Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping | Paper Citation Record

Observation 8d054dd9-3f62-4350-8a54-87b77b21e882 · outbound

This paper cites Ecosystem Structure throughout the Brazilian Amazon from Landsat Observations and Automated Spectral Unmixing.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Ecosystem Structure throughout the Brazilian Amazon from Landsat Observations and Automated Spectral Unmixing

Reference 1

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Observation 801b9f61-ab0a-4dd6-ba97-315e866789b6 · outbound

This paper cites Global patterns and climatic controls of forest structural complexity.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Global patterns and climatic controls of forest structural complexity

Reference 2

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Observation 53538167-6c56-476f-b3c6-082bea31634e · outbound

This paper cites Remotely sensed forest structural complexity predicts multi species occurrence at the landscape scale.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Remotely sensed forest structural complexity predicts multi species occurrence at the landscape scale

Reference 3

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Observation 97e97b5d-38ec-4358-b2aa-76bc20c9f664 · outbound

This paper cites Integrating forest structural diversity measurement into ecological research.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Integrating forest structural diversity measurement into ecological research

Reference 4

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Observation 8abcb58b-9d2c-4ff9-b35c-5fe8ba5c18df · outbound

This paper cites Unravelling the relationship between plant diversity and vegetation structural complexity: A review and theoretical framework.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Unravelling the relationship between plant diversity and vegetation structural complexity: A review and theoretical framework

Reference 5

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Observation b5acff23-d986-4688-96f0-f68843286e69 · outbound

This paper cites Forest and woodland stand structural complexity: Its definition and measurement.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Forest and woodland stand structural complexity: Its definition and measurement

Reference 6

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Observation 6a17e8fa-9e9a-4f35-a8e5-6380daebe82c · outbound

This paper cites High rates of primary production in structurally complex forests.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping High rates of primary production in structurally complex forests

Reference 7

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Observation afbb62f3-b9d0-4195-ab8c-8370e9dd4151 · outbound

This paper cites Quantifying stand structural complexity and its relationship with forest management, tree species diver sity and microclimate.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Quantifying stand structural complexity and its relationship with forest management, tree species diver sity and microclimate

Reference 8

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Observation f4c680d1-9e69-49db-b0c8-774143614d32 · outbound

This paper cites A novel entropy -based method to quantify forest canopy structural complexity from multiplatform lidar point clouds.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A novel entropy -based method to quantify forest canopy structural complexity from multiplatform lidar point clouds

Reference 9

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Observation 9e3b16b8-f1cf-4a6a-9a4c-38a718a19524 · outbound

This paper cites A new index of forest structural heterogeneity using tree architectural attributes measured by terrestrial laser scanning.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A new index of forest structural heterogeneity using tree architectural attributes measured by terrestrial laser scanning

Reference 10

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Observation aebf3b60-14cd-4914-a641-20e49c715ab1 · outbound

This paper cites Measuring habitat complexity and spatial heterogeneity in ecology.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Measuring habitat complexity and spatial heterogeneity in ecology

Reference 11

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Observation 4c7e0449-9808-4ca9-b6bf-154efa6622ed · outbound

This paper cites The Global Ecosystem Dynamics Investigation: High -resolution laser ranging of the Earth’s forests and topography.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping The Global Ecosystem Dynamics Investigation: High -resolution laser ranging of the Earth’s forests and topography

Reference 12

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Observation 7b4042d1-5d05-4cd3-883c-979b1ee19456 · outbound

This paper cites Characterizing the structural complexity of the Earth’s forests with spaceborne lidar.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Characterizing the structural complexity of the Earth’s forests with spaceborne lidar

Reference 13

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Observation d2c961f3-f8f2-4456-a49a-3e73894fe69d · outbound

This paper cites A high- resolution canopy height model of the Earth.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A high- resolution canopy height model of the Earth

Reference 14

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Observation 7ffb2d79-05e6-4174-855b-a6fedb623630 · outbound

This paper cites Unified Deep Learning Model for Global Prediction of Aboveground Biomass, Canopy Height and Cover from High-Resolution, Multi-Sensor Satellite Imagery.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Unified Deep Learning Model for Global Prediction of Aboveground Biomass, Canopy Height and Cover from High-Resolution, Multi-Sensor Satellite Imagery

Reference 15

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Observation e37a7963-4ca4-47d9-a996-adb82173381d · outbound

This paper cites Monitoring of Forest Structure Dynamics by Means of L -Band SAR Tomography.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Monitoring of Forest Structure Dynamics by Means of L -Band SAR Tomography

Reference 16

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Observation df3d1ea8-e940-4283-b75e-0d49b59e0948 · outbound

This paper cites Sensitivity of Multi -Source SAR Backscatter to Changes in Forest Aboveground Biomass.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Sensitivity of Multi -Source SAR Backscatter to Changes in Forest Aboveground Biomass

Reference 17

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Observation 6a81056a-eb86-4039-92b6-df63f918cf02 · outbound

This paper cites Remote sensing approaches to monitor tropical forest restoration: Current methods and future possibilities.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Remote sensing approaches to monitor tropical forest restoration: Current methods and future possibilities

Reference 18

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Observation 428d0883-44c3-4c70-863c-10f7a7464306 · outbound

This paper cites Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art

Reference 19

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This paper cites Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions

Reference 20

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Observation b5921781-2b88-4676-a459-cd1915bcc9c1 · outbound

This paper cites A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests

Reference 21

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Observation ac48af82-93d6-4deb-a565-447ddc21a6f8 · outbound

This paper cites Fusing Sentinel -1 and -2 to Model GEDI -Derived Vegetation Structure Characteristics in GEE for the Paraguayan Chaco.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Fusing Sentinel -1 and -2 to Model GEDI -Derived Vegetation Structure Characteristics in GEE for the Paraguayan Chaco

Reference 22

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Observation 5c3cfcd7-4b10-46d1-acb4-40c13c73048f · outbound

This paper cites Mapping large -scale pantropical forest canopy height by integrating GEDI lidar and TanDEM -X InSAR data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Mapping large -scale pantropical forest canopy height by integrating GEDI lidar and TanDEM -X InSAR data

Reference 23

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Observation df5672d2-120a-4b58-8218-98799cb67434 · outbound

This paper cites Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data

Reference 24

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Observation c44a9c0f-8bb6-4683-b2d4-c60eee168d37 · outbound

This paper cites Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data

Reference 25

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Observation 6c14a6d9-91b9-4257-9474-cb354a8ddef5 · outbound

This paper cites Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping

Reference 26

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Observation 9b6def0b-ccc3-4ed7-89c5-44a232ab922c · outbound

This paper cites Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel- 1, Sentinel-2, ALOS PALSAR-2, and GEDI.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Estimation of Aboveground Biomass for Different Forest Types Using Data from Sentinel- 1, Sentinel-2, ALOS PALSAR-2, and GEDI

Reference 27

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Observation 3d42e33c-47c5-4494-a86a-ef64efbbcee6 · outbound

This paper cites Towards the next generation of Geospatial Artificial Intelligence.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Towards the next generation of Geospatial Artificial Intelligence

Reference 28

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Observation 95f5b5e0-1912-445a-8e80-8ef85a27e915 · outbound

This paper cites Global Ecosystem Dynamics Investigation (GEDI)GEDI L4C Footprint Level Waveform Structural Complexity Index, Version 2 [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Global Ecosystem Dynamics Investigation (GEDI)GEDI L4C Footprint Level Waveform Structural Complexity Index, Version 2 [Internet]

Reference 29

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This paper cites Global Ecosystem Dynamics Investigation (GEDI)GEDI L3 Gridded Land Surface Metrics, Version 2 [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Global Ecosystem Dynamics Investigation (GEDI)GEDI L3 Gridded Land Surface Metrics, Version 2 [Internet]

Reference 30

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Observation 6f1e408b-7fee-4748-8e39-f5a0dec24f95 · outbound

This paper cites New global forest/non-forest maps from ALOS PALSAR data (2007–2010).

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

Reference 31

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This paper cites Sentinel -1 SAR Backscatter Analysis Ready Data Preparation in Google Earth Engine.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Sentinel -1 SAR Backscatter Analysis Ready Data Preparation in Google Earth Engine

Reference 32

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Observation c21089fd-3f67-43b4-9241-bdc9db7bb277 · outbound

This paper cites Copernicus DEM [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Copernicus DEM [Internet]

Reference 33

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This paper cites TanDE M-X - Digital Elevation Model (DEM) - Global, 90m [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping TanDE M-X - Digital Elevation Model (DEM) - Global, 90m [Internet]

Reference 34

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This paper cites The Shuttle Radar Topography Mission.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping The Shuttle Radar Topography Mission

Reference 35

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Observation 07d0a185-2b76-43dc-a1fa-9c6ec065b262 · outbound

This paper cites ASTER Global Digital Elevation Model V003 [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping ASTER Global Digital Elevation Model V003 [Internet]

Reference 36

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This paper cites Google Earth Engine: Planetary-scale geospatial analysis for everyone.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Google Earth Engine: Planetary-scale geospatial analysis for everyone

Reference 37

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This paper cites Discrete return LiDAR point cloud (DP1.30003.001) [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Discrete return LiDAR point cloud (DP1.30003.001) [Internet]

Reference 38

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This paper cites L1A - Discrete airborne LiDAR transects collected by EBA in the Brazilian Amazon (Roraima e Amapá) [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping L1A - Discrete airborne LiDAR transects collected by EBA in the Brazilian Amazon (Roraima e Amapá) [Internet]

Reference 39

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Observation 8ce4e227-d603-45ec-89f3-4b287e645c6a · outbound

This paper cites A biomass map of the Brazilian Amazon from multisource remote sensing.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A biomass map of the Brazilian Amazon from multisource remote sensing

Reference 40

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This paper cites EfficientNetV2: Smaller Models and Faster Training.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping EfficientNetV2: Smaller Models and Faster Training

Reference 41

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This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 42

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This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 43

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This paper cites Dropout as a Bayesian approximation: representing model uncertainty in deep learning.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Dropout as a Bayesian approximation: representing model uncertainty in deep learning

Reference 44

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Observation c1689280-948a-4e91-b4d3-4a472d5ec261 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Adam: A Method for Stochastic Optimization

Reference 45

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This paper cites Terrestrial Ecoregions of the World: A New Ma p of Life on Earth.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Terrestrial Ecoregions of the World: A New Ma p of Life on Earth

Reference 46

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Observation 6053e3e0-b9d8-4562-8af5-d6739f0a33ae · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A Unified Approach to Interpreting Model Predictions

Reference 47

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Observation 4b629a04-799d-4f2b-bab2-955b3b2c0a3c · outbound

This paper cites Burst Misalignment Evaluation for ALOS- 2 PALSAR-2 ScanSAR-ScanSAR Interferometry.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Burst Misalignment Evaluation for ALOS- 2 PALSAR-2 ScanSAR-ScanSAR Interferometry

Reference 48

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This paper cites SAR interferometry using ALOS-2 PALSAR-2 data for the Mw 7.8 Gorkha, Nepal earthquake.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping SAR interferometry using ALOS-2 PALSAR-2 data for the Mw 7.8 Gorkha, Nepal earthquake

Reference 49

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Observation 69fbb2d2-9dfd-46bf-a5d4-03a9f44ec511 · outbound

This paper cites Regenerated ALOS -2/PALSAR-2 global mosaics 2016 and 2014/2015 for forest observations.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Regenerated ALOS -2/PALSAR-2 global mosaics 2016 and 2014/2015 for forest observations

Reference 50

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This paper cites Comparative Study on Remote Sensing Methods for Forest Height Mapping in Complex Mountainous Environments.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Comparative Study on Remote Sensing Methods for Forest Height Mapping in Complex Mountainous Environments

Reference 51

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Observation 7b1fb43b-11f0-4250-81bb-c1347c0dc1c9 · outbound

This paper cites Distribution Pattern of Woody Plants in a Mountain Forest Ecosystem Influenced by Topography and Monsoons.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Distribution Pattern of Woody Plants in a Mountain Forest Ecosystem Influenced by Topography and Monsoons

Reference 52

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This paper cites Deep learning and process understanding for data -driven Earth system science.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Deep learning and process understanding for data -driven Earth system science

Reference 53

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This paper cites Improving Image Classification with Location Context.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Improving Image Classification with Location Context

Reference 54

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Observation 7c0a7172-1843-4e88-9e73-0ed5e0ad752c · outbound

This paper cites Forest Biomass Estimation Using Deep Learning Data Fusion of Lidar, Multispectral, and Topographic Data Remote Sensing of Environment [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Forest Biomass Estimation Using Deep Learning Data Fusion of Lidar, Multispectral, and Topographic Data Remote Sensing of Environment [Internet]

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.361983Z

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Observation f97a0427-2321-4727-9d64-6e9b4579d18e · outbound

This paper cites Generation of country-scale canopy height maps over Gabon using deep learning and TanDEM-X InSAR data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Generation of country-scale canopy height maps over Gabon using deep learning and TanDEM-X InSAR data

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.364868Z

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Observation e185294d-6e58-4f46-869d-3e921f3aeed2 · outbound

This paper cites Multimodal Deep Learning Enables Forest Height Mapping from Patchy Spaceborne Lidar Using Sar and Passive Optical Satellite Data [Internet].

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Multimodal Deep Learning Enables Forest Height Mapping from Patchy Spaceborne Lidar Using Sar and Passive Optical Satellite Data [Internet]

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.367944Z

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Observation a82425cf-6405-4e04-9746-eabea5342851 · outbound

This paper cites Country -wide high- resolution vegetation height mapping with Sentinel-2.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Country -wide high- resolution vegetation height mapping with Sentinel-2

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.370660Z

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Observation 72e1b611-a8d8-40c7-9d38-ee3ab068bbe4 · outbound

This paper cites Comparison of three global canopy height maps and their applicability to biodivers ity modeling: Accuracy issues revealed.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Comparison of three global canopy height maps and their applicability to biodivers ity modeling: Accuracy issues revealed

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.373522Z

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Observation 1ab898d9-a1c1-4b0d-9965-8a81f3c66986 · outbound

This paper cites Repeat GEDI footprints measure the effects of tropical forest disturbances.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Repeat GEDI footprints measure the effects of tropical forest disturbances

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.377190Z

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Observation 387fd25f-b6fa-46d9-aeca-fb4475e437f2 · outbound

This paper cites Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi -Arid Ecosystem.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi -Arid Ecosystem

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.379750Z

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Observation 053edb6a-3821-4c71-971c-48287be43bd6 · outbound

This paper cites High- Resolution Global Maps of 21st -Century Forest Cover Change.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping High- Resolution Global Maps of 21st -Century Forest Cover Change

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.382613Z

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Observation a14db7b1-e806-4e7d-acc6-e77d96fd4e89 · outbound

This paper cites Forest disturbance alerts for the Congo Basin using Sentinel -1.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Forest disturbance alerts for the Congo Basin using Sentinel -1

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.385598Z

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Observation 63d793ae-d323-467b-a7d4-e4c8f5d772a5 · outbound

This paper cites Mapping global forest canopy height through integration of GEDI and Landsat data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Mapping global forest canopy height through integration of GEDI and Landsat data

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.387909Z

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Observation 03a44fd3-4873-4672-9078-afe8bca67e7d · outbound

This paper cites A New InSAR Temporal Decorrelation Model for Seasonal Vegetation Change With Dense Time- Series Data.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping A New InSAR Temporal Decorrelation Model for Seasonal Vegetation Change With Dense Time- Series Data

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.390335Z

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Observation 19c7f366-4031-4f00-9755-7239f62a6aa7 · outbound

This paper cites NASA -ISRO Synthetic Aperture Radar (NISAR) Mission.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping NASA -ISRO Synthetic Aperture Radar (NISAR) Mission

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.393162Z

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Observation dcd87c2d-c0e9-416d-83e3-e4b1b9337bd6 · outbound

This paper cites The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.396331Z

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Observation 2d0a5990-6a16-49d6-9cb8-71f0e55658e5 · outbound

This paper cites Spatially Continuous Mapping of Forest Canopy Height in Canada by Combining GEDI and ICESat -2 with PALSAR and Sentinel.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Spatially Continuous Mapping of Forest Canopy Height in Canada by Combining GEDI and ICESat -2 with PALSAR and Sentinel

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.399270Z

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Observation b41f36f3-c28a-4922-8be4-b5b9f36fe5a5 · outbound

This paper cites The Ice, Cloud, and land Elevation Satellite -2 (ICESat-2): Science requirements, concept, and implementation.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping The Ice, Cloud, and land Elevation Satellite -2 (ICESat-2): Science requirements, concept, and implementation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.402469Z

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Observation d4d65231-156a-4daa-9d9a-fff1cb0cef5e · outbound

This paper cites Computational tools for assessing forest recovery with GEDI shots and forest change maps.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Computational tools for assessing forest recovery with GEDI shots and forest change maps

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.405913Z

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Observation 681fb435-5238-46bf-97f5-2d06d4aca460 · outbound

This paper cites Evidential Deep Learning: Enhancing Predictive Uncertai nty Estimation for Earth System Science Applications.

Scalable deep fusion of spaceborne lidar and synthetic aperture radar for global forest structural complexity mapping Evidential Deep Learning: Enhancing Predictive Uncertai nty Estimation for Earth System Science Applications

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-04T11:17:36.409216Z

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