Distribution Of Total Suspended Solid Research Articles

Analyzing the impact of Jakarta’s reclamation on the distribution of TSS using remote sensing technology

Jakarta Bay is a bay supporting the economy of thousands of nearby fishermen. Therefore, the reclamation in Jakarta Bay raises many environmental, economic, and social problems. During this reclamation, dredging and stockpiling activities increase the turbidity of the waters. This research aims to determine the changes in the distribution of total suspended solids (TSS) after reclamation using Sentinel 2A satellite imagery from 2016 to 2022. This research implemented the previous algorithm to produce the distribution of TSS in Jakarta Bay for attaining TSS values from Sentinel 2A satellite imagery processed by Google Earth Engine with overlay analysis method in a geographic information system. Spatial data were obtained by extracting TSS values using the previous estimation algorithm, namely the Budhiman algorithm, with a correlation coefficient of -0.745 and NMAE of 0.167. Based on the data processing results, it was found that the distribution of TSS from 2016 to 2022 was at a moderate level, which had a relatively significant influence on fisheries, requiring the fishermen to go to the open sea farther from the coast. This shows that reclamation carries no impact on the life of marine biota in Jakarta Bay.

Total suspended solid (TSS) pollution load model at the Jagir River Estuary, Surabaya, East Java

The research aims to create a TSS spatial distribution map model and a pollution load model at the Jagir River Estuary—a descriptive method for the last six years to describe the TSS pollution load model. Satellite image data processing uses SNAP software with the application of the Laili algorithm (2015). The distribution of TSS pollution values and loads still meets the quality standards for mangrove ecosystems. The average value of TSS distribution in 2018 - 2023, respectively, is 18,966 mg/L, 14,578 mg/L, 17,267 mg/L, 16.921 mg/L, and 15,013 mg/L with the highest TSS pollution load occurring in 2023 and the lowest in 2021 and 2022. The average pollution load from 6 research stations in 2019 – 2023 still does not exceed the capacity limit of the Jagir River to accommodate TSS accumulation. The TSS pollution load model in the Jagir River Estuary, Surabaya, East Java, follows a quadratic pattern with the regression equation y = -173.01X2 + 2339.20X - 2299.80 (R2 = 0.7674) with a peak TSS pollution load reaching 5,607.05 tons m3/month in January and lowest in August

Monitoring Total Suspended Solid Distribution In Coastal Bali Area Using MODIS Satellite Data

Total Suspended Solid (TSS) is one important parameter for water quality. This research aims to analyze MODIS feasibility for identifying TSS, to identify TSS monthly patterns and annual patterns variability, and to analyze the TSS distribution patterns around Bali coastal area. Observation data of the wet season was observed in Benoa Bay on 2nd October 2013 and the dry season was observed in Perancak from July on 28th to July 31st, 2009. The comparison between observation data and satellite data was used to establish a new modification algorithm for suitable conditions around Bali coastal area. Based on research analysis, the feasibility of MODIS was different in each season. In the wet season, the coefficient correlation was (r) = 0.55 and in the dry season, it was (r) = 0.68. poor correlation in the wet season indicated the bottom effect of the area which has a shallow and heterogeneous depth. The TSS average in the wet season was 75.55 mg/l and 55.97 mg/l in the dry season. The highest value was analyzed in November (82.74 mg/l) and the lowest value in June (46.41 mg/l). During wet season, the stream volume and the stream flow rate increase and bring the TSS into coastal areas through the runoff process. The mapping patterns showed that the southern coastal area and western coastal area of Bali had a high value every month. The northern coastal had a high value only in the wet season. The characteristic of Bali river area, which is perennial and intermittent rivers caused this phenomenon. The population and Bali land-use area also affected the high TSS in these areas. Yearly patterns of TSS from 2009 to 2013 around Bali coastal areas were different every year. The highest TSS distribution observed in 2013 wet season is 87.75 mg/l. The lowest TSS distribution occurred in 2009 dry season with a value of 52.2 mg/l. The TSS tends to increase every year due to the changing in Bali land use. TSS patterns from 2009 to 2013 were dynamic every year. The El Nina and La Nino events also gave impact on the patterns. The MODIS feasibility in different locations was different depending on the characteristic of the physical property of water. The shallow and small area causes misinterpretation of the satellite reflectance. The TSS monthly patterns depended on the season and the mapping can be used to describe the sources of TSS pollution, the distribution, and the quantity of TSS in the coastal area.

Temporal detection of Total Suspended Solid (TSS) distribution in the southern area of Obi Island

The Halmahera Selatan Regency has many potential natural resources including mining potential, and nickel is one potential that can be found in Obi Island. The abundance of nickel in Obi Island also increases activities that cause various materials to enter the sea. The sediment materials entering the waters through land runoff are suspended sediment or Total Suspended Solids (TSS). Sentinel 2 satellite imageries could observed TSS concentration and its distribution in this research through visible and infrared channels. The distribution of TSS will be determined by using an algorithm, which uses the blue and green bands with corrected atmospheric reflectance format. Based on the data processing results, the distribution of TSS values in the southern area of Obi Island in 2023 was in the range of 4 - 874 mg/l that were divided into three groups of areas, represented by A area within the range of 4 – 874 mg/l, which describes the distribution of TSS in coastal areas without human settlements, B area within range of 4 - 237 mg/l which depicting TSS conditions at river estuaries, and group C area within range of 4 – 431 mg/l which illustrating TSS locations in coastal areas with human settlements.

Modelling of ocean currents and distribution of total suspended solids in Citarum River estuary

The Citarum River is an important river in West Java, which empties into the Java Sea carrying large suspended sediment concentrations. The purpose of this study is to examine the interaction of current patterns and distribution of total suspended solids (TSS) in the Northwest and Southeast Monsoons using hydrodynamic Modelling. The flow model and TSS used were 2-dimensional models with the OpenFlows FLOOD software. The ocean tide model results were validated using the Root Mean Square Error (RMSE) method with a value of 0.10. The current velocity in the West and East monsoons ranges from 0.07 - 0.35 m/s. Currents flow north and northeast during high-tide conditions and move south and southwest during low-tide conditions in both seasons. The movement of TSS was influenced by the current patterns. The highest concentration of TSS is in the Northwest Monsoon at low tide, which was in the range of 560–575 mg/L. The lowest TSS concentration was in the Southeast Monsoon during high tide conditions, ranging from 80 to 120 mg/L. The high concentration of TSS in the Northwest Monsoon was influenced by higher rainfall, with an average in January and only 23.2 mm/day while in the Southeast Monsoon it is only 7.8 mm/day.

Spatial study of total suspended solid (TSS) for shrimp catching areas based on changes in watershed land cover and oceanographic factors in Ciletuh Bay 2017 – 2021

The TSS in Ciletuh Bay originates from the Ci Leutuh and Ci Marinjung estuaries. This study aimed to analyze the effect of changes in watershed land cover and oceanographic factors (salinity, bathymetry, sea surface currents) on the distribution of TSS and the relationship between TSS and shrimp catch activity. This research uses remote sensing method, Budhiman Algorithm for TSS, Cilamaya Algorithm for salinity, and Maximum Likelihood Classification for watershed land cover. The results show that sea surface currents and changes in watershed land cover (forest, bare land, and shrub) affect the distribution of TSS in Ciletuh Bay. The relationship between TSS with salinity and bathymetry is negatively correlated. The existence of TSS in Ciletuh Bay causes the dominance of muddy waters so that it becomes a habitat for various types of Penaeid shrimp. The types of penaeid shrimp that are mostly caught in Ciletuh Bay are rebon shrimp and endok shrimp.

Monitoring the spatial distribution of water quality of an urban stormwater pond using satellite images

Stormwater ponds play a critical role in managing urban runoff and mitigating the impact of pollutants on receiving water bodies. This study investigates the potential of remote sensing (RS) techniques in retrieving water level and key water quality parameters in urban stormwater wet ponds. Specifically, the focus is on water level, chlorophyll-a (Chl-a), total suspended solids (TSS), turbidity, and Secchi depth (SD). The results indicate that RS techniques can provide reliable estimates of water level, Chl-a, turbidity, SD, and TSS in urban stormwater wet ponds. Results revealed that Chl-a concentrations are higher near the inlets and within the forebay, with a significant decrease downstream of the forebay. TSS and total dissolved solids (TDS) concentrations follow a similar pattern to Chl-a, being higher near the inlet and within the forebay, but significantly lower downstream. Notably, the highest concentrations of TSS, TDS, and Chl-a are observed in July, likely due to heavy rainfall events during that period. Through principal component analysis (PCA) and correlation analysis, the study effectively captured the interrelationships among the water quality parameters in the stormwater pond. The spatial distribution of TSS and Chl-a shows a correlation. Furthermore, the study uncovers a relationship between water temperature and Chl-a concentration, with Chl-a decreasing as the temperature exceeds 20 °C and increasing when it drops below 20 °C. This relationship is influenced by sunlight availability, which affects Chl-a growth, as evidenced by variations in Chl-a concentration between the water column's bottom layers and surface. Overall, this research highlights the potential of utilizing RS techniques to retrieve water quality parameters, providing valuable information for water managers and decision-makers. The ability to generate maps of these parameters using reflected light measurements above stormwater wet ponds also contributes to effective water quality management strategies.

Total suspended solid distribution as impact tin mining at surrounded Pangkalpinang seawater Bangka Island

Bangka Belitung Archipelago is well known as tin mining production in Indonesia. The mining activity was performed on land and offshore area which affect the shoreline and total suspended solid distribution especially at Pangkalpinang sea water. The aim of this study is to evaluate total suspended solid (TSS) distribution and compare with oceanography parameters (current and wave). The concentration of TSS was analysed in the laboratory by gravimetric total suspended solids. This study was conducted in June- July 2022 by using survey method and IDW Interpolation. The result showed that total suspended solid have various value, ranging from 56.3 mg/l – 93.3 mg/l. Based on PP No.22 in 2021, several stations on Pangkalpinang sea waters have passed the sea water quality standard. Prolonged exposure of sedimentation will lead to shoreline changes.

Assessment of Total Suspended Solid Concentration Dynamics Based on Geospatial Models as an Impact of Anthropogenic in Pekalongan Waters, Indonesia

Changes in total suspended solids (TSS) concentrations provide information to determine the quality of the carrying capacity of waters as marine resources. This research aims to analyze the concentration and distribution of TSS in marine waters due to anthropogenic impacts on land. The concentration and distribution changes of TSS were analyzed using a geospatial model approach. The in-situ data were collected in August 2021 and June 2022 at 11 stations in the east monsoon and analyzed in the laboratory using the gravimetric method. The results show that TSS concentration changes at the study area significantly increased concentration from 40,3-85,4 mg/L in 2021 to 64,7-140,5 mg/L in 2022, increased by 37,6 – 39,2%, distributed to the east in open water due to the influence of the surface current, which is driven by the wind and tidal current. The anthropogenic factors, such as land use and micro-industrial activities, were dominantly correlated with the increase in TSS concentration in the waters, which is driven by input from land due to the influence of precipitation. This research provides comprehensive monitoring, evaluating, and managing scheme data and information to researchers, local governments, and environmentalists for mitigation planning to reduce the subtraction of water quality due to anthropogenic impacts.

Influence of Rainfall and Spatial Temporal Distribution Analysis of Total Suspended Solid in Laut Tawar Lake

Total Suspended Solid (TSS) is a solid particle suspended in the water column of organic and inorganic materials, sized more than two micrometers. The high concentration of TSS in the waters causes a decrease in water clarity and potentially reduces dissolved oxygen that can threaten the life of aquatic biota. This study aims to analyze the spatial and temporal distribution of TSS and analyze the influence of rainfall on TSS in Laut Tawar Lake waters. The lake TSS ranged from 44 – 91 mg/L with an average of 68.67 ± 11.23 mg/L. Spatially TSS ranged from 63.17 - 73.67 mg/L and temporally ranged from 51.14 - 81.43 mg/L. The distribution of TSS was not spatially different because the lake waters are perfectly agitated. The difference in TSS was obtained temporally due to the influence of rainfall. The catchment area can be eroded by only 100 mm of rain/month. It leads to high production of TSS loading into the lake waters. It was indicated by the difference in TSS of Dry Months with TSS of Wet and Moist Months. The determinant coefficient of influence of rainfall on the TSS concentration of the lake waters is 0.62.

Temporal analysis of total suspended solids (TSS) at Ujung Pangkah Beach, Gresik, from 2016 - 2020 using aqua MODIS image data

Total suspended solids (TSS) is a parameter widely used to detect pollution on the coast, especially in areas that have a sloping coastal structure where currents and waves parallel to the coast will accumulate these solids to form sedimentation gradually. This study aims to map the distribution of TSS on the coast of Ujung Pangkah Gresik where at the end of this coast there is a flow from the Bengawan Solo river. The method in this study implements remote sensing technology to collect Aqua MODIS satellite image data of from 2016 to 2020. Based on calculation results, the wavelength band 1 (660 nanometers) of the Aqua MODIS image is the best wavelength by looking at the R correlation value generated of 0.573, so it can be concluded that the Aqua MODIS satellite imagery with a resolution of 250 - 500 meters can still be used to create a mathematical model for mapping the TSS distribution on the coast. In terms of forecasting for 5 years, the reflectance value generated from the image does not give significant results, because this satellite image is very influenced by the weather, so it is very difficult to get a cloud-free image in the same month every year to extract the reflectance value.

Landsat Image-Based Retrieval and Analysis of Spatiotemporal Variation of Total Suspended Solid Concentration in Jiaozhou Bay, China

The total suspended solid (TSS) concentration (mg/L) is an important parameter of water quality in coastal waters. It is of great significance to monitor the spatiotemporal distribution and variation of TSS as well as its influencing factors. In this study, a quantitative retrieval model of TSS in Jiaozhou Bay (JZB) was established based on Landsat images from 1984 to 2020 (coefficient of determination (R2) = 0.77, root mean square error (RMSE) = 1.82 mg/L). In this paper, first, the long-term spatiotemporal variation of TSSs in JZB is revealed and, next, its influencing factors are further analyzed. The results show that the annual average TSSs in JZB reached their highest level in 1993 and their lowest level in 2016, showing a decreasing trend during the past decades. The TSSs were high in spring and winter and low in summer and autumn. The spatial distribution of the TSSs in JZB was similar at different timepoints, i.e., high in the northwest and gradually decreasing to the southeast. Tidal elevation exerted a significant influence on the daily variation of TSSs, and wind speed had a significant influence on the seasonal variation of TSSs. The Dagu River’s discharge only affected the TSSs at the river mouth. Tidal elevation, river discharge, and wind speed were major influence factors for TSSs’ variation in JZB. The results showed that the empirical model based on Landsat satellite data could be used to effectively monitor the long-term variation of TSSs in JZB.

Total suspended solids characterization and management implications for lakes in East China

In this study, we empirically developed a robust model (the Root Mean Square Error (RMSE), bias, NSE and RE were 26.63 mg/L, −4.86 mg/L, 0.47 and 16.47%, respectively) for estimating the total suspended solids (TSS) concentrations in lakes and reservoirs (Hereinafter referred to as lakes) across the Eastern Plain Lake (EPL) Zone. The model was based on 700 in-situ TSS samples collected during 2007–2020 and logarithmic transformed red band reflectance of Landsat data. Based on the Google Earth Engine (GEE), the TSS concentrations in 16,804 lakes were mapped from 1984 to 2019. The results demonstrated a decreasing tendency of TSS in 82.2% of the examined lakes (72.5% of the basins) indicating that the pollutants carried by TSS flowing into the lakes were decreasing. Statistically significant variation (p < 0.05) was found in half of these lakes (28.6% of the basins). High TSS level (>100 mg/L) was observed in 0.31% of lakes (1.1% of the basins). The changing rates of TSS in 47.8% of the lakes (52.7% of the basins) ranged between −50 mg/L/yr and 0. We found high and significantly increased relative spatial heterogeneity of TSS in 4.6% and 6.5% of lakes, respectively. Likewise, the environmental factors, i.e., fertilizer usage, domestic wastewater, industrial wastewater, precipitation, wind speed and Normalized Difference Vegetation Index (NDVI) exhibited a significant correlation with interannual TSS in 38, 21, 20, 11, 17 and 15 of the 91 basins, respectively. This analysis indicated that only precipitation and fertilizer usage were significantly (p < 0.05) related to the spatial distribution of TSS. The relative contributions of the six factors to the interannual TSS changes were varied in different basins. Overall, the NDVI (the representation of vegetation cover) had a high mean contribution to the interannual TSS changes with an average contribution of 7.2%, and contributions of fertilizer were varied greatly among the basins (0.01%–68%). Human activities (fertilizer usage, domestic wastewater, industrial wastewater) and natural factors (precipitation, wind speed and NDVI) played relatively important roles to TSS changes in 14 and 15 of the 91 basins, respectively. Beyond the six factors in this study, other unanalyzed factors (such as lake depth and soil texture) also had some impacts on the distribution of TSS in the study area.

A remote sensing approach to ascertain spatial and temporal variations of seawater quality parameters in the coastal area of Bay of Bengal, Bangladesh

Sea surface temperature (SST), surface chlorophyll (SChl), Sea surface salinity (SSS), and total suspended solids (TSS) are some critical seawater quality parameters (SWQP) in the Bay of Bengal (BoB) of Bangladesh. The research objectives were to investigate the distribution of SST, SChl, SSS, and TSS in the Summer and Winter seasons of 2014, 2018, and 2020 and denominate the spatial and temporal variation of these parameters in the BoB. The MODIS-Aqua, VIIRS-SNPP level-3 ocean color, and Landsat 8 OLI-TIRS multitemporal images were used and the Geographical Information System (GIS), and Remote Sensing (RS) techniques were applied for interpreting and mapping the output. The results asserted that temporally in the Summer season SChl and SSS increased by 11.02% and 7.96% respectively and TSS decreased by 14.25% from 2014 to 2020. On the other hand, in the Winter season, SST and SSS decreased by 3.37% and 3.38% respectively and SChl and TSS increased by 2.32% and 70.95% respectively from 2014 to 2020. Besides, in the Summer season, the maximum values of SST, SChl, and TSS were 30.16 °C, 2.61 mg/m3, 268.45 mg/l respectively and in the Winter season, the maximum values were 25.06 °C, 2.93 mg/m3, 192.31 mg/l respectively. Spatially, all the maximum values of SST, SChl, and TSS were concentrated in areas near the coastline. Contrary, the maximum values of SSS were 29.01 ppt and 31.21 ppt in the Summer and Winter seasons respectively and both values were coagulated in the open sea area. Seasonally, The SST and TSS were higher in the Summer season and SChl and SSS were higher in the Winter season for all the years in the BoB.

Determining effective water depth for total suspended solids (TSS) mapping using PlanetScope imagery

ABSTRACT The rapid development of remote sensing technology has increased the possibility to produce a spatially explicit estimation of Total Suspended Solids (TSS). However, factual information regarding the effective depth of waters where TSS can be effectively mapped using remote sensing data is rare. This information is essential to determine the effective depth of TSS mapping and the effect of the water column on the representativeness of the estimation results. This study aimed to (1) determine the effective water depths of TSS mapping using PlanetScope imagery, (2) map the spatial distribution of TSS at every effective depth using PlanetScope imagery, and (3) analyse the spatial distribution of the mapped TSS based on the best empirical modelling for every effective depth. PlanetScope image offered new opportunities in high spatial resolution remote sensing with daily revisit time. Four single bands of PlanetScope images (blue, green, red, and near-infrared) – corrected to the Bottom of Atmosphere (BOA) reflectance, 12 band ratios, and four Principal Component bands (PC-band) were inputted to the determination process of the effective water depths. Empirical modelling between the in-situ TSS at each effective water depth andures what was the issue, wasnt able to o PlanetScope pixels at the corresponding locations was conducted. However, only image bands that exceeded the significance limit (r) were used for modelling using linear, exponential, logarithmic, second-order polynomial, or power regressions. The results showed that the band ratios of PlanetScope images could record TSS up to the effective depth of 1.8 m. The best empirical modelling in each effective depth of waters was the band ratio which is dominated by the contribution of the blue bands (B1), red (B3), and NIR (B4). B4/B3 bands combination produced TSS information at the effective depths of 0–0.2 and 0–0.4 m, B3/B4 bands at 0–0.6 and 0–0.8 m, B1/B4 bands at 0–1 and 0–1.2 m, and B1/B3 bands at 0–1.4, 0–1.61, and 0–1.8 m. For all effective depths, the spatial distribution pattern of TSS in the study site (Menjer Lake, Central Java, Indonesia) showed that high concentrations evenly spread along the edge and became increasingly lower to the centre of the lake. Meanwhile, the vertical distribution showed that the deeper the cumulative water depth, the higher the TSS.

Development of Empirical Model of Total Suspended Solid (TSS) by using Landsat 8 on the Coast of Bekasi Regency

The Coastal area is transitional areas between terrestrial and marine ecosystems which are still affected by changes on land and in the sea. Various activities carried out on the coast make this area vulnerable to environmental changes that originate from natural phenomena and human activities. The north coast of Bekasi is prone to water quality degradation due to its proximity to Jakarta Bay and the mouth of the Citarum River to the Java Sea. The decline in the quality of Bekasi coastal waters can be measured by several parameters such as salinity, turbidity, brightness, chlorophyll concentration and Total Suspended Solid (TSS), the presence of organic or inorganic material. Landsat 8 can estimate the concentration and distribution of TSS spatially and temporally. This study aims to develop an empirical model for estimating TSS concentrations in the coastal area of Bekasi Regency by using Landsat 8 data. This method used a combination regression from five channels. The results showed there are four empirical models with a value of R2 of 0.5. The calculation of the accuracy value using RMSE is still high, which is around 100, but the construction of this model is better than the previous algorithm. Another alternative is to use multiple linear regression to see the relationship between the interaction variables of each band and the TSS concentration.

INTERSEASONAL VARIABILITY IN THE ANALYSIS OF TOTAL SUSPENDED SOLIDS(TSS) IN SURABAYA COASTAL WATERS USING LANDSAT-8 SATELLITE DATA

The spatial and temporal capabilities of remote sensing data are very effective for monitoring the value of total suspended solids(TSS) in water using optical sensors. In this study,TSS observations were conductedin the westseason, transition season 1, east season, and transition season 2 in 2018 and 2019. Landsat 8 image data wereused,extracted into TSS values using a semi-analytic model developed in the Mahakam Delta, East Kalimantan, Indonesia. The TSS data obtained were then analysed for distribution patterns in each season. The sample points were randomly scattered throughout the study area. The TSS distribution pattern in the west season showeda high concentration spread over the coastal area to theoff sea, while the pattern in the east season only showeda high concentration inthecoastal areas. Transitional seasons1 and 2 showed different patterns of TSS distribution in 2018 and 2019, with more varied values. The distribution of TSS is strongly influenced by the season. Observation of each cluster resultedin the conclusion thathuman activity and the rainfall rate can affect the concentration of TSS.

Dynamics Of Total Suspended Solid (TSS) Around Coral Reef Beach Damas, Trenggalek

Total suspended solids (TSS) are sediment material that floats in the water column that moves without touching the water bed, influenced by input from land, river flow, and water oceanography factors. TSS is closely related to sedimentation, which can harm aquatic ecosystems, especially coral reefs. This research was conducted using TSS data as well as flow data for each season (May, June, October 2019, February and March 2020) to know the distribution of suspended solids concentration, knowing the dynamics of changes in TSS concentrations on Damas Beach by season, and to determine the relationship TSS with the growth of coral reefs at Damas Beach. TSS levels in Damas waters are quite high, which can be indicated by the turbid waters. TSS levels in March 2020 showed dominating results with a range of 37.8–72.6 mg/L and an increase in the range of 72.7-145 mg/L. The highest distribution of TSS on Damas Beach is found in the Rainy season.

Monitoring Area and Health Changes of Mangrove Forest Using Multitemporal Landsat Imagery in Taman Hutan Raya Ngurah Rai, Bali Province

The mangrove forest is a very productive ecosystem, both economically and ecologically. Mangrove forests can protect settlements, buildings, and agriculture on the coast from strong winds or seawater intrusion, support the livelihoods of coastal communities and store high carbon stocks. Regardless of its role, the Taman Hutan Raya Ngurah Rai Mangrove Forest continues to be threatened by human activities. This study aims to monitor changes in the area, health, and water quality of mangrove forests. The data used are Landsat 7 ETM + imagery and Landsat 8 OLI in 2010-2020. We used NDVI vegetation indices to analyze mangrove health and Total Suspended Solid (TSS) to investigate the water quality of the mangrove forest. Temporal water quality parameters are obtained by using the TSS algorithm on Landsat imagery. The results showed variations in mangrove forest area changes, NDVI values, and water quality. In 2010 - 2015 Mangrove Forest Area increase by 117.72 ha but decrease in 2015-2020 by 96.21 ha. Mangrove health was also improved in 2010-2015 but the decline in 2015-2020. Meanwhile, mangrove forest water quality seen from the TSS distribution tends to grow from 2010 to 2020.

Aplication of Landsat 8 Oli for the total suspended solid (TSS) mapping in the Tri An reservoir, Dong Nai province

Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies. Total suspended solid (TSS) is an important water quality parameter and a surrogate for the water clarity. It can be used as the indicator of sediment in the reservoir, which usually consists of silt, fine sand and microorganisms. This study aimed to utilize the remote sensing technology, in particular Landsat 8 Operational Land Imager (Landsat 8 OLI), to determine the amount of TSS concentration as well as the spatial distribution of TSS concentration in the surface water of the Tri An reservoir. The relationship between field TSS data collected in March, 2020 and the reflectance values of the the Landsat 8 Oli images was investigated. Results showed that there was a strong linear relationshiop between TSS concentration and the reflectance of the red and near infrared reflectance bands from the Landsat 8 Oli (r ranged from 0.58–0.93), in which the ratio of the red band produced the best correlation with the TSS (r = 0.93, with a standard error of 0.6–1.39 mg/L). Based on the linear regression equation, the TSS concentration calculated from the red reflectance values was used for mapping the spatial distribution of TSS in the surface water of the Tri An reservoir. Our results confirmed the accuracy and potential of using the single band from Landsat 8 OLI for mapping the spatial distribution of TSS in the Tri An reservoir.