Assessment of Inland Water Quality In Banjar Regency Using Remotely Sensed Satellite Image

Autor: Rony Riduan, Riza Miftahul Khair, Andre Anantama Irawan, Farrel Alta Ferisza Siregar
Rok vydání: 2022
DOI: 10.5281/zenodo.7336356
Popis: The main environmental issues in Banjar Regency Indonesia are the handling of residential wastewater and environmental degradation due to mining activities. Efforts to monitor and analyze water quality status with a large area and diverse land use require a lot of time and money. This research will help provide alternative solutions for predicting the quality of inland waters using remote sensing satellite image interpretation. The research was conducted to obtain the distribution pattern of water quality parameters such as Turbidity, TSS (Total Suspended Solid), organic CDOM (Colored Dissolved Organic Matter Absorption), and Chlorophyll-a (Chl-a). These four parameters are generally monitored through field sampling which is time-consuming and costly. Remote sensing provides the possibility to provide water quality information over a wide area and identify trends in changing water quality patterns through historical data. The research was conducted through the interpretation of Sentinel-2 satellite imagery and other sources such as Landsat and SRTM. Data were collected over the last 5 years and processed using the GEE (Google Earth Engine), ESASNAP (European Space Agency - Sentinel Application Platform), and QGIS applications. The interpretation results for current conditions are calibrated using field measurement data, then mapped to display patterns of water quality parameter conditions spatially and temporally. The last step is to perform spatial statistical analysis and the trend of changes in water quality using the GEODA application. The distribution of water quality parameter values shows various patterns for inland waters in Banjar Regency but tends to increase in locations close to residential and agricultural areas. All water quality parameters reviewed also show an increasing trend in the last 5 years according to the analysis period.
Databáze: OpenAIRE