Coral reefs are one of the prominent marine ecosystems in the world. Coral reefs are facing threats from both natural and anthropogenic factors. Monitoring, protecting and studying these ecosystems are considered as a complex process because they are underwater features. Remote sensing can be quite useful in this by providing huge amount of database of satellite images. Landsat series have been providing satellite data for last 50 years and now it is one of the large databases providing satellite imageries. Accurate processing of these images can increase the accuracy of coral reef information extraction from these images. Classification is one of the important processes that can give adequate and precise information about coral reefs. This study is intended to compare various supervised classification techniques available for extraction of information from the image and to suggest best of them. Maximum Likelihood and Support Vector Machine have proven to be good classification module that can be used to classify Landsat Images to coral reef detection and monitoring.
By 2050 most parts of India will be water stressed zones as most of the water resources are under heavy stress due to increasing nutrient contamination in their waters. In this scenario, studying the changes occurring in the freshwater nutrient contamination levels over a temporal scale is extremely important. This study focuses on monitoring the changes occurring in the nutrient contamination levels over a decade in a large reservoir known as Nagarjuna Sagar (NS) using remote sensing data. In this study, Landsat (5 & 8) data for the year 2005year , 2009year , 2015 data for the years 2016 and 2018 is used to study nutrient contamination in NS. The spatial spread of chlorophyll -a (chl-a) area is used as a proxy to estimate the extent of nutrient contamination in NS. In this study, only October images of NS are used as they exhibit the maximum spatial spread of Chl-a and hence help assess the contamination levels over the period 2005 -2018. The analysis shows that during this period, chl-a spatial spread area has increased from 21 Km 2 to 205 Km 2 , indicating a decrease in water quality in the reservoir. The study shows that this is accompanied by an increase in the agricultural land use area by 1000 Km 2 in addition to a steep increase in the use of agricultural inputs, primarily fertilisers like urea, P and K. Thus, while the combined effect of excessive usage of fertilizers with agricultural intensification has increased crop yields, it has also contributed to damaging the freshwater resources.
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