The increasing availability of multimodal
remote sensing datasets offers tremendous opportunities to map landscape
features and track their changes across space and time. This 45-minute
webinar will showcase several new statewide geospatial datasets
generated from the latest 2023 leaf-off LiDAR and imagery collection.
Connecticut hosts terabytes of high-resolution remote sensing data in
online repositories, such as CTECO, ranging from 1930s grayscale aerial
photographs to modern multispectral aerial images and high-density 3D
LiDAR point clouds. The latest 2023 statewide leaf-off LiDAR survey
comprises over 700 billion individual points at a density of roughly 14
points/m², complemented by a concurrent multispectral aerial imagery
collection exceeding two trillion image pixels at 8 cm spatial
resolution. Integrating LiDAR with aerial imagery enables accurate
feature extraction and classification, making it virtually possible to
map every urban tree, utility pole, and powerline segment in the state.
However, traditional algorithms often struggle under the sheer volume
and complexity of these large datasets, underscoring the need for
high-throughput, GeoAI-powered analysis pipelines that can operate at
scale. This webinar will showcase geospatial products including tree
canopy height, plant area index, and foliage height diversity, and will
discuss how these products contribute to downstream analysis and
synthesis efforts, such as urban tree equity, forest carbon modelling,
and roadside vegetation management.