Lidar-facilitated volunteered geographic information for topographic change detection

Lidar-facilitated volunteered geographic information for topographic change detection


Acquisition of volunteered geographic information (VGI) or geographic crowdsourcing has gained increased attention from academia in the last decade, especially for topographic change detection, collaborative mapping and natural hazard monitoring. By means of VGI we can collect positional data and georeferenced text, messages, photos or other information, e.g. by tagging existing information with geographical location.

Different approaches can be used to motivate citizens and professionals to participate in VGI, while the main motivation is usually a desire to cooperate in a worthy cause. Better data quality can be achieved, if together with laymen as data contributors, experts are cooperating.

Topographic maps and data cover entire states. In the A4C4 quality requirements scheme (Authority, Accuracy, Availability, Actuality; Completeness, Coverage, Consistency, Correctness), VGI wins in comparison with expert topographic data only in Actuality and conditionally in Correctness, but this is very significant for the Surveying and Mapping Authorities (SMAs).

European SMAs renew topographic data periodically, e.g. once in every 3 years. In order to achieve high and geographically homogeneous Actuality of VGI input at any time (i.e. continuously), SMAs have to attract data contributors all over their countries. Therefore, the main goals of this research are (1) to empower volunteers for easy and quick data collection, and (2) to empower geodetic professionals to process these data with photogrammetric quality. A term facilitated volunteered geographic information was introduced, which describes the fact that the collection of VGI can be accelerated if the beneficial institution like SMA, supports volunteers e.g. with simple and user-friendly applications such as digital mapping interfaces or topographic data browsers.

When VGI, especially volunteered photos are crossed with complementary georeferenced big data, e.g. with lidar point clouds or photogrammetrically derived digital surface models (lidar-like data) of whole countries or satellite images, new research directions emerge. Given the potentials offered by VGI and volunteered photos collection, the following three beyond state-of-the-art research problems arise:

CENTRAL PROBLEM – How to optimize the methodology of topographic map updating to involve arbitrary VGI, single volunteered non-metric photos, lidar or lidar-like data and satellite images?

CONTEXTUAL PROBLEM – How to support volunteers in the facilitated VGI, and in the volunteered non-metric photo collection for the purpose of full quality photogrammetric map updating, (1) for different topographical changes e.g. of road network, buildings, land use and land cover, and (2) at different national topographic map scales of e.g. 1:5000 vs. 1:50.000?

TECHNOLOGICAL PROBLEM – Specifically, (1) how to photogrammetrically orientate and georeference a single non-metric volunteered photo made by amateur camera or mobile phone, and (2) how to extract and map 3D topographic changes from such an amateur photo only with the help of lidar or lidar-like data?

Topographic map updating is usually done by photogrammetric survey, where imagery used to detect changes is professional, i.e. metric, orientated, stereo (in pair), and vertical (aerial - from an airplane). The main objective of the proposed research is the development of optimal methodology for a topographic map updating based on a mashup of volunteered geographic data, volunteered amateur photos and professional lidar or lidar-like data. We can summarize this with the following hypothesis:

A topographic mashup of arbitrary VGI, volunteered photos, professional lidar or lidar-like data and/or satellite images can provide a professional standard quality input for 3D topographic change detection and mapping in the process of topographic map updating.