scholarly journals BIO OPTICAL MODELLING OF LAGUNA LAKE USING BOMBER TOOL AND WASI-DERIVED INVERTED PARAMETERS

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 277-282
Author(s):  
R. L. Jalbuena ◽  
A. C. Blanco ◽  
A. Manuel ◽  
R. R. Sta. Ana ◽  
J. A. Santos
Keyword(s):  
Water Quality ◽  
Optical Properties ◽  
Optical Model ◽  
Water Source ◽  
Biological Properties ◽  
Landsat 8 ◽  
Produce Water ◽  
Optical Modelling ◽  
Laguna Lake

Abstract. Laguna Lake is significant to its surrounding cities and municipalities as it serves multiple purposes: flood basin, aquaculture, water source for irrigation and domestic use, among others. Monitoring the lake’s water quality is an integral part ensuring that the lake would continue to serve its purposes. Bio-optical modelling is a type of empirical model that relates the inherent optical properties of water to different biological properties like chlorophyll-a. The BOMBER (Bio-Optical Model Based tool for Estimating water quality and bottom properties from Remote sensing images) tool makes use of the different IOPs apparent optical properties (AOPs) of satellite images to be able to produce water quality maps. To localize the parameters used by the BOMBER tool, the use of WASI (The Water Color Simulator) tool was introduced. Inverting in situ spectral measurements of the lake, WASI tool was able to produce parameters localized for the lake. This research used 2018 Landsat 8 Images to produce images and used a water profiler to validate results. Results show the bio-optical model provided a R-squared value of 0.6912 and an RMSE of 2.43 μg/l which shows good correlation between the in-situ and the bio-optical model results.

scholarly journals OPTMIZATION OF BIO-OPTICAL MODEL PARAMETERS FOR TURBID LAKE WATER QUALITY ESTIMATION USING LANDSAT 8 AND WASI-2D

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 67-72
Author(s):  
A. Manuel ◽  
A. C. Blanco ◽  
A. M. Tamondong ◽  
R. Jalbuena ◽  
O. Cabrera ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
The Philippines ◽  
Quality Data ◽  
Model Parameters ◽  
Landsat 8 ◽  
Water Quality Data ◽  
Chlorophyll A Concentration ◽  
In Situ Data

Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.

scholarly journals Developing of Total Suspended Sediment Model Using Landsat-8 Satellite Image and In-Situ Data at The Surabaya Coast, East Java, Indonesia

2017 ◽  
Vol 49 (1) ◽  
pp. 73 ◽  
Author(s):  
Teguh Hariyanto ◽  
Trismono C. Krisna ◽  
Khomsin Khomsin ◽  
Cherie Bhekti Pribadi ◽  
Nadjadji Anwar
Keyword(s):  
Water Quality ◽  
Suspended Sediment ◽  
Coastal Water ◽  
Satellite Image ◽  
Coastal Region ◽  
Sediment Concentration ◽  
Landsat 8 ◽  
Total Suspended Sediment ◽  
Coastal Water Quality

The decrease of coastal-water quality in the Surabaya coastal region can be recognized from the conceentration of Total Suspended Sediment(TSS ) . As a result we need a system for monitoring sediment concentration in the coastal region of Surabaya which regularly measures TSS. The principle to model and monitor TSSconcentration using remote sensing methods is by the integration of Landsat-8OLI satellites image processing using some ofTSS-models then those are analyzed for looking its suitability with TSS value direcly measured in the field ( in-situ measurement). The TSS value modeled from all algorithms validated usingcorrelation analysis and linear regression . The result shows that TSS model with the highest correlation value is TSS algorithm by Budiman (2004)with r value 0.991. Hence this algorithm can be used to investigate TSS-distribution which represent the coastal water quality of Surabaya with TSS value between 75 mg/L to 125 mg/L.

scholarly journals Can single empirical algorithms accurately predict inland shallow water quality status from high resolution, multi-sensor, multi-temporal satellite data?

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1511-1516 ◽  
Author(s):  
I. Theologou ◽  
M. Patelaki ◽  
K. Karantzalos
Keyword(s):  
Water Quality ◽  
High Resolution ◽  
Satellite Data ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Multi Temporal ◽  
Water Quality Status ◽  
Quality Status ◽  
Empirical Algorithms

Assessing and monitoring water quality status through timely, cost effective and accurate manner is of fundamental importance for numerous environmental management and policy making purposes. Therefore, there is a current need for validated methodologies which can effectively exploit, in an unsupervised way, the enormous amount of earth observation imaging datasets from various high-resolution satellite multispectral sensors. To this end, many research efforts are based on building concrete relationships and empirical algorithms from concurrent satellite and in-situ data collection campaigns. We have experimented with Landsat 7 and Landsat 8 multi-temporal satellite data, coupled with hyperspectral data from a field spectroradiometer and in-situ ground truth data with several physico-chemical and other key monitoring indicators. All available datasets, covering a 4 years period, in our case study Lake Karla in Greece, were processed and fused under a quantitative evaluation framework. The performed comprehensive analysis posed certain questions regarding the applicability of single empirical models across multi-temporal, multi-sensor datasets towards the accurate prediction of key water quality indicators for shallow inland systems. Single linear regression models didn’t establish concrete relations across multi-temporal, multi-sensor observations. Moreover, the shallower parts of the inland system followed, in accordance with the literature, different regression patterns. Landsat 7 and 8 resulted in quite promising results indicating that from the recreation of the lake and onward consistent per-sensor, per-depth prediction models can be successfully established. The highest rates were for chl-a (r<sup>2</sup>=89.80%), dissolved oxygen (r<sup>2</sup>=88.53%), conductivity (r<sup>2</sup>=88.18%), ammonium (r<sup>2</sup>=87.2%) and pH (r<sup>2</sup>=86.35%), while the total phosphorus (r<sup>2</sup>=70.55%) and nitrates (r<sup>2</sup>=55.50%) resulted in lower correlation rates.

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 RADIOMETRIC CALIBRATION OF LANDSAT-8 OLI AND SENTINEL-2 MSI IMAGES FOR WATER QUALITY MODELLING OF LAGUNA LAKE, PHILIPPINES

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 229-232
Author(s):  
E. V. Gubatanga Jr ◽  
A. C. Blanco ◽  
C. H. Lin ◽  
B. Y. Lin
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Reference Image ◽  
Time Interval ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Landsat 8 Oli ◽  
Laguna Lake ◽  
Over Time ◽  
Sentinel 2

Abstract. Regular monitoring of water quality in Laguna Lake is important for it supports aquaculture and provides water supply for Metro Manila. Remote sensing makes it possible to monitor the spectral conditions of the lake on a regular time interval and with complete coverage except for the areas with cloud and shadow cover. Along with in-situ water quality measurements, bio-optical models can be developed to determine the relationship between spectral and bio-optical properties of the lake water and consequently enables the estimation of water quality through remote sensing. However, radiometric calibration is needed to minimize the effects of the changing atmospheric conditions over time and to account for the difference in sensors (e.g., Landsat-8 OLI, Sentinel-2 MSI) used for water quality assessment. Canonical correlation analysis is used to detect pseudo-invariant features (PIFs), which are ground objects that do not dramatically vary in spectral properties over time. Road surface and other large man-made infrastructures are the commonly detected PIFs. These PIFs are used to compute for the parameters used to normalize reflectance values of remotely-sensed images obtained on different dates and using different sensors. The normalization resulted to a reduction of difference in reflectance values between the reference image and the adjusted image, though not marginal. This is due to the use of a linear equation to adjust the image, which limits the ability of the reflectance values of the image to fit to the values of the reference image.

Spectral reflectivity variations of Brassica napus depending on degree of soil moisture

2021 ◽  
Author(s):  
Yury Davidovich
Keyword(s):  
Optical Properties ◽  
Soil Moisture ◽  
Brassica Napus ◽  
Spectral Reflectance ◽  
Multispectral Image ◽  
Anthropogenic Factors ◽  
Landsat 8 ◽  
Reflectance Function ◽  
Spectrometric Measurements

&lt;p&gt;Studying of the optical properties of agricultural vegetation is one of the methods for plants condition estimation, prediction of their development and changes influenced by natural and anthropogenic factors.&lt;/p&gt;&lt;p&gt;The work is dedicated to the investigation of spectral reflectance function of agricultural &lt;em&gt;Brassica napus&lt;/em&gt; taking into account the degree of soil moisture. When most of the agricultural lands in Belarus are covered with vegetation in summer, employing the optical properties of agricultural vegetation for deciphering the soil depends on the degree of soil moisture. Insufficient numbers of days in year when the soil is not covered by vegetation or is in a plowed state requires in-situ optical measurements, because there are more than 50 % cloudy conditions in the year, especially in spring and autumn time.&lt;/p&gt;&lt;p&gt;The study has been carried out near the Minsk 11.06.2020 (53.837004&amp;#186; N, 27.487597&amp;#186; E) in clear, cloudless day. The relief for investigated field is hilly-ridge, characterized by a predominance of elevation marks from 250 to 300 m and it is actively sown field. During the spectrometric measurements, the field has been sown with &lt;em&gt;Brassica napus&lt;/em&gt; in the phenological phase of pod formation.&lt;/p&gt;&lt;p&gt;When studying the spectral reflectance of &lt;em&gt;Brassica napus&lt;/em&gt;, in-situ spectrometric measurements and analysis of a multispectral image have been carried out. Spectrometric measurements have been carried out by FSR-02 spectrometer (spectral range 400-900 nm, spectral resolution 4.3 nm) aiming to retrieve spectral reflectance function.&lt;/p&gt;&lt;p&gt;The normalized vegetation index NDVI has been used for analyzing the multispectral image from Landsat 8 OLI system with a spatial resolution of 30 m. The results of a study of the correlation between the reflection coefficient of &lt;em&gt;Brassica napus&lt;/em&gt;&lt;span&gt;&amp;#160;and the area of observed soils will be presented. In addition, the results of the analysis of quasi-synchronous values of the NDVI index and in-situ measurements of the spectral reflectance of &lt;em&gt;Brassica napus&lt;/em&gt; will be discussed.&lt;/span&gt;&lt;/p&gt;

scholarly journals Determination of Bathing Water Quality Using Thermal Images Landsat 8 on the West Coast of Tangier: Preliminary Results

2019 ◽  
Vol 11 (8) ◽  
pp. 972 ◽  
Author(s):  
El Khalil Cherif ◽  
Farida Salmoun ◽  
Francisco Javier Mesas-Carrascosa
Keyword(s):  
Water Quality ◽  
West Coast ◽  
River Mouth ◽  
Decision Makers ◽  
Landsat 8 ◽  
Bacterial Concentration ◽  
The West ◽  
Bathing Water ◽  
Bathing Water Quality

Bathing water quality has been monitored in the west coast of Tangier, Morocco due to increased urban and industrial discharge through the Boukhalef river, using in-situ bacteriological measurements which demand high economical and temporal costs. In this study, Landsat 8 Thermal Infrared Sensor (TIRS) images were used as an alternative to the classical method, for determining bathing water quality to help decision makers obtain up-to-date and cost-effective information for coastal environment protection. For this purpose, during spring and summer 2017, seven sampling points were examined in terms of bacteriological parameters: Total Coliforms (TC), Faecal Coliforms (FC), Intestinal Enterococci (IE) and Escherichia coli (E. coli). Also, a spatial-temporal analysis was performed in this temporal window to detect temperature anomalies and their spatial distribution along the coastal bathing area. In addition, a relationship between in-situ bacteriological parameter measurements and temperature from satellite images was analyzed. The results of the water temperature distribution showed the highest values next to the Boukhalef river mouth, as well as the poorest water quality according to in-situ measurements, while lower values and better water quality status were observed moving away from the Boukhalef river mouth. The relationship between water temperature and bacterial concentration showed a high correlation coefficient (R2 = 0.85). Consequently, the model development approaches used may be useful in estimating bacterial concentration in coastal bathing areas and can serve to create a monitoring system to support decision makers in the protection actions of the coast.

A Landsat 8 OLI Satellite Data-Based Assessment of Spatio-Temporal Variations of Lake Sevan Phytoplankton Biomass

2017 ◽  
Vol 17 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Garegin Tepanosayn ◽  
Vahagn Muradyan ◽  
Azatuhi Hovsepyan ◽  
Lilit Minasyan ◽  
Shushanik Asmaryan
Keyword(s):  
Water Quality ◽  
Phytoplankton Biomass ◽  
Atmospheric Correction ◽  
In Situ Measurements ◽  
Biomass Estimation ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Phytoplankton Communities ◽  
Spatio Temporal

Abstract The Sevan is one of the world’s largest highland lakes and the largest drinking water reservoir to the South Caucasus. An intensive drop in the level of the lake that occurred over the last decades of the 20th century has brought to eutrophication. The 2000s were marked by an increase in the level of the lake and development of fish farming. To assess possible effect of these processes on water quality, creating a state-ofthe- art water quality monitoring system is required. Traditional approaches to monitoring aquatic systems are often time-consuming, expensive and non-continuous. Thus, remote sensing technologies are crucial in quantitatively monitoring the status of water quality due to the rapidity, cyclicity, large-scale and low-cost. The aim of this work was to evaluate potential applications of the Landsat 8 Operational Land Imager (OLI) to study the spatio-temporal phytoplankton biomass changes. In this study phytoplankton biomasses are used as a water quality indicator, because phytoplankton communities are sensitive to changes in their environment and directly correlated with eutrophication. We used Landsat 8 OLI (30 m spatial resolution, May, Aug, Sep 2016) images converted to the bottom of atmosphere (BOA) reflectance by performing standard preprocessing steps (radiometric and atmospheric correction, sun glint removal etc.). The nonlinear regression model was developed using Landsat 8 (May 2016) coastal blue, blue, green, red, NIR bands, their ratios (blue/red, red/green, red/blue etc.) and in situ measurements (R2=0.7, p<0.05) performed by the Scientific Center of Zoology and Hydroecology of NAS RA in May 2016. Model was applied to the OLI images received for August and September 2016. The data obtained through the model shows that in May the quantity of phytoplankton mostly varies from 0.2 to 0.6g/m3. In August vs. May a sharp increase in the quantity of phytoplankton around 1-5 g/m3 is observable. In September, very high contents of phytoplankton are observed for almost entire surface of the lake. Preliminary collation between data generated with help of the model and in-situ measurements allows to conclude that the RS model for phytoplankton biomass estimation showed reasonable results, but further validation is necessary.

scholarly journals Analysis of Water Quality in Historical Shipwreck Sites to Support the Development of Marine Ecotourism in the Thousand Islands

2021 ◽  
Vol 324 ◽  
pp. 03001
Author(s):  
Agustin Rustam ◽  
Ira Dillenia ◽  
Rainer A Troa ◽  
Eko Triarso ◽  
Ofri Johan ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Measurement ◽  
Added Value ◽  
North Coast ◽  
Landsat 8 ◽  
Marine Biota ◽  
Marine Tourism ◽  
Thousand Islands ◽  
Marine Ecotourism

Thousand Islands has become the main focus of the marine tourism development in Special Capitol Region of Jakarta (DKI Jakarta). In this regard, one of the marine tourism objects proposed to be further developed is historical shipwreck diving as a new marine ecotourism attraction in the Thousand Islands. The historical sites of shipwrecks that are widely scattered underwater are expected to give added value to the beauty of underwater panorama because most of the sites have been covered with coral reefs adding to the uniqueness to the underwater diving attractions. However, the high activity on the North Coast of Java area and surrounding islands tends to affect the water quality and the presence of shipwrecks assuming it will be used for the development of diving tourism. This study aims to determine the carrying capacity of water quality on shipwrecks based on in situ water quality measurement and image analysis. The method of data collection and analysis carried out is a combination of in situ measurements at the location; analysis of water samples with laboratory testing and analysis of Landsat 8 satellite imagery. The result showed that nutrient and orthophosphate values of nitrate, which supported the life of marine biota and micro-algae that helped the biota’s biofouling process, increased the site’s attractiveness from 0.094 – 0.101 mg/L and 0.005 – 0.008 mg/L, respectively. Furthermore, other water quality values measured are still in accordance with quality standards for marine life survival on shipwrecks and ecotourism, especially dive spots with clear water visibility.

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