Monitoring of Lake Water Quality Through Streamlit Web Application (Case Study: Lake Matano And Lake Towuti, South Sulawesi)

Lalu Muhamad Jaelani, Martanti Aji Pangestu

Abstract


The Indonesian government, through the National Medium Term Development Plan (RPJMN) 2015-2019, stated that water reservation, including the function of lakes, is one of the priorities. Lakes are not only functioned to maintain the ecological balance but also to provide water, protein, mineral, energy sources, and even tourism to support the community's economic growth. Lake Matano and Lake Towuti are designated as Nature Tourism Park areas. However, the lakes' environment is starting to be damaged. The damages exist in areas such as water-absorbent areas, lake borders, and lake waters. In addition, these damages increase the disaster risk. Therefore, to maintain the lake's sustainability, it is necessary to conduct research on the parameters of the condition of the fertility level of the lake waters. One of the parameters of the fertility level of the waters is chlorophyll-a. In the previous studies, observations of chlorophyll-a in Lake Matano and Lake Towuti have been carried out using Landsat-8. However, with these observations, a chlorophyll-a had not properly been monitored by using an application through web-based satellite imagery using web applications using the primary python programming language. The data for processing chlorophyll-a itself are obtained through the geemap library. Chlorophyll-a itself was processed using the existing algorithm. The current web application displays several features, namely the web application information and the results of the chlorophyll-a map. The results of the estimated value of chlorophyll-a range from 0 - 0.6 mg/m3. The minimum value of chlorophyll-a was found in 2014 which was 0.4 mg/m3, while the highest value of chlorophyll-a was found at 0.6 mg/m3 in 2016. The results of this chlorophyll-a analysis was categorized into oligotrophic waters with low fertility. 


Keywords


Chlorophyll-a; geemap; Jaelani Algorithm 2015; Landsat 8; Remote Sensing; Streamlit

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References


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DOI: http://dx.doi.org/10.12962/j24423998.v18i2.14396

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