Detection and Mapping of Spatial Distribution of Floating Algae in Batticaloa Lagoon, Sri Lanka Using Remote Sensing & GIS

Evanjalin Delina Jesudasan Prince, N D K Dayawansa, Ranjith Premalal De Silva

Abstract


This study intended to detect and map the spatial distribution of floating algae (FAg) in Batticaloa Lagoon in Sri Lanka using sub-pixel classification of satellite imagery and to assess the impact of land use/ land cover (LULC) and water quality in the lagoon surrounding on its spatial distribution.  Cloud free three Sentinel-2A satellite images were acquired for the dry period of May to September 2017. Since algae is mixed with water in most of the locations, mixed pixels were present in the images.  Hence, sub-pixel classification was used to detect the FAg. Near real time field measurements of selected water quality parameters were conducted in 30 locations in monthly interval for the period of March 2017 to February 2018 to develop a water quality index (WQI) and to identify its relationship with the presence of FAg. A buffer zone of 3 km was created around the lagoon to obtain LULC distribution to study their influence on FAg. Spatial coverage of FAg showed significant correlations (p<0.05, p< 0.01) with water quality of the lagoon in dry season. The developed WQI showed a strong inverse relationship with the coverage of FAg (r2 = 0.78) in dry season. Further, the locations with high (> 70%) and moderate (50-70%) level of algal infestation showed poor (< 50%) WQI, where the area was prone to urban and agricultural runoff discharges. However, the sampling locations confined to natural habitats were free from FAg and showed better (> 50%) WQI. The study shows that the sub-pixel classification has the potential to detect and map the level of spreading of FAg which can be linked to overall water quality of the lagoon represented by WQI and the LULC in the lagoon surrounding.

Keywords


Floating Algae, Land use/Land cover, Spatial coverage, Sub-pixel classification, Water quality index

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v17.2.1389

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