PelaSIG, a QGIS plugin for marine megafauna census: application to the aerial ACCOBAMS Survey Initiative dataset

被引:2
作者
Niviere, Manon [1 ]
Blanchard, Ariane [1 ]
Jraifi, Oussama [1 ]
Van Canneyt, Olivier [1 ]
Doremus, Ghislain [1 ]
Spitz, Jerome [1 ,2 ]
Mansoux, Bruno [1 ,3 ]
Panigada, Simone [4 ]
Laran, Sophie [1 ]
机构
[1] La Rochelle Univ, Observ Pelagis, CNRS, UAR 3462, La Rochelle, France
[2] La Rochelle Univ, Ctr Etud Biol Chize, UMR 7273, CNRS, La Rochelle, France
[3] CNRS, UAR 3468, BBEES Bases Donnees Biodivers Ecol Environm & Soc, Museum Natl Hist Nat, Paris, France
[4] Tethys Res Inst, Milan, Italy
关键词
QGIS; plugin; tools; line transect survey; spatial ecology; GIS; marine megafauna; Mediterranean Sea; LARGE-SCALE SURVEYS; PART I; ABUNDANCE; CETACEANS;
D O I
10.3389/fmars.2023.1270335
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The distribution of wild animals and their monitoring over large areas raises many logistical and technical difficulties that hinder the collection of observation data. The use of Geographic Information Systems (GIS) has increased significantly in recent years. QGIS, an open-source GIS software dedicated to the processing of geospatial data, enables the development of dedicated plugins for specific workflows. The open-source PelaSIG plugin has been developed in Python for QGIS 3 to facilitate and standardise the different steps before and after distance sampling surveys. It brings together a set of tools for survey preparation, automatic data checking, visualisation and presentation of survey effort and sightings to provide an adapted workflow. This plugin is currently designed to process dedicated aerial datasets collected with the SAMMOA software during marine megafauna surveys (i.e., marine mammals, seabirds, elasmobranchs, sea turtles, etc.). Here, we first describe the different tools already available, and then, we present an application with the dataset from the aerial survey of the ACCOBAMS Survey Initiative (ASI) conducted in 2018 over the Mediterranean Sea and using a multi-target protocol.
引用
收藏
页数:13
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