Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Zaragozí, Benito; Belda, Antonio; Gimenez, Paulo J. A.; Navarro, J.T.; Bonet, Andreu

doi:10.1016/j.ecoinf.2015.08.001

Cited by 13 publications

(15 citation statements)

References 15 publications

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“…Tools for the remote capture, digital storing and processing of largescale data related to ungulate management (e.g. observations, harvest, mortality and recruitment rates) have become available and are commonly used in several European countries (Ueno et al 2014;Zaragozí et al 2015;Helle et al 2016;Bubnicki et al 2016). As accurate spatial data accumulates, it will provide valuable information for e.g.…”

Section: Ungulate Management Databasesmentioning

confidence: 99%

Challenges and science-based implications for modern management and conservation of European ungulate populations

et al. 2017

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Wildlife management systems face growing challenges to cope with increasingly complex interactions between wildlife populations, the environment and human activities. In this position statement, we address the most important issues characterising current ungulate conservation and management in Europe. We present some key points arising from ecological research that may be critical for a reassessment of ungulate management in the future.

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Section: Ungulate Management Databasesmentioning

confidence: 99%

Challenges and science-based implications for modern management and conservation of European ungulate populations

et al. 2017

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“…In the future, high quality sound recording should be integrated into a camera trapping approach and respective software options developed, such as automatic recognition of sound patterns (Zaragozí, Belda, Giménez, Navarro, & Bonet, ). Soundscape ecology is defined as the collection of biological, geophysical, and anthropogenic sounds that emanate from a landscape and which vary over space and time reflecting important ecosystem processes and human activities and can be used to answer a variety of research questions (Pijanowski et al., ).…”

Section: Future Featuresmentioning

confidence: 99%

“…Some software are able to match the same individuals based on natural individual markers, such as fur patterns, and use capture-markrecapture methods to estimate population sizes (reviewed in Bolger, Morrison, Vance, Lee, & Farid, 2012). This approach is being developed for use in Snoopy (Smedley & Terdal, 2014 In the future, high quality sound recording should be integrated into a camera trapping approach and respective software options developed, such as automatic recognition of sound patterns (Zaragozí, Belda, Giménez, Navarro, & Bonet, 2015). Soundscape ecology is defined as the collection of biological, geophysical, and anthropogenic sounds that emanate from a landscape and which vary over space and time reflecting important ecosystem processes and human activities and can be used to answer a variety of research questions (Pijanowski et al, 2011).…”

Section: Future Fe Ature Smentioning

confidence: 99%

Software to facilitate and streamline camera trap data management: A review

Young

Rode‐Margono

Amin

2018

Ecology and Evolution

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Improving technology and increasing affordability mean that camera trapping—the use of remotely triggered cameras to photograph wildlife—is becoming an increasingly common tool in the monitoring and conservation of wild populations. Each camera trap study generates a vast amount of data, which need to be processed and labeled before analysis. Traditionally, processing camera trap data has been performed manually by entering data into a spreadsheet. This is time‐consuming, prone to human error, and data management may be inconsistent between projects, hindering collaboration. Recently, several programs have become available to facilitate and quicken data processing. Here, we review available software and assess their ability to better standardize camera trap data management and facilitate data sharing and collaboration. To identify available software for camera trap data management, we used internet searches and contacted researchers and practitioners working on large camera trap projects, as well as software developers. We tested all available programs against a range of software characteristics in addition to their ability to record a suite of important data variables extracted from images. We identified and reviewed 12 available programs for the management of camera trap data. These ranged from simple software assisting with the extraction of metadata from an image, through to comprehensive programs that facilitate data entry and analysis. Many of the programs tested were developed for use on specific studies and so do not cover all possible software or data collection requirements that different projects may have. We highlight the importance of a standardized software solution for camera trap data management. This approach would allow all possible data to be collected, enabling researchers to share data and contribute to other studies, as well as facilitating multi‐project comparisons. By standardizing camera trap data collection and management in this way, future studies would be better placed to guide conservation policy on a global level.

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“…; Sundaresan, Riginos & Abelson ; Sanderson & Harris ; Krishnappa & Turner ; Tobler ; Zaragozí et al . ; McShea et al . ; Ivan & Newkirk ; see the latter and Table S1 for a comparison of approaches).…”

Section: Introductionmentioning

confidence: 99%

“…Efficient use of these analytical tools requires efficient and systematic management of the large numbers of images that can be generated in short periods of time. A variety of approaches using different software have been developed for that purpose (Harris et al 2010;Fegraus et al 2011;Sundaresan, Riginos & Abelson 2011;Sanderson & Harris 2013;Krishnappa & Turner 2014;Tobler 2014;Zaragoz ı et al 2015;McShea et al 2016;Ivan & Newkirk 2016; see the latter and Table S1 for a comparison of approaches). These software approaches have different foci and offer different sets of features.…”

Section: Introductionmentioning

confidence: 99%

camtrapR: an R package for efficient camera trap data management

et al. 2016

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Summary1. Camera trapping is a widely applied method to study mammalian biodiversity and is still gaining popularity. It can quickly generate large amounts of data which need to be managed in an efficient and transparent way that links data acquisition with analytical tools. 2. We describe the free and open-source R package camtrapR, a new toolbox for flexible and efficient management of data generated in camera trap-based wildlife studies. The package implements a complete workflow for processing camera trapping data. It assists in image organization, species and individual identification, data extraction from images, tabulation and visualization of results and export of data for subsequent analyses. There is no limitation to the number of images stored in this data management system; the system is portable and compatible across operating systems. 3. The functions provide extensive automation to minimize data entry mistakes and, apart from species and individual identification, require minimal manual user input. Species and individual identification are performed outside the R environment, either via tags assigned in dedicated image management software or by moving images into species directories. 4. Input for occupancy and (spatial) capture-recapture analyses for density and abundance estimation, for example in the R packages unmarked or secr, is computed in a flexible and reproducible manner. In addition, survey summary reports can be generated, spatial distributions of records can be plotted and exported to GIS software, and single-and two-species activity patterns can be visualized. 5. camtrapR allows for streamlined and flexible camera trap data management and should be most useful to researchers and practitioners who regularly handle large amounts of camera trapping data.

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Advances in camera trap data management tools: Towards collaborative development and integration with GIS

Cited by 13 publications

References 15 publications

Challenges and science-based implications for modern management and conservation of European ungulate populations

Challenges and science-based implications for modern management and conservation of European ungulate populations

Software to facilitate and streamline camera trap data management: A review

camtrapR: an R package for efficient camera trap data management

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