The use of remote sensing data, such as satellite imageries and aerial photos, allows us to map the variability of terrain properties, such as vegetation, water, geology, both in space and time. This paper suggests an integration of the classification of the landslides for the region of East Sikkim and the images are displayed through a web portal. The classification is done using k-means and k nearest neighbor classifier and the better one is selected to classify the landslides and then uploaded on a web portal.

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A node localization algorithm using the Jaya algorithm (JA) and range-free method of reliable anchor pair (RAP) selection approach is proposed to determine the position of target nodes or unknown devices in isotropic, O-shaped, and S-shaped anisotropic wireless sensor networks (WSNs). The reliable anchor selection method separates anchor nodes into prime anchor node pairs, subprime anchor node pairs, and unreachable anchor node pairs to determine the distance between anchor node pairs and target nodes. The nature-inspired Jaya algorithm is used to predict the position of the target node. The presented work is compared with the existing localization methods, including DV(Distance Vector)-maxHop, PSO (Particle Swarm Optimization), and QSSA (Quantized Salp Swarm Algorithm) based localization algorithms. The proposed approach increases localization accuracy regarding the number of anchor nodes and node density. The proposed algorithm also looks at how the degree of irregularity and computation time affect the performance.