Spatial Intelligence & Geo-Foundation Models Research Group Our research group focuses on the core domains of Spatial Intelligent Perception and Autonomous Navigation, driven by the frontier of Geospatial Intelligence (GeoAI). We integrate cutting-edge technologies including LiDAR SLAM, photogrammetry, and multi-source information fusion, with a strategic emphasis on Geospatial Foundation Models. To meet the operational requirements […]

Environmental Change and Terrestrial Ecosystem Response Changes of forest quality are composed by the changes in forest structure and species composition, which are usually caused by tree growth, anthropogenic activities (e.g., forest treatment, logging), and environmental disturbances (e.g., drought, flood, and wildfire). To quantitatively assess forest structure changes from multitemporal lidar data, we proposed an […]

Vegetation maps provide crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and national strategic decision making. The current vegetation map of China was produced by a team of more than 250 scientists over the course of two decades starting in the 1980s, who spent a huge amount of efforts to manually delineate […]

Spatial Intelligence & Geo-Foundation Models Research Group Our research group focuses on the core domains of Spatial Intelligent Perception and Autonomous Navigation, driven by the frontier of Geospatial Intelligence (GeoAI). We integrate cutting-edge technologies including LiDAR SLAM, photogrammetry, and multi-source information fusion, with a strategic emphasis on Geospatial Foundation Models. To meet the operational requirements […]

Knowledges about processing of interactions within organisms, between organisms and environment form bedrock of understanding how ecosystem organized. Interactions in forest ecosystem are inferred from patterns of spatial-temporal co-occurrence or avoidance in physical space. Based on the complexity of three-dimensional (3D) ecosystem, ecologists urgently need accurate in-situ data to construct nonlinear relationships and describe complex […]

Geographic One-class Data: Methods & Applications We are interested in the theory and applications of geographic one-class data. One common problem with geographic data is that, for a specific geographic event, only occurrence information is available; information about the absence of the event is not available. We define these specific types of geospatial data as […]

Development of Near-surface Remote Sensing Platforms for Forest Resource Information Acquisition Light detection and ranging (lidar), an active remote sensing technology, has the abilities of high-precision and strong penetration to vegetation, which shows unparalleled advantages in obtaining forest resource information comparing with other traditional remote sensing technologies. In this context, we designed and developed a […]

3D forest structure parameter extraction and upscaling Individual trees are the basic element composition of a forest stand. The structure characteristic and spatial distribution of trees are the key factors to be surveyed in forest inventory. Lidar, as an emerging active remote sensing technology, provides an automatic, effective and accurate tool for deriving individual tree […]

Monitoring and analyzing the spatial and temporal changes of forest resource information Changes of forest quality are composed by the changes in forest structure and species composition, which are usually caused by tree growth, anthropogenic activities (e.g., forest treatment, logging), and environmental disturbances (e.g., drought, flood, and wildfire). To quantitatively assess forest structure changes from […]