Abstract

The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. <br><br> Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

Highlights

  • Some of the methods reviewed were based on the comparison of satellite and aerial imagery, and in some cases the methods are based on the comparison of elevation models from different periods (Im et al, 2008)

  • Since the classification is based on the radiometric characteristics we correct the classification results using the nDSM

  • In the best case scenario there will be a full match between NTDB and the Automatic Buildings Extraction (ABE)

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Summary

INTRODUCTION

Motivation In recent years, an innovative approach was developed and implemented for change detection. This approach is based on advanced R&D activities were carried out to automatically update the NTDB (National Topographic Data Base) in Israel.

General
Case Studies
Remote Sensing Procedures
Segmentation
Classification
Correct Classification Using Height Information
Fused Classification to Segmentation
Compare Objects
Delineate Vector Objects
RESULTS
SUMMERY

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