight days. This requires data be highly consistent that avoid bias caused by inconsistency when two satellites are simultaneously used. Therefore, this study evaluated consistency surface reflectance (SR) and land temperature (LST) between based on five test sites from different parts world using synchronized underfly image pairs both satellites. Previous cross-comparisons have demonstrated high spectral bands Landsat-9, differences around 1%. However, it is unclear whether low deviation will amplified in subsequent multiband calculations. It also necessary determine difference across cover types. used a three-level cross-comparison approach specifically examine these concerns. Besides commonly band-by-band comparison, which served as first-level comparison study, included second-level calculations several indicators third-level composite index calculated obtained comparison. found per-band would change after second- comparisons. Remote Sensing Ecological Index (RSEI) was for because integrating four indicators. results show exhibited satellites' SR data, average absolute percent (PC) 1.88% R2 0.957 six sites. increased 2.21% index-based decreasing 0.956. indicates complex calculations, some extent. analyzing specific types, notable emerged water category, PC ranging 18% 35% lower than 0.6. Additionally, there were nearly 5% built-up value 0.7. LST reveals 0.24°C areas but can 0.58°C land-dominated 0.42°C higher desert environments. Overall, consistent. their performance varies depending Caution needed particularly water-related research utilizing simultaneously. Significant discrepancies may arise characterized deserts lands.

Язык: Английский

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Monitoring of chlorophyll-a and suspended sediment concentrations in optically complex inland rivers using multisource remote sensing measurements

Ecological Indicators, Год журнала: 2023, Номер 155, С. 111041 - 111041

Опубликована: Окт. 9, 2023

In recent decades, phytoplankton proliferation and sediment input to rivers (especially urban rivers) have become more dramatic under the compound pressure of climate change human activities. Given generally narrow width current high spatial resolution satellites, which are limited by band settings, bandwidth, signal-to-noise ratio, UAVs with their exceptional spatiotemporal can be used as a useful tool for river environmental monitoring inversion uncertainty assessment. this study, UAV-based hyperspectral (X20P) multispectral (P4M) images, along Sentinel-2 MultiSpectral Instrument (MSI), Landsat-8 Operational Land Imager (OLI) Landsat-9 OLI2 data, were assess in retrieving chlorophyll-a (Chla) suspended (SS) concentrations rivers. Chla SS models based on UAV satellite data constructed using stepwise multiple regression typical retrieval algorithms, respectively, performance was focus our research. The results demonstrated that concentration inversion, each sensor performed follows: X20P > P4M Landsat9 MSI Landsat8 OLI, OLI. addition, retrievals analyzed assistance model. Results showed bandwidths finely tuned settings essential inversion. algorithm, NDCI, is only effective certain bands (band 1 from 684 724 nm 2 660 680 nm). It also noted lack some key (e.g., red-edge 700–710 nm), severely limiting practical application relation Chla. However, specific variances different relatively small impact example, correlation between R/B (a algorithm) ranged 0.68 0.77. monitoring, other hand, necessitates higher than monitoring. accuracy decreased markedly when images resampled 10 m 30 resolution. it not crucial original (RMSE<30cm = 6.28 mg/L) (RMSE10m 5.85 (RMSE30m 4.08 while increased. Our highlighted various options future SS, exploiting synergy satellites achieve precise observations at greater temporal scales, will benefit aquatic environment management protection.

Язык: Английский

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Validation of satellite-derived water-leaving reflectance in contrasted French coastal waters based on HYPERNETS field measurements

Frontiers in Remote Sensing, Год журнала: 2024, Номер 4

Опубликована: Фев. 8, 2024

Since 2021, two autonomous HYPERNETS (A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation) stations are operated contrasted French coastal waters: one the center an optically complex lagoon at mouth a highly turbid estuary. These perform predefined sequences above-water radiometric following strict viewing geometry. The data recorded by ®HYPSTAR is automatically transmitted to servers quality-controls then computation water-leaving signal. Numerous matchups were identified with high (Sentinel2-MSI Landsat8/9-OLI) medium (Sentinel3-OLCI Aqua-MODIS) spatial resolution analyzed assess performance different atmospheric correction algorithms (Sen2Cor, ACOLITE, POLYMER, iCOR, C2RCC, GRS, BPAC, NIR-SWIR). Considering specifications each site (i.e., temporal variations optical properties), optimized matchup protocols first established guaranty quality comparisons between products field measurements. results highlight failure limits several complex/turbid waters. importance accurate sun glint corrections low moderately-turbid waters (with good performances C2RCC GRS processors, e.g., errors (MAPE) lower than 25% green spectral region) also shown while use dark targets fitting estimate aerosol contributions proved be most method case Sen2Cor ACOLITE 20% visible near-infrared regions).

Язык: Английский

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Assessing on-orbit radiometric performance of SDGSAT-1 MII for turbid water remote sensing

Remote Sensing of Environment, Год журнала: 2025, Номер 321, С. 114683 - 114683

Опубликована: Фев. 27, 2025

Язык: Английский

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AI-driven opportunities and challenges in lake remote sensing

Опубликована: Апрель 1, 2025

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Characterization of Java Island's volcanoes based on volcano density and quantification of volcanic products using Landsat imagery

Geosystems and Geoenvironment, Год журнала: 2025, Номер unknown, С. 100398 - 100398

Опубликована: Апрель 1, 2025

Язык: Английский

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Combining RadCalNet Sites for Radiometric Cross Calibration of Landsat 9 and Landsat 8 Operational Land Imagers (OLIs)

Remote Sensing, Год журнала: 2023, Номер 15(24), С. 5752 - 5752

Опубликована: Дек. 15, 2023

Combining images from multiple Earth Observing (EO) satellites increases the temporal resolution of data, overcoming limitations imposed by low revisit time and cloud coverage. However, this requires an intercalibration process to ensure that there is no radiometric difference in top-of-atmosphere (TOA) observations or quantify any offset respective instruments. In addition, combining vicarious calibration processes instruments can provide a useful mechanism validate compare data sensors. The Radiometric Calibration Network (RadCalNet) provides automated surface reflectance participating ground sites be used for instrument calibration. We present comparative analysis Landsat 8 9 Operational Land Imagers (OLI) sensors comparing them measurements RadCalNet as quantitative approach. serves common reference calibration, providing SI-traceable TOA with its associated absolute uncertainties. This paper discusses method calculating weighted average their presented methodology quantifies uncertainty OLI instruments, demonstrating two are good agreement each other reliably cross-correlated scientific community.

Язык: Английский

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Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(20), С. 29048 - 29070

Опубликована: Апрель 3, 2024

Язык: Английский

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A comprehensive review of various environmental factors' roles in remote sensing techniques for assessing surface water quality

The Science of The Total Environment, Год журнала: 2024, Номер 957, С. 177180 - 177180

Опубликована: Ноя. 23, 2024

Язык: Английский

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