The application discloses a crested
ibis recognition and
ecological monitoring method based on multi-
modal data fusion, relates to the technical field of wild animal
ecological monitoring, and comprises the following steps: installing a micro Beidou positioning tracker on a crested
ibis individual to collect activity trajectory data, arranging visible light and
infrared thermal
imaging equipment in the main
habitat and foraging area of the crested
ibis, arranging an
acoustic sensor array around the night
habitat and breeding ground, and acquiring visual and acoustic
feature data sets.Through a cross-
modal attention mechanism, three types of features are adaptively weighted and fused to generate a multi-
modal joint
feature vector containing time and space context information, which is associated and matched with a preset ecological
database, an behavior-environment correlation model is established, and a foraging
preference index,
habitat suitability
score and activity path planning scheme are output.The method integrates multi-
modal data for
joint analysis, completes the quantitative output of crested ibis
ecological monitoring, and improves the integrity of crested ibis recognition and ecological monitoring.