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Analysing landscape visibility

PixScape software is dedicated to the analysis of the landscape visibility from raster data. This software integrates the main functionalities available in standard GIS in this domain and offers other original features such as tangential view and multi-resolution analysis.

PixScape has been developed at the research laboratory ThéMA in Besançon (France).

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PixScape is open source and distributed under GPL license. The software is developped in Java and runs on any computer supporting Java 7 or later (PC under Linux, Windows, Mac...)
It runs also on cluster supporting OpenMPI for Java and on GPU card supporting CUDA.




Documentation

User manual

Manual: manuel-en.pdf

Sample data

Sample project for testing PixScape: sample_project.zip

Source code

PixScape is licenced under GPL. The source code can be downloaded from the sourcesup git repository:

git clone https://git.renater.fr/anonscm/git/pixscape/pixscape.git

References

Sahraoui Y., Clauzel C., Foltête J-C., 2021. A metrics-based approach for modeling covariation of visual and ecological landscape qualities, Ecological Indicators, 123, pp.107331.

Youssoufi S., Houot H., Vuidel G., Sophie Pujol S., Fred Mauny F., Foltete J-C., 2020. Combining visual and noise characteristics of a neighborhood environment to model residential satisfaction: an application using GIS-based metrics, Landscape and Urban Planning 103932.

Foltête J-C., Ingensand J., Blanc N., 2020. Coupling crowd-sourced imagery and visibility modelling to identify landscape preferences at the panorama level, Landscape and Urban Planning 103756.

Karasov O., Heremans S., Külvik M., Domnich A., Chervanyov I., 2020. On how crowdsourced data and landscape organisation metrics can facilitate the mapping of cultural ecosystem services: An Estonian case study, Land 9: 158.

Sahraoui Y., Vuidel G., Joly D, Foltête J-C., 2018. Integrated GIS software for computing landscape visibility metrics, Transactions in GIS, 22 (5), 1310-1323.

Hilal M., Joly D., Roy D., Vuidel G., 2018. Visual structure of landscapes seen from built environment, Urban Forestry & Urban Greening, 32, 71-80.

Sahraoui Y., Youssoufi S., Foltête J-C., 2016. A comparison of in situ and GIS landscape metrics for residential satisfaction modeling, Applied Geography, 74, 199-210.

Sahraoui Y., Clauzel C., Foltête J-C., 2016. Spatial modelling of landscape aesthetic potential in urban-rural fringes, Journal of Environmental Management, 181, 623-636.

Contact

About the software application and its use gilles.vuidel@univ-fcomte.fr