Our image analysts use unique techniques of advanced object-based classification to create elevation models with land consumption patterns, path loss, signal attenuation and re-use details. We employ tried and tested Photogrammetric methods to create a 3D grid to represent the surface of the earth. Our Remote Sensing professionals with cross-domain expertise, process several manual and semi-automated exercises for Image Classification to generate reliable clutter data using various resolutions.
Our classified clutter data generation procedure options are primarily satellite-based, derived from remotely sensed imagery and geodata. By classifying the areas into clutter classes with mappable global-consistent classification scheme, we simplify the Radio and Telecommunication networking application planning. Clove has been closely following the new and exciting field of Geographic Object-Based Image Analysis (GEOBIA). Pixel-based methods tend to break down for imagery below 5m resolution, GEOBIA offers an alternative that aggregates pixels into homogeneous areas for subsequent classification. Setting up the criteria for classification requires an experienced image analyst. For a truly accurate classification, ground truth should be collected in the field. If it’s not available, reliable information about local land use (from someone familiar with the area) is the next best alternative. Our improved land management practices are used for applications like Bio-diversity activities, climate monitoring, habitat identification and land conversion decision making.