WISDAM (Wildlife Image Survey – Detection and Mapping): Software to produce data suitable for abundance estimation and spatial modelling from aerial photographic surveys of marine and terrestrial megafauna

WISDAM (Wildlife Image Survey – Detection and Mapping): Software to produce data suitable for abundance estimation and spatial modelling from aerial photographic surveys of marine and terrestrial megafauna | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecography This is a preprint and has not been peer reviewed. Data may be preliminary. 12 May 2026 V1 Latest version Share on WISDAM (Wildlife Image Survey – Detection and Mapping): Software to produce data suitable for abundance estimation and spatial modelling from aerial photographic surveys of marine and terrestrial megafauna Authors : Amanda Hodgson 0000-0002-9479-3018 [email protected] , Martin Wieser [email protected] , Frederic Maire [email protected] , Christophe Cleguer [email protected] , and Nat Kelly [email protected] Authors Info & Affiliations https://doi.org/10.22541/authorea.15003200/v1 18 views 13 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Advancements in the capabilities of imaging technology and aerial platforms (e.g. drones, satellites) have enhanced our capacity to survey wildlife abundance, distribution and habitat use, and have improved the accuracy of the data collected. We developed our WISDAM (Wildlife Image Survey – Detection and Mapping) open-source software to support aerial imagery surveys by standardising and automating the process of extracting data from the images. The software is based on our experience developing imagery/drone survey methods and our intrinsic understanding of the data requirements for wildlife surveys. Although many researchers are interested in automating the review of the images, there has been little attention on the manual review of images, a process critical for training new Artificial Intelligence (AI) models, improving existing models, and providing reliable data for species where model performance may be insufficient, particularly for species occurring at very low densities. A standardised manual review process is critical for maintaining a consistent probability of detecting animals throughout an image survey dataset. The current capabilities of WISDAM include manually labelling objects (e.g. detected animals) with metadata, mapping these detections along with aerial image footprints (including over marine landscapes) to real-world coordinates, labelling images with environmental attributes and other metadata, identifying multiple detections of individual animals (manually or according to spatial referencing), automatic matching of detections from multiple sources (e.g. multiple manual reviewers or AI models), export of data as CSV files or in multiple GIS formats, and export of images and detections to dedicated folders for training AI models. WISDAM also allows the import and verification of detections from AI models. We encourage contributions (e.g. recommended additions, bug fixes, and AI training imagery) from users to enhance the tool's capabilities. WISDAM is already in use by a several research and local community groups in numerous countries. Information & Authors Information Version history V1 Version 1 12 May 2026 Collection Ecography Keywords Marine Mammals Aerial Surveys species distribution modelling global change individual-based modelling range dynamics movement ecology population dynamic modelling aerial survey aerial photography wildlife survey image processing wildlife mapping Conservation science Biodiversity change Monitoring Ecological modelling Marine Mammals Aerial Surveys Spatial ecology temporal ecology biogeography macroecology environmental science human-nature interactions migration ecology animal navigation compass orientation animal migration avian navigation species distribution modelling global change individual-based modelling range dynamics movement ecology population dynamic modelling Authors Affiliations Amanda Hodgson 0000-0002-9479-3018 [email protected] View all articles by this author Martin Wieser [email protected] Edith Cowan University, Joondalup, Australia View all articles by this author Frederic Maire [email protected] Edith Cowan University, Joondalup, Australia View all articles by this author Christophe Cleguer [email protected] Edith Cowan University, Joondalup, Australia View all articles by this author Nat Kelly [email protected] Edith Cowan University, Joondalup, Australia View all articles by this author Metrics & Citations Metrics Article Usage 18 views 13 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Amanda Hodgson, Martin Wieser, Frederic Maire, et al. WISDAM (Wildlife Image Survey – Detection and Mapping): Software to produce data suitable for abundance estimation and spatial modelling from aerial photographic surveys of marine and terrestrial megafauna. Authorea . 12 May 2026. DOI: https://doi.org/10.22541/authorea.15003200/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/authorea.15003200/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe530c6b86458d3',t:'MTc3OTIxNTYxMQ=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();