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NON-TRIVIAL FEATURE DERIVATION FOR INTENSIFYING FEATURE DETECTION USING LIDAR DATASETS THROUGH ALLOMETRIC AGGREGATION DATA ANALYSIS APPLYING DIFFUSED HIERARCHICAL CLUSTERING FOR DISCRIMINATING AGRICULTURAL LAND COVER IN PORTIONS OF NORTHERN MINDANAO,PHILIPPINES
Image classification OBIA LiDAR Allometric relations Non-trivial feature derivations Euclidean transformation
2016/12/1
Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging ...
IMPROVING SEMI-GLOBAL MATCHING: COST AGGREGATION AND CONFIDENCE MEASURE
Dense Matching Digital Elevation Model Stereo Benchmark Accuracy
2016/7/4
Digital elevation models are one of the basic products that can be generated from remotely sensed imagery. The Semi Global Matching (SGM) algorithm is a robust and practical algorithm for dense image ...
PLAN4BUSINESS - A SERVICE PLATFORM FOR AGGREGATION, PROCESSING AND ANALYSIS OF URBAN AND REGIONAL PLANNING DATA
Spatial planning, integration engine analysis engine plan4business INSPIRE data heterogeneity data harmonisation
2014/4/24
The paper presents the main objectives of the plan4business project that aims to develop a service platform for integration, analysing
and presenting spatial planning data. The platform should serve...