Assessing the efficacy of Landsat-8 OLI imagery derived models for remotely estimating chlorophyll-a concentration in the Upper Ganga River, India

ABSTRAKWaduk Gajah Mungkur (WGM) adalah bendungan buatan yang memiliki luas genangan maksimum 8800 ha, terletak di Desa Pokoh Kidul, Kecamatan Wonogiri, Kabupaten Wonogiri. Kondisi perairan WGM dipengaruhi oleh faktor klimatologis, fisik, dan aktivitas manusia yang dapat menyumbang nutrisi sehingga mempengaruhi status trofiknya. Tujuan dari penelitian ini adalah mengkaji kemampuan citra Landsat 8 OLI untuk memperoleh parameter-parameter yang digunakan untuk menilai status trofik, menentukan dan memetakan status trofik yang diperoleh dari citra Landsat 8 OLI, dan mengevaluasi hasil pemetaan dan manfaat citra penginderaan jauh untuk identifikasi status trofik WGM. Identifikasi status trofik dilakukan berdasarkan metode Trophic State Index (TSI) Carlson (1997) menggunakan tiga parameter yaitu kejernihan air, total fosfor, dan klorofil-a. Model yang diperoleh berdasar pada rumus empiris dari hasil uji regresi antara pengukuran di lapangan dan nilai piksel di citra Landsat 8 OLI. Model dipilih berdasarkan nilai koefisien determinasi (R2) tertinggi. Hasil penelitian merepresentasikan bahwa nilai R2 kejernihan air sebesar 0,813, total fosfor sebesar 0,268, dan klorofil-a sebesar 0,584. Apabila nilai R2 mendekati 1, maka semakin baik model regresi dapat menjelaskan suatu parameter status trofik. Berdasarkan hasil kalkulasi diperoleh distribusi yang terdiri dari kelas eutrofik ringan, eutrofik sedang, dan eutrofik berat yaitu pada rentang nilai indeks 50,051 – 80,180. Distribusi terbesar adalah eutrofik sedang. Hal tersebut menunjukkan tingkat kesuburan perairan yang tinggi dan dapat membahayakan makhluk hidup lain.Kata kunci: Waduk Gajah Mungkur, citra Landsat 8 OLI, regresi, TSI, status trofikABSTRACTGajah Mungkur Reservoir is an artificial dam that has a maximum inundated areas of 8800 ha, located in Pokoh Kidul Village, Wonogiri Regency. The reservoir’s water conditions are affected by climatological and physical factors, as well as human activities that can contribute to nutrients that affect its trophic state. This study aimed to assess the Landsat 8 OLI capabilities to obtain parameters that are used to determine its trophic state, identifying and mapping the trophic state based on parameters derived from Landsat 8 OLI, and evaluating the results of the mapping and the benefits of remote sensing imagery for identification of its trophic state. Identification of trophic state is based on Trophic State Index (TSI) Carlson (1997), which uses three parameters there are water clarity, total phosphorus, and chlorophyll-a. The model is based on an empirical formula of regression between measurements in the field and the pixel values in Landsat 8 OLI. Model is selected on the highest value towards coefficient of determination (R2). The results represented that R2 of water clarity is 0.813, total phosphorus is 0.268, and chlorophyll-a is 0.584. If R2 close to 1, regression model will describe the parameters of the trophic state better. Based on the calculation the distribution consists of mild eutrophic, moderate eutrophic, and heavy eutrophic that has index values from 50.051 to 80.18. The most distribution is moderate eutrophication, and it showed the high level of trophic state and may harm other living beings.Keywords: Gajah Mungkur Reservoir, Landsat 8 OLI satellite imagery, regression, TSI, trophic state

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Retrieval and Evaluation of Chlorophyll-a Concentration in Reservoirs with Main Water Supply Function in Beijing, China, Based on Landsat Satellite Images

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094419 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4419

Author(s):

Yuequn Lai ◽

Jing Zhang ◽

Yongyu Song ◽

Zhaoning Gong

Keyword(s):

Remote Sensing ◽

Water Supply ◽

Chlorophyll A ◽

Phosphorus Concentration ◽

Landsat 8 ◽

Supply Function ◽

Estimation Model ◽

Nitrogen And Phosphorus ◽

Chlorophyll A Concentration ◽

Guanting Reservoir

Remote sensing retrieval is an important technology for studying water eutrophication. In this study, Guanting Reservoir with the main water supply function of Beijing was selected as the research object. Based on the measured data in 2016, 2017, and 2019, and Landsat-8 remote sensing images, the concentration and distribution of chlorophyll-a in the Guanting Reservoir were inversed. We analyzed the changes in chlorophyll-a concentration of the reservoir in Beijing and the reasons and effects. Although the concentration of chlorophyll-a in the Guanting Reservoir decreased gradually, it may still increase. The amount and stability of water storage, chlorophyll-a concentration of the supply water, and nitrogen and phosphorus concentration change are important factors affecting the chlorophyll-a concentration of the reservoir. We also found a strong correlation between the pixel values of adjacent reservoirs in the same image, so the chlorophyll-a estimation model can be applied to each other.

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

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-w11-67-2020 ◽

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.

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