Shoreline change studies in small-scale beaches require high-resolution satellite images. In this regard, high-resolution satellite images from Google Earth (GE) would be an alternative source however novel studies are needed to verify the effectiveness and the efficiency of applying those images for shoreline change detection in small-scale beaches. Addressing this gap, the current study attempts to develop a new method. Accuracies of delineated shorelines under different scenarios were used to develop relationships with digitizing methods and used eye-altitude to estimate the most effective, efficient and productive method. This was done using Digital Shoreline Analysis System (DSAS) in ArcGIS software. It was found that the eye-altitude influences on digitizing accuracy and it could be improved when increasing the zoom level of the image which is under investigation. Maximum zoom level (50 m) used in this study showed the highest accuracy in shoreline digitizing while the most productive eye-altitude for shoreline delineation was found as 300 m. The current study identified that GE coupled with DSAS tool in ArcGIS software can be used as an effective and efficient method for small-scale shoreline change analysis and it is suggested that this methodology could be adopted for other similar studies.

Estimation of shoreline change using satellite images is considered as a very effective method because the coastline is found highly dynamic. This study focuses to develop a methodology to detect shoreline changes using satellite imageries obtained from Google Earth platform. The study was carried out in north-east coastline of Jaffna in Sri Lanka. Shorelines from 2002 to 2017 were delineated on the multi-temporal satellite images in the Google Earth software by visual interpretation and change was detected using Digital Shoreline Analysis System in ArcGIS. Tidal variation, digitizing error, and geometric errors were considered to calculate the uncertainty. Mean End Point Rate, mean Shoreline Change Envelop, mean Net Shoreline Movement, and mean Weighted Linear Regression Rate were used as main shoreline change statistics. Result shows that there is net shoreline accretion of 6.13 ± 8.74 m with an annual rate of deposition of 0.5 m/year. During the study period, 76.12% of the observed shoreline is found accreted while the 23.88% of the shoreline is eroded. Mean Uncertainty of the shoreline is 3.73 ± 0.59 m. The study revealed that the satellite images from Google Earth platform can be used for time series analysis of shorelines after appropriate corrections.

Groundwater is one of the most important natural resources in the northern coastal belt of Sri Lanka, as there are no major water supply schemes or perennial rivers. Overexploitation, seawater intrusion and persistent pollution of this vital resource are threatening human health as well as ecosystems in the Jaffna Peninsula. Therefore, the main intent of the present paper is to apply geospatial techniques to assess the spatial variation of groundwater quality and availability for the sustainable management of groundwater in the coastal areas. The electrical conductivity (EC) and depth to water (DTW) of 41 wells were measured during the period from March to June 2014, which represents the dry period of the study area. Surface interpolation, gradient analysis, a local indicators of spatial autocorrelations (LISA) and statistical analysis were used to assess the quality and availability of groundwater. The results revealed that the drinking and irrigation water quality in the study area were poor and further deteriorated with the progression of the dry season. Good quality and availability of groundwater were observed in the western zone compared to other zones of the study area. A negative correlation was identified between depth to water and electrical conductivity in the western zone. Hence, relatively deep wells in the western zone of the study area can be used to utilize the groundwater for drinking, domestic and agricultural purposes. The outcomes of this study can be used to formulate policy decisions for sustainable management of groundwater resources in Jaffna Peninsula.

Most parts of the Southern coastal belt of Sri Lanka are fringed with shallow water coral reefs of high economic, ecological and socioeconomic attributes. Polhena, Madiha and Dondra are some of the places where the isolated coral reefs are located in this region. Descriptive details such as the extent, reef margins, and coral compositions of these reefs are lacking due to the difficulties of accessibility, harsh conditions and the lacking of trained expertise for reef mapping. Remote sensing can be used as a tool to identify the reef locations, spatial distribution, bottom nature, present status of the reef area for their effective management and conservation. In this research, bathymetry maps were produced using ‘Depth of Penetration’ method for Landsat7 ETM+ satellite images. Image band 1 (0.45-0.515μm), band2 (0.525-0.605μm), band3 (0.63-0.69μm) and band4 (0.75-0.9μm) have been used as main inputs of bathymetry mapping. Colour composites, classified images and manually digitized images were used to map the spatial pattern of the reefs. The image processing has been carried out with ILWIS 3.3 and ArcGIS 9.3 software. Created maps were validated using ground truth data which were taken during the field survey. The Pearson correlation coefficient (r=0.921) indicates that there is a high correlation between true depth and the calculated depth from the map. The standard error of the estimate is 0.85. According to the created GIS maps, maximum depth (1.83±0.79m) was recorded in Dondra reef while lowest depth (1.46±1.23 m) was recorded in Polhena reef. Depth of the madiha reef was 1.81±0.99 m. Highest reef area represented by the Polhena reef (240300 m2) while lowest area represented by the Madiha reef (51300 m2). Area of the Dondra reef was 85500 m2. Band 4 is the best for shallow (<4m) reef mapping and high resolution images are ideal for more detailed habitat mapping.DOI: http://dx.doi.org/10.4038/sljas.v19i0.7450 Sri Lanka J. Aquat. Sci. 19 (2014): 41-55

Last few decades the land-use pattern has changed in Matara District in Sri Lanka due to the influence of both natural and anthropogenic hazard impacts. These hazards have caused the interruption for social, economic and the environmental sectors in this area. Since the comprehensive field surveys are highly expensive, time consuming and requiring more human power the remote sensing satellite images can be used to map the changing pattern of land-use types over a large period of time. This study focuses on how far remote sensing data give the information on land-use pattern change as an effective information and communication technology in collaboration with GIS. The Medium resolution Lansdsat satellite images were used in this study because they are freely and readily available therein cost effective and highly efficient. The ground features have been extracted from the images in 1990, 1993, 2001, 2003, 2005, 2009 and 2014 respectively. Water body has been extracted using NIR band by using single band classification method while the vegetation cover was extracted by using Normalized Difference Vegetation Index (NDVI). Multiband image classification was also implemented for each year using Maximum Likelihood Classification. According to the results, the land-use pattern has changed over the last 24 years in a significant level. The accuracy of the Maximum Likelihood Classification is 84.43%.