Xu, 2017
ViewPDF| Publication | Publication Date | Title |
|---|---|---|
| Hartling et al. | Urban tree species classification using UAV-based multi-sensor data fusion and machine learning | |
| Jakubowksi et al. | Predicting surface fuel models and fuel metrics using Lidar and CIR imagery in a dense, mountainous forest | |
| Illarionova et al. | Estimation of the canopy height model from multispectral satellite imagery with convolutional neural networks | |
| Hoffrén et al. | Assessing GEDI-NASA system for forest fuels classification using machine learning techniques | |
| Röder et al. | Application of optical unmanned aerial vehicle-based imagery for the inventory of natural regeneration and standing deadwood in post-disturbed spruce forests | |
| Zhou et al. | An automated, high-performance approach for detecting and characterizing broccoli based on UAV remote-sensing and transformers: A case study from Haining, China | |
| Karna | Mapping above ground carbon using worldview satellite image and lidar data in relationship with tree diversity of forests | |
| Queinnec et al. | Mapping dominant boreal tree species groups by combining area-based and individual tree crown LiDAR metrics with Sentinel-2 data | |
| Chen et al. | An integrated GIS tool for automatic forest inventory estimates of Pinus radiata from LiDAR data | |
| Mustafa et al. | Object based technique for delineating and mapping 15 tree species using VHR WorldView-2 imagery | |
| Harikumar et al. | Void-Volume-Based stem geometric modeling and branch-knot localization in terrestrial laser scanning data | |
| Chroni et al. | Fusing Multispectral and LiDAR Data for CNN-Based Semantic Segmentation in Semi-Arid Mediterranean Environments: Land Cover Classification and Analysis | |
| Chen et al. | Forest age estimation using UAV-LiDAR and Sentinel-2 data with machine learning algorithms-a case study of Masson pine (Pinus massoniana) | |
| Rahm et al. | Detecting forest degradation in the Congo Basin by optical remote sensing | |
| Xu | Obtaining forest description for small-scale forests using an integrated remote sensing approach | |
| Felix et al. | Comparing pixel-and object-based forest canopy gaps classification using low-cost unmanned aerial vehicle imagery | |
| Haywood et al. | Semi-automating the stand delineation process in mapping natural eucalypt forests | |
| Chen et al. | Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests | |
| Nik Effendi et al. | Combination of hyperspectral and LiDAR for aboveground biomass estimation using machine learning | |
| Radecka et al. | Mapping secondary succession species in agricultural landscape with the use of hyperspectral and airborne laser scanning data | |
| Nazeri | Evaluation of multi-platform LiDAR-based leaf area index estimates over row crops | |
| Lian et al. | Combining multisource remote sensing data to calculate individual tree biomass in complex stands | |
| Khokthong | Drone-based assessments of crowns, canopy cover and land use types in and around an oil palm agroforestry experiment | |
| Reddy et al. | Forest inventory techniques and remote sensing | |
| Puliti | Use of photogrammetric 3D data for forest inventory |