scholarly journals Monitoring of Turbidity Variation in the Ukai Reservoir, Gujarat, INDIA, during 1993-2018 using Landsat Series of Dataset

2021 ◽  
pp. 236-251
Author(s):  
V. Pompapathi ◽  
Shard Chander ◽  
Ashwin Gujrati ◽  
H.A. Solanki ◽  
R. P. Singh
Keyword(s):  
Light Attenuation ◽  
Field Measurements ◽  
River System ◽  
Quality Parameters ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Hydrological Process ◽  
Average Value ◽  
Post Monsoon

Turbidity is one of the important water quality parameters, which is required to understand the eco-hydrological process such as a trophic state of water, soil erosion into the river system, mixing of other water sources, runoff, discharge etc. An algorithm has been developed to estimate the turbidity (in NTU: Nephelometric Turbidity Unit) over inland waters using Red band of optical multispectral dataset. Field measurements were carried out over Ukai reservoir for 27-28th March 2018 for pre monsoon and 27-30th September 2018 for post monsoon seasons, sampling sites ranging from turbid to clear water. Where in situ water leaving reflectance and turbidity were measured. Model was derived between in situ measured turbidity and spectral reflectance of Red band of Landsat series of datasets includes Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) data from 1993-2018. The model was applied to derive the turbidity maps of Ukai reservoir for pre-monsoon (March, April and May months) season and post monsoon (September, October and November months) seasons. Overall turbidity was in the range of 1.47-25 NTU during the field data collection for both pre and post monsoon seasons. To investigate the results in detail, the reservoir was divided into three parts, i.e. Down (A), Middle (B) and Up Streams (C). The water was relatively clear in the downstream portion with average turbidity less than 5 NTU over the study period. While maximum turbidity was observed in the upstream portion with values more than 20 NTU. In the middle portion, the turbidity values were fluctuating within the range 4-13 NTU with an average value of 6 NTU. These turbidity maps can be used to determine underwater light attenuation that has importance in ecosystem modelling.

scholarly journals Comparison of Historical Water Temperature Measurements with Landsat Analysis Ready Data Provisional Surface Temperature Estimates for the Yukon River in Alaska

2021 ◽  
Vol 13 (12) ◽  
pp. 2394
Author(s):  
Carson Baughman ◽  
Jeffrey Conaway
Keyword(s):  
Standard Deviation ◽  
Surface Temperature ◽  
Water Temperature ◽  
In Situ Measurements ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Yukon River ◽  
Daily Water Temperature ◽  
Daily Water

Water temperature is a key element of freshwater ecological systems and a critical element within natural resource monitoring programs. In the absence of in situ measurements, remote sensing platforms can indirectly measure water temperature over time and space. The Earth Resources Observation and Science (EROS) Center has processed archived Landsat imagery into analysis ready data (ARD), including Level-2 Provisional Surface Temperature (pST) estimates derived from the Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Thermal Infrared Sensor (TIRS). We compared in situ measurements of water temperature within the Yukon River in Alaska with 52 instances of pST estimates between June 2014 and September 2020. Agreement was good with an RMSE of 2.25 °C and only a slight negative bias in the estimated mean daily water temperature of −0.47 °C. For the 52 dates compared, the average daily water temperature measured by the USGS streamgage was 11.3 °C with a standard deviation of 5.7 °C. The average daily pST estimate was 10.8 °C with a standard deviation of 6.1 °C. At least in the case of large unstratified rivers in Alaska, ARD pST can be used to infer water temperature in the absence of or in tandem with ground-based water temperature monitoring campaigns.

scholarly journals Determinación de calidad de agua en el Lago Vichuquén, con imágenes de satélite Landsat 8, sensor OLI, año 2016, Chile

2018 ◽  
pp. 67 ◽  
Author(s):  
I. Briceño ◽  
W. Pérez ◽  
D. San Miguel ◽  
S. Ramos
Keyword(s):  
Water Quality ◽  
Urban Areas ◽  
Laboratory Data ◽  
Radiata Pine ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Linear Regression Models ◽  
Chl A ◽  
The Mean

<p>Trophic structure deterioration in continental water bodies (lakes and damps) has been a growing problem during the last years. Numerous factors, either natural or man-made contribute in value increments of various water quality indexes ranging toward eutrophication. Our study had objective to use remote sensing as complementary tool to study the spatial distribution and dynamics of Lake Vichuquén water quality parameters in two seasons of 2016 through the use of two satellite images of the Landsat 8 OLI sensor, with in situ and laboratory data. The Chl-a and Z<sub>SD</sub> parameters were estimated from multiple linear regression models. The results indicate that the trophic state of Lake Vichuquén corresponds to a eutrophic level in summer and mesotrophic in autumn. The laboratory analyzes establish for the summer and autumn season that the Chl-a data oscillate between 14.1 and 5.5 μg/l and for the Z<sub>SD</sub> between 3.7 and 2.5 m respectively. The increase in the levels of eutrophication of Lake Vichuquén is influenced in the first place by the seasonality and secondly by the different land uses that accelerate this type of processes; such as the plantations of radiata pine and eucalyptus, the agricultural activities and the urban areas surrounding the lake. The mean square error for each variable and each season varied in Chl-a in summer and another year 0.74 and 0.01 µg/l and Z<sub>SD</sub> 0.16 m respectively.</p>

scholarly journals ALGORITMA DUA DIMENSI UNTUK ESTIMASI MUATAN PADATAN TERSUSPENSI MENGGUNAKAN DATA SATELIT LANDSAT-8, STUDI KASUS: TELUK LAMPUNG

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Muchlisin Arief ◽  
Syifa Wismayati Adawiah ◽  
Maryani Hartuti ◽  
Ety Parwati
Keyword(s):  
Linear Equation ◽  
Optical Sensors ◽  
Total Suspended Solid ◽  
Suspended Solid ◽  
Quality Parameters ◽  
Landsat 8 ◽  
The West ◽  
Remote Sensing Technique ◽  
Measurement Results

Remote sensing technique is a powerful tool for monitoring the coastal zone. Optical sensors can be used to measure water quality parameters Total Suspended Matter (MPT). In order to be able to extract information MPT, the satellite data need to be validated with in situ measurements that make the relationship between the reflectance band with concentration MPT measurement results. In this model, do the correlation between the measurement results with the reflectance values band 3 and band 4. then obtained a linear equation, then calculated using the argument of a ratio of 60:75 to each of the correlation coefficient, the obtained linear equation two Dimension T (X3, X4) = 2313.77 X3 + 4741.11 X4 + 314.95. Based on the concentration MPT of dated June 3, 2015 was lower than in the west to the east. this is because the east is already contaminated with the plant, effluent solids by humans, while the west for still many floating net fish, and mangrove. Based on the results of measurement and calculation results , is still far from perfect (accuracy 60%), one factor is the value thresholding, when determining the boundary between: clouds, sea, and land. Generally indicates that the model is still in need for repair. Abstrak Penginderaan jauh adalah alat yang ampuh untuk memantau zona pesisir. Sensor optik dapat digunakan untuk mengukur parameter kualitas air Total Suspended Solid/Muatan Padatan Tersuspensi (MPT). Agar supaya dapat mengekstraksi informasi MPT, maka, data satelit perlu divalidasi dengan pengukuran in situ yaitu membuat hubungan antara reflektansi band dengan konsentrasi MPT hasil pengukuran. Pada model ini, dilakukan korelasi antara hasil pengukuran dengan nilai reflektansi band3 dan band4, maka diperoleh persamaan linier, kemudian dihitung dengan menggunakan dalil perbandingan 60 : 75, untuk masing-masing koefisien korelasinya, maka diperoleh persamaan linier dua dimensi T(X3,X4) = 2313.77 X3 + 4741,11 X4 + 314.95.  Berdasarkan konsentrasi MPT  pada 3 Juni 2015 di sebelah baratlebih rendah dibandingkan sebelah timur. Hal ini dikarenakan sebelah timur sudah terkontaminasi dengan pabrik, buangan benda padat oleh manusia, sedangkan sebelah barat karena masih banyak keramba jaring apung ikan dan mangrove. Berdasarkan hasilnya antara pengukuran dan hasil perhitungan, masih jauh dari sempuna (ketelitiannya 60 %), salah satu faktornya adalah dalam menentukan nilai thresholding, pada saat  menentukan batas antara: awan, laut dan darat. Secara umum menunjukkan bahwa model yang masih membutuhkan perbaikan.

scholarly journals Radiometric Correction of Landsat-8 and Sentinel-2A Scenes Using Drone Imagery in Synergy with Field Spectroradiometry

2018 ◽  
Vol 10 (11) ◽  
pp. 1687 ◽  
Author(s):  
Joan-Cristian Padró ◽  
Francisco-Javier Muñoz ◽  
Luis Ávila ◽  
Lluís Pesquer ◽  
Xavier Pons
Keyword(s):  
Near Infrared ◽  
Field Measurements ◽  
Systematic Sampling ◽  
Landsat 8 ◽  
Radiometric Correction ◽  
Multispectral Data ◽  
Central Hypothesis ◽  
Sentinel 2A ◽  
Sentinel 2

The main objective of this research is to apply unmanned aerial system (UAS) data in synergy with field spectroradiometry for the accurate radiometric correction of Landsat-8 (L8) and Sentinel-2 (S2) imagery. The central hypothesis is that imagery acquired with multispectral UAS sensors that are well calibrated with highly accurate field measurements can fill in the scale gap between satellite imagery and conventional in situ measurements; this can be possible by sampling a larger area, including difficult-to-access land covers, in less time while simultaneously providing good radiometric quality. With this aim and by using near-coincident L8 and S2 imagery, we applied an upscaling workflow, whereby: (a) UAS-acquired multispectral data was empirically fitted to the reflectance of field measurements, with an extensive set of radiometric references distributed across the spectral domain; (b) drone data was resampled to satellite grids for comparison with the radiometrically corrected L8 and S2 official products (6S-LaSRC and Sen2Cor-SNAP, respectively) and the CorRad-MiraMon algorithm using pseudo-invariant areas, such as reflectance references (PIA-MiraMon), to examine their overall accuracy; (c) then, a subset of UAS data was used as reflectance references, in combination with the CorRad-MiraMon algorithm (UAS-MiraMon), to radiometrically correct the matching bands of UAS, L8, and S2; and (d) radiometrically corrected L8 and S2 scenes obtained with UAS-MiraMon were intercompared (intersensor coherence). In the first upscaling step, the results showed a good correlation between the field spectroradiometric measurements and the drone data in all evaluated bands (R2 > 0.946). In the second upscaling step, drone data indicated good agreement (estimated from root mean square error, RMSE) with the satellite official products in visible (VIS) bands (RMSEVIS < 2.484%), but yielded poor results in the near-infrared (NIR) band (RMSENIR > 6.688% was not very good due to spectral sensor response differences). In the third step, UAS-MiraMon indicated better agreement (RMSEVIS < 2.018%) than the other satellite radiometric correction methods in visible bands (6S-LaSRC (RMSE < 2.680%), Sen2Cor-SNAP (RMSE < 2.192%), and PIA-MiraMon (RMSE < 3.130%), but did not achieve sufficient results in the NIR band (RMSENIR < 7.530%); this also occurred with all other methods. In the intercomparison step, the UAS-MiraMon method achieved an excellent intersensor (L8-S2) coherence (RMSEVIS < 1%). The UAS-sampled area involved 51 L8 (30 m) pixels, 143 S2 (20 m) pixels, and 517 S2 (10 m) pixels. The drone time needed to cover this area was only 10 min, including areas that were difficult to access. The systematic sampling of the study area was achieved with a pixel size of 6 cm, and the raster nature of the sampling allowed for an easy but rigorous resampling of UAS data to the different satellite grids. These advances improve human capacities for conventional field spectroradiometry samplings. However, our study also shows that field spectroradiometry is the backbone that supports the full upscaling workflow. In conclusion, the synergy between field spectroradiometry, UAS sensors, and Landsat-like satellite data can be a useful tool for accurate radiometric corrections used in local environmental studies or the monitoring of protected areas around the world.

scholarly journals Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 565
Author(s):  
Nguyen Nguyen Vu ◽  
Le Van Trung ◽  
Tran Thi Van
Keyword(s):  
Statistical Model ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Measured Data ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

1996 ◽  
Vol 47 (6) ◽  
pp. 763 ◽  
Author(s):  
EG Abal ◽  
WC Dennison
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Suspended Solids ◽  
Light Attenuation ◽  
River Mouth ◽  
Total Suspended Solids ◽  
Quality Parameters ◽  
Depth Range ◽  
Moreton Bay ◽  
A Site

Correlations between water quality parameters and seagrass depth penetration were developed for use as a biological indicator of integrated light availability and long-term trends in water quality. A year-long water quality monitoring programme in Moreton Bay was coupled with a series of seagrass depth transects. A strong gradient between the western (landward) and eastern (seaward) portions of Moreton Bay was observed in both water quality and seagrass depth range. Higher concentrations of chlorophyll a, total suspended solids, dissolved and total nutrients, and light attenuation coefficients in the water column and correspondingly shallower depth limits of the seagrass Zostera capricorni were observed in the western portions of the bay. Relatively high correlation coefficient values (r2 > 0.8) were observed between light attenuation coefficient, total suspended solids, chlorophyll a, total Kjeldahl nitrogen and Zostera capricorni depth range. Low correlation coefficient values (r2 < 0.8) between seagrass depth range and dissolved inorganic nutrients were observed. Seagrasses had disappeared over a five-year period near the mouth of the Logan River, a turbid river with increased land use in its watershed. At a site 9 km from the river mouth, a significant decrease in seagrass depth range corresponded to higher light attenuation, chlorophyll a, total suspended solids and total nitrogen content relative to a site 21 km from the river mouth. Seagrass depth penetration thus appears to be a sensitive bio-indicator of some water quality parameters, with application for water quality management.

scholarly journals Application of an improved surface energy balance model to two large valley glaciers in the St. Elias Mountains, Yukon

2020 ◽  
pp. 1-16
Author(s):  
Tim Hill ◽  
Christine F. Dow ◽  
Eleanor A. Bash ◽  
Luke Copland
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Landsat 8 ◽  
Glacier Surface ◽  
Ice Dynamics ◽  
Surface Melt

Abstract Glacier surficial melt rates are commonly modelled using surface energy balance (SEB) models, with outputs applied to extend point-based mass-balance measurements to regional scales, assess water resource availability, examine supraglacial hydrology and to investigate the relationship between surface melt and ice dynamics. We present an improved SEB model that addresses the primary limitations of existing models by: (1) deriving high-resolution (30 m) surface albedo from Landsat 8 imagery, (2) calculating shadows cast onto the glacier surface by high-relief topography to model incident shortwave radiation, (3) developing an algorithm to map debris sufficiently thick to insulate the glacier surface and (4) presenting a formulation of the SEB model coupled to a subsurface heat conduction model. We drive the model with 6 years of in situ meteorological data from Kaskawulsh Glacier and Nàłùdäy (Lowell) Glacier in the St. Elias Mountains, Yukon, Canada, and validate outputs against in situ measurements. Modelled seasonal melt agrees with observations within 9% across a range of elevations on both glaciers in years with high-quality in situ observations. We recommend applying the model to investigate the impacts of surface melt for individual glaciers when sufficient input data are available.

scholarly journals Underwater Holographic Sensor for Plankton Studies In Situ Including Accompanying Measurements

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4863
Author(s):  
Victor Dyomin ◽  
Alexandra Davydova ◽  
Igor Polovtsev ◽  
Alexey Olshukov ◽  
Nikolay Kirillov ◽  
...  
Keyword(s):  
World Ocean ◽  
Field Tests ◽  
Field Measurements ◽  
Measuring Systems ◽  
Water Turbidity ◽  
Background Data ◽  
Average Size ◽  
Size Dispersion

The paper presents an underwater holographic sensor to study marine particles—a miniDHC digital holographic camera, which may be used as part of a hydrobiological probe for accompanying (background) measurements. The results of field measurements of plankton are given and interpreted, their verification is performed. Errors of measurements and classification of plankton particles are estimated. MiniDHC allows measurement of the following set of background data, which is confirmed by field tests: plankton concentration, average size and size dispersion of individuals, particle size distribution, including on major taxa, as well as water turbidity and suspension statistics. Version of constructing measuring systems based on modern carriers of operational oceanography for the purpose of ecological diagnostics of the world ocean using autochthonous plankton are discussed. The results of field measurements of plankton using miniDHC as part of a hydrobiological probe are presented and interpreted, and their verification is carried out. The results of comparing the data on the concentration of individual taxa obtained using miniDHC with the data obtained by the traditional method using plankton catching with a net showed a difference of no more than 23%. The article also contains recommendations for expanding the potential of miniDHC, its purpose indicators, and improving metrological characteristics.

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

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