A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones
Identifieur interne : 000322 ( Main/Exploration ); précédent : 000321; suivant : 000323A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones
Auteurs : K. Anderson [Royaume-Uni] ; D. Griffiths [Royaume-Uni] ; L. Debell [Royaume-Uni] ; S. Hancock [Royaume-Uni] ; J. P. Duffy [Royaume-Uni] ; J. D. Shutler [Royaume-Uni] ; W. J. Reinhardt [Royaume-Uni] ; A. Griffiths [Royaume-Uni]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding ‘scheme blocks’ framework was used to build the application (‘app’), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing–a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for ‘UAV toolkit’ (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).
Url:
DOI: 10.1371/journal.pone.0151564
PubMed: 27144310
PubMed Central: 4856374
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>This manuscript describes the development of an android-based smartphone application for capturing aerial photographs and spatial metadata automatically, for use in grassroots mapping applications. The aim of the project was to exploit the plethora of on-board sensors within modern smartphones (accelerometer, GPS, compass, camera) to generate ready-to-use spatial data from lightweight aerial platforms such as drones or kites. A visual coding ‘scheme blocks’ framework was used to build the application (‘app’), so that users could customise their own data capture tools in the field. The paper reports on the coding framework, then shows the results of test flights from kites and lightweight drones and finally shows how open-source geospatial toolkits were used to generate geographical information system (GIS)-ready GeoTIFF images from the metadata stored by the app. Two Android smartphones were used in testing–a high specification OnePlus One handset and a lower cost Acer Liquid Z3 handset, to test the operational limits of the app on phones with different sensor sets. We demonstrate that best results were obtained when the phone was attached to a stable single line kite or to a gliding drone. Results show that engine or motor vibrations from powered aircraft required dampening to ensure capture of high quality images. We demonstrate how the products generated from the open-source processing workflow are easily used in GIS. The app can be downloaded freely from the Google store by searching for ‘UAV toolkit’ (UAV toolkit 2016), and used wherever an Android smartphone and aerial platform are available to deliver rapid spatial data (e.g. in supporting decision-making in humanitarian disaster-relief zones, in teaching or for grassroots remote sensing and democratic mapping).</p>
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<biblStruct><analytic><author><name sortKey="Ait Aider, O" uniqKey="Ait Aider O">O Ait-Aider</name>
</author>
<author><name sortKey="Andreff, N" uniqKey="Andreff N">N Andreff</name>
</author>
<author><name sortKey="Lavest, J" uniqKey="Lavest J">J Lavest</name>
</author>
<author><name sortKey="Martinet, P" uniqKey="Martinet P">P Martinet</name>
</author>
<author><name sortKey="Leonardis, A" uniqKey="Leonardis A">A Leonardis</name>
</author>
<author><name sortKey="Bischof, H" uniqKey="Bischof H">H Bischof</name>
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<author><name sortKey="Pinz, A" uniqKey="Pinz A">A Pinz</name>
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<affiliations><list><country><li>Royaume-Uni</li>
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<tree><country name="Royaume-Uni"><noRegion><name sortKey="Anderson, K" sort="Anderson, K" uniqKey="Anderson K" first="K." last="Anderson">K. Anderson</name>
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<name sortKey="Debell, L" sort="Debell, L" uniqKey="Debell L" first="L." last="Debell">L. Debell</name>
<name sortKey="Duffy, J P" sort="Duffy, J P" uniqKey="Duffy J" first="J. P." last="Duffy">J. P. Duffy</name>
<name sortKey="Griffiths, A" sort="Griffiths, A" uniqKey="Griffiths A" first="A." last="Griffiths">A. Griffiths</name>
<name sortKey="Griffiths, D" sort="Griffiths, D" uniqKey="Griffiths D" first="D." last="Griffiths">D. Griffiths</name>
<name sortKey="Hancock, S" sort="Hancock, S" uniqKey="Hancock S" first="S." last="Hancock">S. Hancock</name>
<name sortKey="Reinhardt, W J" sort="Reinhardt, W J" uniqKey="Reinhardt W" first="W. J." last="Reinhardt">W. J. Reinhardt</name>
<name sortKey="Shutler, J D" sort="Shutler, J D" uniqKey="Shutler J" first="J. D." last="Shutler">J. D. Shutler</name>
</country>
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