References of "Lhoest, Simon"
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See detailHuman in the forest: Long-term interactions, lifestyle and ecosystem services in Central Africa
Gillet, Pauline ULiege; Lhoest, Simon ULiege; Morin-Rivat, Julie et al

Poster (2016, May 20)

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See detailForest Resources Management: Axis, background and illustration of a research project
Lhoest, Simon ULiege

Conference (2015, December 10)

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See detailInteractions between forests and youth in the Walloon Region (Belgium)
Lhoest, Simon ULiege

Conference given outside the academic context (2015)

Description of main types of forests in the Walloon Region, roles of youth and its interaction with forest management in Wallonia, links between forest management and environmental stakes as climate ... [more ▼]

Description of main types of forests in the Walloon Region, roles of youth and its interaction with forest management in Wallonia, links between forest management and environmental stakes as climate change and biodiversity erosion, importance of the involvement of population in forest resources protection. [less ▲]

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See detailWiMUAS: New inventory method to perform wildlife counts with UAS and review the large datasets
Linchant, Julie ULiege; Lhoest, Simon ULiege; Semeki, Jean et al

Conference (2015, October 13)

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See detailHow Many Hippos (HOMHIP): Algorithm for automatic counts of animals with infrared thermal imagery from UAV
Lhoest, Simon ULiege; Linchant, Julie ULiege; Quevauvillers, Samuel ULiege et al

Conference (2015, October 02)

The common hippopotamus (Hippopotamus amphibius L.) is part of the animal species endangered because of multiple human pressures. Monitoring of species for conservation is then essential, and the ... [more ▼]

The common hippopotamus (Hippopotamus amphibius L.) is part of the animal species endangered because of multiple human pressures. Monitoring of species for conservation is then essential, and the development of census protocols has to be chased. UAV technology is considering as one of the new perspectives for wildlife survey. Indeed, this technique has many advantages but its main drawback is the generation of a huge amount of data to handle. This study aims at developing an algorithm for automatic count of hippos, by exploiting thermal infrared aerial images acquired from UAV. This attempt is the first known for automatic detection of this species. Images taken at several flight heights can be used as inputs of the algorithm, ranging from 38 to 155 meters above ground level. A Graphical User Interface has been created in order to facilitate the use of the application. Three categories of animals have been defined following their position in water. The mean error of automatic counts compared with manual delineations is +2.3% and shows that the estimation is unbiased. Those results show great perspectives for the use of the algorithm in populations monitoring after some technical improvements and the elaboration of statistically robust inventories protocols. [less ▲]

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See detailWiMUAS: A tool to review wildlife data from various flight plans
Linchant, Julie ULiege; Lhoest, Simon ULiege; Quevauvillers, Samuel ULiege et al

Conference (2015, October 02)

To get around UAS limitations and propose a viable solution for wildlife monitoring, the development of new inventory methods is needed. However, most authors use the classic systematic transect method as ... [more ▼]

To get around UAS limitations and propose a viable solution for wildlife monitoring, the development of new inventory methods is needed. However, most authors use the classic systematic transect method as data processing and statistics are easier. We thus created an application to process data from every type of flight plan and to help detect and compare observations on large datasets. WiMUAS is a small software compatible with the open-source QGIS© that allows the creation of visual maps compatible with geographical information systems based on telemetry data and payload parameters to estimate the covered area. The application also has a slider for animal detection that allows multiple observers to record and compare their results for accurate counts. We then tested it on data from a trial realized on savannah animal populations in Democratic Republic of Congo using the Falcon UAS. We created a new type of flight plan, a rosette-shaped design that can be covered in three flights,.and repeated it twice. More than 5000 images were collected during the six flights. Image projection gives an area of 12,4 km2 for the first trial and of 12,1 km2 for the second. The mean sampling rate for both test is 6,1 %. Observers spotted buffaloes, hippos, warthogs and various antelopes with different success over an average rate of 8 images reviewed per minute. Resulting densities observed by the three observers are similar for each test (coefficient of variation 6,9 and 8,6 % respectively) but mean densities vary a lot between the two trials (23,8 and 6,5 animals/km2 respectively). [less ▲]

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See detailContribution au monitoring de populations d'hippopotame commun (Hippopotamus amphibius L.) par l'utilisation de la technologie drone (Parc National de la Garamba, République Démocratique du Congo)
Lhoest, Simon ULiege

Master's dissertation (2015)

In an era of indisputable decline in populations of large wildlife species, setting up regular and efficient monitoring methods is essential. Because of the difficulties associated with conventional ... [more ▼]

In an era of indisputable decline in populations of large wildlife species, setting up regular and efficient monitoring methods is essential. Because of the difficulties associated with conventional pedestrian and aerial survey procedures, the development of UAV technology turns out to be a potentially interesting alternative. This work focuses on monitoring common hippopotamus (Hippopotamus amphibius L.) with the use of this innovative tool. The search for flight parameters optimization to maximize detection and visibility of animals showed a very small decrease in detection rate and certainty of counts with an increasing flying height and a high variability linked to operators realizing observations. It is recommended to fly at a height of 140 meters above ground level, between 6:30 and 8:45 am at the end of the dry season, with cloud cover and wind as low as possible. Three counts correction methods are proposed to estimate the total population from the only emerged observed animals. The average overall correction factor is 1.252. An attempt to describe the demography of a group by individuals length measurements was also implemented. It allowed to obtain a mean distribution of hippos in three age classes, even if results are not extremely accurate. Finally, an algorithm for the semi-automatic count of hippos on thermal infrared imagery was developed, and brought to a mean error of +3.9%. Taking into account the recommendations proposed in this study for the development of inventories protocols would help dealing with the practical constraints of conventional monitoring methods. [less ▲]

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Peer Reviewed
See detailHOW MANY HIPPOS (HOMHIP): Algorithm for automatic counts of animals with infra-red thermal imagery from UAV
Lhoest, Simon ULiege; Linchant, Julie ULiege; Quevauvillers, Samuel ULiege et al

in International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences (2015), XL-3/W3

The common hippopotamus (Hippopotamus amphibius L.) is part of the animal species endangered because of multiple human pressures. Monitoring of species for conservation is then essential, and the ... [more ▼]

The common hippopotamus (Hippopotamus amphibius L.) is part of the animal species endangered because of multiple human pressures. Monitoring of species for conservation is then essential, and the development of census protocols has to be chased. UAV technology is considering as one of the new perspectives for wildlife survey. Indeed, this technique has many advantages but its main drawback is the generation of a huge amount of data to handle. This study aims at developing an algorithm for automatic count of hippos, by exploiting thermal infrared aerial images acquired from UAV. This attempt is the first known for automatic detection of this species. Images taken at several flight heights can be used as inputs of the algorithm, ranging from 38 to 155 meters above ground level. A Graphical User Interface has been created in order to facilitate the use of the application. Three categories of animals have been defined following their position in water. The mean error of automatic counts compared with manual delineations is +2.3% and shows that the estimation is unbiased. Those results show great perspectives for the use of the algorithm in populations monitoring after some technical improvements and the elaboration of statistically robust inventories protocols. [less ▲]

Detailed reference viewed: 104 (42 ULiège)
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Peer Reviewed
See detailWIMUAS: Developing a tool to review wildlife data from various UAS flight plans
Linchant, Julie ULiege; Lhoest, Simon ULiege; Quevauvillers, Samuel ULiege et al

in International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences (2015), XL-3/W3

To get around UAS limitations and propose a viable solution for wildlife monitoring, the development of new inventory methods is needed. However, most authors use the classic systematic transect method as ... [more ▼]

To get around UAS limitations and propose a viable solution for wildlife monitoring, the development of new inventory methods is needed. However, most authors use the classic systematic transect method as data processing and statistics are easier. We thus created an application to process data from every type of flight plan and to help detect and compare observations on large datasets. WiMUAS is a small software compatible with the open-source QGIS© that allows the creation of visual maps compatible with geographical information systems based on telemetry data and payload parameters to estimate the covered area. The application also has a slider for animal detection that allows multiple observers to record and compare their results for accurate counts. We then tested it on data from a trial realized on savannah animal populations in Democratic Republic of Congo using the Falcon UAS. We created a new type of flight plan, a rosette-shaped design that can be covered in three flights,.and repeated it twice. More than 5000 images were collected during the six flights. Image projection gives an area of 12,4 km2 for the first trial and of 12,1 km2 for the second. The mean sampling rate for both test is 6,1 %. Observers spotted buffaloes, hippos, warthogs and various antelopes with different success over an average rate of 8 images reviewed per minute. Resulting densities observed by the three observers are similar for each test (coefficient of variation 6,9 and 8,6 % respectively) but mean densities vary a lot between the two trials (23,8 and 6,5 animals/km2 respectively). [less ▲]

Detailed reference viewed: 86 (26 ULiège)