scholarly journals HAZE REMOVAL IN THE VISIBLE BANDS OF LANDSAT 8 OLI OVER SHALLOW WATER AREA

2017 ◽  
Vol 13 (2) ◽  
pp. 151
Author(s):  
. Kustiyo ◽  
Anis Kamilah Hayati
Keyword(s):  
Shallow Water ◽  
Reference Data ◽  
Atmospheric Correction ◽  
Water Area ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Haze Removal ◽  
Shallow Water Area ◽  
Correlation Number

Haze is one of radiometric quality parameters in remote sensing imagery. With certain atmospheric correction, haze is possible to be removed. Nevertheless, an efficient method for haze removal is still a challenge. Many methods have been developed to remove or to minimize the haze disruption. While most of the developed methods deal with removing haze over land areas, this paper tried to focus to remove haze from shallow water areas. The method presented in this paper is a simple subtraction algorithm between a band that reflected by water and a band that absorbed by water. This paper used data from Landsat 8 with visible bands as a band that reflected by water while the band that absorbed by water represented by NIR, SWIR-1, and SWIR-2 bands. To validate the method, a reference data which relatively clear of cloud and haze contamination is selected. The pixel numbers from certain points are selected and collected from data scene, results scene and reference scene. Those pixel numbers, then being compared each other to get a correlation number between data scene to reference scene and between result scene and reference scene. The comparison shows that the method using NIR, SWIR-1, and SWIR-2 all significantly improved correlations numbers between result scene with reference scene to higher than 0.9. The comparison also indicates that haze removal result using NIR band had the highest correlation with reference data..

scholarly journals Modelling Reservoir Chlorophyll-a, TSS, and Turbidity Using Sentinel-2A MSI and Landsat-8 OLI Satellite Sensors with Empirical Multivariate Regression

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Yashon O. Ouma ◽  
Kimutai Noor ◽  
Kipkemoi Herbert
Keyword(s):  
Water Quality ◽  
Optical Sensors ◽  
Multivariate Regression ◽  
Atmospheric Correction ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Band Adjustment ◽  
Sentinel 2A

Sentinel-2A/MSI (S2A) and Landsat-8/OLI (L8) data products present a new frontier for the assessment and retrieval of optically active water quality parameters including chlorophyll-a (Chl-a), suspended particulate matter (TSS), and turbidity in reservoirs. However, because of their differences in spatial and spectral samplings, it is critical to evaluate how well the sensors are suited for the seamless generation of the water quality parameters (WQPs). This study presents results from the retrieval of the WQP in a reservoir from L8 and S2A optical sensors, after atmospheric correction and standardization through band adjustment. An empirical multivariate regression model (EMRM) algorithmic approach is proposed for the estimation of the water quality parameters in correlation with in situ laboratory measurements. From the results, both sensors estimated Chl-a concentrations with R2 of greater than 70% from the visible green band for L8 and a combination of green and SWIR-1 bands for S2A. While the NMSE% was nearly the same for both sensors in Chl-a estimation, the RMSE was <10 μg/L and >10 μg/L for L8 and S2A estimations of Chl-a, respectively. For TSS retrieval, L8 outperformed S2A by 31% in accuracy with R2>0.9 from L8’s red, blue, and green bands, as compared to 0.47≤R2≥0.61 from S2A’s red and NIR bands. The RMSE were the same as for Chl-a, and the NMSE% were both in the same range. Both sensors retrieved turbidity with high and nearly equal accuracy of R2>70% from the visible and NIR bands, with equal RMSE at <10% NTU and NMAE% from S2A being higher by more than 30% as compared to L8’s NMAE% at 15%. The study concluded that the higher performance accuracy of L8 is attributed to its higher SNR and spectral bandwidth placement as compared to S2A bands. Comparatively, S2A overestimated Chl-a and turbidity but performed equally well compared to OLI in the estimation of TSS. The results show that while absolute accuracy of retrieval of the WQPs still requires improvements, the developed algorithms are broadly able to discern the biooptical water quality in reservoirs.

Directional Wave Spectra from Video Images Data and SWAN Model

2015 ◽  
Vol 74 (5) ◽  
Author(s):  
Muhammad Zikra ◽  
Noriaki Hashimoto ◽  
Masaru Yamashiro ◽  
Kojiro Suzuki
Keyword(s):  
Shallow Water ◽  
Water Area ◽  
Paper Analysis ◽  
Wave Spectra ◽  
Swan Model ◽  
Video Images ◽  
Shallow Water Area ◽  
Directional Wave ◽  
Probe Sensor ◽  
Rectification Process

In this paper, analysis of directional wave spectra in shallow water area estimated by video images data has been compared with numerical model of SWAN. Estimation of directional wave spectra from video images is based on the Bayesian Directional Method using a group of pixels brightness on the image. For this study, the pixels can be considered equivalent to fixed instruments as wave probe sensor after rectification process. The results show that there is a good agreement between directional wave spectra estimated by video images data and the SWAN model. Both methods estimate similar shape of directional wave spectra in the shallow water. In addition, the energy distribution of directional wave spectra in shallow water is concentrated significantly in frequency and direction. 

Time variability of acoustic signals in a benign shallow‐water area

2000 ◽  
Vol 108 (5) ◽  
pp. 2578-2578
Author(s):  
Peter L. Nielsen ◽  
Martin Siderius ◽  
Finn B. Jensen
Keyword(s):  
Shallow Water ◽  
Acoustic Signals ◽  
Water Area ◽  
Time Variability ◽  
Shallow Water Area

scholarly journals SATELLITE-DERIVED BATHYMETRY: ACCURACY ASSESSMENT ON DEPTHS DERIVATION ALGORITHM FOR SHALLOW WATER AREA

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 159-164 ◽  
Author(s):  
N. M. Said ◽  
M. R. Mahmud ◽  
R. C. Hasan
Keyword(s):  
Shallow Water ◽  
Accuracy Assessment ◽  
Water Area ◽  
Bathymetric Data ◽  
Sensing Technology ◽  
Shallow Water Area ◽  
Multispectral Satellite Imagery ◽  
Marginal Improvement ◽  
Acquisition Technique ◽  
Hydrographic Surveying

Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

scholarly journals WIND AND WAVE RELATIONSHIPS IN A SHALLOW WATER AREA

1974 ◽  
Vol 1 (14) ◽  
pp. 6
Author(s):  
J.S. Driver ◽  
J.D. Pitt
Keyword(s):  
Shallow Water ◽  
Water Area ◽  
Extreme Conditions ◽  
Shallow Water Area ◽  
Wave Conditions ◽  
Direct Measures

An instrumentation system to record direct measures of both wind and wave conditions has been installed at the Wash. Data from these instruments are used in conjunction with long term wind records from another station to predict the frequency and duration of extreme conditions.

scholarly journals Validation of adjoint‐generated environmental gradients for the acoustic monitoring of a shallow water area

2008 ◽  
Vol 123 (5) ◽  
pp. 3510-3510
Author(s):  
Matthias Meyer ◽  
Jean‐Pierre Hermand ◽  
Mohamed Berrada ◽  
Mark Asch
Keyword(s):  
Shallow Water ◽  
Environmental Gradients ◽  
Acoustic Monitoring ◽  
Water Area ◽  
Shallow Water Area

scholarly journals A tool for analysis of the influence of the Earth surface soil layer temperature on the inhomogeneity of grain crops development by the Earth remote sensing data

2021 ◽  
Author(s):  
R.V. Brezhnev ◽  
Yu.A. Maglinets ◽  
K.V. Raevich ◽  
V.G. Margaryan
Keyword(s):  
Surface Temperature ◽  
Atmospheric Correction ◽  
Sensor Data ◽  
Relational Model ◽  
Landsat 8 ◽  
Earth Surface ◽  
Agricultural Crops ◽  
Landsat 8 Oli ◽  
The Earth ◽  
Vegetation Heterogeneity

The work is devoted to the analysis of the influence of the earth surface temperature on the inhomogeneity of the agricultural crops development. The aim of the work is to expand the object-relational model for describing the inhomogeneous spatial structure of a spatial object by including surface temperature as one of the key features that allow determining the cause of vegetation heterogeneity, along with relief features, differences in the soil chemical composition and other significant characteristics. Experimental studies are carried out at sites located in Sukhobuzimsky district of Krasnoyarsk Territory, for which agricultural crops (grains) and the their sowing dates are known a priori, which allows stating any facts of the vegetation development deviation from the normative trajectory with reference to the sequence and timing norms of phenological phase changing. Landsat-8 OLI (Operational Land Imager) TIRS (Thermal Infrared Sensor) data are used as initial data for temperature measurements. Objects of research are presented in the form of a polygon map in SHP format. The temperature values are calculated using the algorithm for estimating the earth temperature developed by Weng Q., Lu D. and Schubring J. The surface reflectance values are the NDVI vegetation index values also obtained from the Landsat-8 OLI data that underwent atmospheric correction by the DOS method. The research results are implemented in the form of a software module and integrated into the Earth remote monitoring (ERM) system of SFU Space and Information Technologies Institute (SITI). The results are used within the concept of object-oriented monitoring of spatial objects developed by the team of authors, and represent index images of the surface temperature of objects, as well as vector schematic maps.

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