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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Shallow Water Ocean Color Observations Inversion Using Particle Swarm Optimization and Genetic Algorithm
摘要： In this work, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) optimization techniques are used to retrieve water column inherent optical properties (IOPs), bottom reflectance and geometric depth from a simulated hyperspectral dataset. The synthetic dataset (N=6000) is created using two different bottom types (Sand and seagrass), three levels of depth, 20 concentrations of Chlorophyll – a (Chl-a) with a wide range of modelled IOP variations resembling natural clear and optically complex waters. Results indicate that PSO and GA showed similar retrieval results in IOPs. Bottom reflectance values from PSO are near to input bottom substrate values compared to GA. In case of Geometric depth also, average depth value retrieved by PSO are better than GA retrieved. In terms of processing time, PSO exhibited higher computational efficiency than GA by five times. Further studies can use PSO to process Hyperspectral remote sensing Imagery in shallow waters.
关键词： PSO,Shallow waters,Ocean color inversion,Optimization,GA
更新于2025-09-23 15:21:21
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Ocean Dynamics Observed by VIIRS Day/Night Band Satellite Observations
摘要： Three cases of Day/Night Band (DNB) observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) are explored for applications to assess the ocean environment and monitor ocean dynamics. An approach to use the ratio between the target radiance and the reference radiance was developed in order to better assess the ocean diurnal and short-term environmental changes with VIIRS DNB observations. In the La Plata River Estuary, the sediment fronts showed 20–25 km diurnal inshore-offshore movements on 13 March 2017. In the waters off the coast of Argentina in the South Atlantic, VIIRS DNB measurements provided both daytime and nighttime observations and monitoring of the algal bloom development and migration between 24 and 26 March 2016. This algal bloom generally kept the same spatial patterns, but moved nearly 20 km eastward in the three-day period. In the Yangtze River Estuary and Hangzhou Bay region along China’s east coast, VIIRS DNB observations also revealed complicated coastal dynamic changes between 12 and 14 April 2017. Even though there are still some challenges and limitations for monitoring the ocean environment with VIIRS DNB observations, this study shows that satellite DNB observations can provide additional data sources for ocean observations, especially observations during the nighttime.
关键词： satellite remote sensing,VIIRS,DNB observation,ocean color,nocturnal study,ocean dynamics
更新于2025-09-23 15:21:01
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Regionalization and Dynamic Parameterization of Quantum Yield of Photosynthesis to Improve the Ocean Primary Production Estimates From Remote Sensing
摘要： Quantum yield of photosynthesis (φ) expresses the efficiency of phytoplankton carbon fixation given certain amount of absorbed light. This photophysiological parameter is key to obtaining reliable estimates of primary production (PPsat) in the ocean based on remote sensing information. Several works have shown that φ changes temporally, vertically, and horizontally in the ocean. One of the primary factors ruling its variability is light intensity and thereby, it can be modeled as a function of Photosynthetically Available Radiation (PAR). We estimated φ utilizing long time-series collected in the North Subtropical Oligotrophic Gyres, at HOT and BATS stations (Pacific and Atlantic oceans, respectively). Subsequently the maximum quantum yield (φm) and Kφ (PAR value at half φm) were calculated. Median φm values were ～0.040 and 0.063 mol C mol photons?1 at HOT and BATS, respectively, with higher values in winter. Kφ values were ～8.0 and 10.8 mol photons m?2 d?1 for HOT and BATS, respectively. Seasonal variability in Kφ showed its peak in summer. Dynamical parameterizations for both regions are indicated by their temporal behaviors, where φm is related to temperature at BATS while Kφ to PAR, in both stations. At HOT, φm was weakly related to temperature and its median annual value was used for the whole data series. Differences in the study areas, even though both belong to Subtropical Gyres, reinforced the demand for regional parameterizations in PPsat models. Such parameterizations were finally included in a PPsat model based on phytoplankton absorption (PPsat?aphy?based), where results showed that the PPsat?aphy?based model coupled with dynamical parameterization improved PPsat estimates. Compared with PPsat estimates from the widely used VGPM, a model based on chlorophyll concentration (PPsat?chl?based), PPsat?aphy?based reduced model-measurement differences from ～62.8 to ～8.3% at HOT, along with well-matched seasonal cycle of PP (R2 = 0.76). There is not significant reduction in model-measurement differences between PPsat?chl?based and PPsat?aphy?based PP at BATS though (37.8 vs. 36.4%), but much better agreement in seasonal cycles with PPsat?aphy?based (R2 increased from 0.34 to 0.71). Our results point to improved estimation of PPsat by parameterized quantum yield along with phytoplankton absorption coefficient at the core.
关键词： quantum yield of photosynthesis,ocean color,phytoplankton primary production,in situ measurements,dynamical parameterization,marine seasonal variability
更新于2025-09-23 15:21:01
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Can Multispectral Information Improve Remotely Sensed Estimates of Total Suspended Solids? A Statistical Study in Chesapeake Bay
摘要： Total suspended solids (TSS) is an important environmental parameter to monitor in the Chesapeake Bay due to its effects on submerged aquatic vegetation, pathogen abundance, and habitat damage for other aquatic life. Chesapeake Bay is home to an extensive and continuous network of in situ water quality monitoring stations that include TSS measurements. Satellite remote sensing can address the limited spatial and temporal extent of in situ sampling and has proven to be a valuable tool for monitoring water quality in estuarine systems. Most algorithms that derive TSS concentration in estuarine environments from satellite ocean color sensors utilize only the red and near-infrared bands due to the observed correlation with TSS concentration. In this study, we investigate whether utilizing additional wavelengths from the Moderate Resolution Imaging Spectroradiometer (MODIS) as inputs to various statistical and machine learning models can improve satellite-derived TSS estimates in the Chesapeake Bay. After optimizing the best performing multispectral model, a Random Forest regression, we compare its results to those from a widely used single-band algorithm for the Chesapeake Bay. We find that the Random Forest model modestly outperforms the single-band algorithm on a holdout cross-validation dataset and offers particular advantages under high TSS conditions. We also find that both methods are similarly generalizable throughout various partitions of space and time. The multispectral Random Forest model is, however, more data intensive than the single band algorithm, so the objectives of the application will ultimately determine which method is more appropriate.
关键词： water quality,total suspended solids,ocean color,satellite remote sensing,statistical analysis,Random Forest,Chesapeake Bay,multispectral,machine learning
更新于2025-09-19 17:15:36
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Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea
摘要： Since 2007, green tide blooms with Ulva prolifera as the dominant species have occurred every summer in the Yellow Sea. Biomass is a critical parameter used to describe the severity of green tide blooms. In this study, we analyzed the relationships between several indices (normalized difference vegetation index (NDVI), floating algae index (FAI), ratio vegetation index (RVI), enhanced vegetation index (EVI), ocean surface algal bloom index (OSABI), Korea Ocean Satellite Center (KOSC) approach) and the biomass per unit area of Ulva prolifera by using the in situ measurements from a water tank experiment. EVI, NDVI, and FAI showed strong exponential relationships with Ulva prolifera biomass per unit area. In order to apply the relationships to satellite remote sensing data, the impacts of the atmosphere (different aerosol optical depth at 550 nm) and mixed pixels to the relationships were analyzed. The results show that atmosphere has little effect on the relationship between EVI and Ulva prolifera biomass per unit area with R2 = 0.94 and APD (the average percentage deviation) = 19.55% when EVI is calculated from Rrc (Rayleigh-corrected reflectance), and R2 = 0.95 and APD = 17.53% when EVI is calculated from Rtoa (top-of-atmosphere reflectance). Due to the low sensitivity to the atmosphere, the EVI relationship can be directly utilized in the top-of-atmosphere (TOA) reflectance without atmospheric correction. In addition, the EVI was slightly affected by mixed pixels with the APD only increased by ~10%. The EVI relationship was then applied to a long MODIS image time series to obtain the maximal total biomass of floating Ulva prolifera in the Yellow Sea from 2007 to 2016. The results showed that the maximum and minimum total biomass occurred in 2016 (~1.17 million tons) and 2012 (~0.074 million tons), respectively. The main factors that caused the inter-annual biomass variability were analyzed. The total amount of nutrients from Sheyang River which was the largest river on the northern coast of Jiangsu Province, and Porphyra cultivation in the Radial Sand Ridges of Jiangsu Province had both strong correlation with Ulva prolifera total biomass.
关键词： Atmosphere effect,Remote sensing,Ulva prolifera,Ocean color,Biomass,EVI
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE Globecom Workshops (GC Wkshps) - Waikoloa, HI, USA (2019.12.9-2019.12.13)] 2019 IEEE Globecom Workshops (GC Wkshps) - Improving QKD for Entangled States with Low Squeezing via Non-Gaussian Operations
摘要： This study investigates standard and regional algal pigment index 1 (API1) estimates in the Atlantic off the southwestern Iberian Peninsula. Standard API1 data are those delivered by the Medium Resolution Imaging Spectrometer (MERIS) orbiting sensor. Equivalent quantities are computed by applying a regional inversion scheme using as input both MERIS and in situ remote sensing re?ectances (Rrs). Reference data for the development of the regional algorithm and for the analysis of tested products include ?eld measurements of total concentration of chlorophyll a (TChla) and coincident Rrs values collected at different distances from the coast. Validation results, based on matchup analysis, identi?es a systematic overestimation of standard API1 versus the reference TChla values. The additional comparison of product maps in selected regions of interest con?rms this tendency and demonstrates the feasibility and relevance of using regional algorithms for investigating spaceborne products. Analogous applications are hence devised for the early-stage evaluation of the forthcoming Sentinel-3/OLCI data products.
关键词： remote sensing re?ectance,Medium Resolution Imaging Spectrometer (MERIS) algal pigment index 1 (API1),ocean color,multilayer perceptron (MLP) neural nets
更新于2025-09-19 17:13:59
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Display Technology 2019: Never a Dull Moment
摘要： This study investigates standard and regional algal pigment index 1 (API1) estimates in the Atlantic off the southwestern Iberian Peninsula. Standard API1 data are those delivered by the Medium Resolution Imaging Spectrometer (MERIS) orbiting sensor. Equivalent quantities are computed by applying a regional inversion scheme using as input both MERIS and in situ remote sensing re?ectances (Rrs). Reference data for the development of the regional algorithm and for the analysis of tested products include ?eld measurements of total concentration of chlorophyll a (TChla) and coincident Rrs values collected at different distances from the coast. Validation results, based on matchup analysis, identifies a systematic overestimation of standard API1 versus the reference TChla values. The additional comparison of product maps in selected regions of interest confirms this tendency and demonstrates the feasibility and relevance of using regional algorithms for investigating spaceborne products. Analogous applications are hence devised for the early-stage evaluation of the forthcoming Sentinel-3/OLCI data products.
关键词： ocean color,remote sensing re?ectance,Medium Resolution Imaging Spectrometer (MERIS) algal pigment index 1 (API1),multilayer perceptron (MLP) neural nets
更新于2025-09-16 10:30:52
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Evaluation of Semi-Analytical Algorithms to Retrieve Particulate and Dissolved Absorption Coefficients in Gulf of California Optically Complex Waters
摘要： Two semi-analytical algorithms, Generalized Inherent Optical Property (GIOP) and Garver-Siegel-Maritorena (GSM), were evaluated in terms of how well they reproduced the absorption coefficient of phytoplankton (aph(λ)) and dissolved and detrital organic matter (adg(λ)) at three wavelengths (λ of 412, 443, and 488 nm) in a zone with optically complex waters, the Upper Gulf of California (UGC) and the Northern Gulf of California (NGC). In the UGC, detritus determines most of the total light absorption, whereas, in the NGC, chromophoric dissolved organic material (CDOM) and phytoplankton dominate. Upon comparing the results of each model with a database assembled from four cruises done from spring to summer (March through September) between 2011 and 2013, it was found that GIOP is a better estimator for aph(λ) than GSM, independently of the region. However, both algorithms underestimate in situ values in the NGC, whereas they overestimate them in the UGC. Errors are associated with the following: (a) the constant a*ph(λ) value used by GSM and GIOP (0.055 m2 mgChla?1) is higher than the most frequent value observed in this study’s data (0.03 m2 mgChla?1), and (b) satellite-derived chlorophyll a concentration (Chla) is biased high compared with in situ Chla. GIOP gave also better results for the adg(λ) estimation than GSM, especially in the NGC. The spectral slope Sdg was identified as an important parameter for estimating adg(λ), and this study’s results indicated that the use of a fixed input value in models was not adequate. The evaluation confirms the lack of generality of algorithms like GIOP and GSM, whose reflectance model is too simplified to capture expected variability. Finally, a greater monitoring effort is suggested in the study area regarding the collection of in situ reflectance data, which would allow explaining the effects that detritus and CDOM may have on the semi-analytical reflectance inversions, as well as isolating the possible influence of the atmosphere on the satellite-derived water reflectance and Chla.
关键词： remote sensing,ocean color,inherent optical properties
更新于2025-09-09 09:28:46
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Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite
摘要： The purpose of this study was to optimize a composite method for the Geostationary Ocean Color Imager (GOCI), which is the first geostationary ocean color sensor in the world. Before interpreting the sensitivity of each composite with ground measurements, we evaluated the accuracy of bidirectional reflectance distribution function (BRDF) performance by comparing modeled surface reflectance from BRDF simulation with GOCI-measured surface reflectance according to composite period. The root mean square error values for modeled and measured surface reflectance showed reasonable accuracy for all of composite days since each BRDF composite period includes at least seven cloud-free angular sampling for all BRDF performances. Also, GOCI-BRDF-adjusted NDVIs with four different composite periods were compared with field-observation NDVI and we interpreted the sensitivity of temporal crop dynamics of GOCI-BRDF-adjusted NDVIs. The results showed that vegetation index seasonal profiles appeared similar to vegetation growth curves in both field observations from crop scans and GOCI normalized difference vegetation index (NDVI) data. Finally, we showed that a 12-day composite period was optimal in terms of BRDF simulation accuracy, surface coverage, and real-time sensitivity.
关键词： bidirectional reflectance distribution function (BRDF),vegetation profiles,Geostationary Ocean Color Imager (GOCI),composite period,normalized difference vegetation index (NDVI)
更新于2025-09-04 15:30:14