| _ | above | _ |
|---|
| above | ground biomass estimation in an African tropical forest with lidar and hyperspectral data |
| above | Ground Level Estimation of Airborne Synthetic Aperture Radar Altimeter by a Fully Supervised Altimetry Enhancement Network |
| above | the Nyquist Rate, Modulo Folding Does Not Hurt |
| above | - and Belowground Biomass Carbon Stock and Net Primary Productivity Maps for Tidal Herbaceous Marshes of the United States |
| above | -bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform-A case study in Wild Duck Lake Wetland, Beijing, China |
| above | -ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging |
| above | -Ground Biomass Estimation for Coniferous Forests in Northern China Using Regression Kriging and Landsat 9 Images |
| above | -Ground Biomass Estimation of Plantation with Different Tree Species Using Airborne LiDAR and Hyperspectral Data |
| above | -Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods |
| above | -Ground Biomass Retrieval over Tropical Forests: A Novel GNSS-R Approach with CyGNSS |
| above | -Ground Objects in Urban Scenes from Medium Scale Aerial Imagery |
| Accurate Determination of Underground GPR Wavefront and B-Scan Shape From | above | -Ground Point Sources |
| Aerosol Optical Properties | above | Productive Waters of Gorky Reservoir for Atmospheric Correction of Sentinel-3/OLCI Images |
| Aircraft Detection | above | Clouds by Sentinel-2 MSI Parallax |
| angular shrinkage BERT model for few-shot relation extraction with none-of-the- | above | detection, An |
| Application of Convolutional Neural Network on Lei Bamboo | above | -Ground-Biomass (AGB) Estimation Using Worldview-2 |
| Approaches of Satellite Remote Sensing for the Assessment of | above | -Ground Biomass across Tropical Forests: Pan-tropical to National Scales |
| Assessing Performance of L- and P-Band Polarimetric Interferometric SAR Data in Estimating Boreal Forest | above | -Ground Biomass |
| Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for | above | -Ground Biomass Retrieval of a Tropical Forest |
| Assessment of Forest | above | Ground Biomass Estimation Using Multi-Temporal C-band Sentinel-1 and Polarimetric L-band PALSAR-2 Data |
| Assessment of Forest | above | -Ground Biomass Estimation from PolInSAR in the Presence of Temporal Decorrelation |
| Assessments of the | above | -Ocean Atmospheric CO2 Detection Capability of the GAS Instrument Onboard the Next-Generation FengYun-3H Satellite |
| BIOMASS Level 2 Prototype Processor: Design and Experimental Results of | above | -Ground Biomass Estimation, The |
| Canopy Height and | above | -Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data |
| Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of | above | -Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, A |
| Combined Characterization of Airborne Saharan Dust | above | Sofia, Bulgaria, during Blocking-Pattern Conditioned Dust Episode in February 2021 |
| Comparison and Evaluation of Three Methods for Estimating Forest | above | Ground Biomass Using TM and GLAS Data |
| Comparison of | above | -Water Seabird and TriOS Radiometers along an Atlantic Meridional Transect |
| Comparison of Backpack, Handheld, Under-Canopy UAV, and | above | -Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests |
| Comparison of Machine Learning Methods for Estimating Mangrove | above | -Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam |
| Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of | above | -Ground Biomass Change in Oregon, USA |
| Comparison of Regression Techniques for Estimation of | above | -Ground Winter Wheat Biomass Using Near-Surface Spectroscopy, A |
| Complex Surface Displacements | above | the Storage Cavern Field at Epe, NW-Germany, Observed by Multi-Temporal SAR-Interferometry |
| Composite Electromagnetic Scattering and High-Resolution SAR Imaging of Multiple Targets | above | Rough Surface |
| Dark target effectiveness for dark-object subtraction atmospheric correction method on mangrove | above | -ground carbon stock mapping |
| Detecting interaction | above | digital tabletops using a single depth camera |
| Detecting Targets | above | the Earth's Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1 |
| Development of A Model To Correct Multi-view Angle | above | Water Measurements for The Analysis of The Bidirectional Reflectance of Coral And Other Reef Substrates |
| Development of a Regional LIDAR-Derived | above | -Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA |
| Drought in Northern Italy: Long Earth Observation Time Series Reveal Snow Line Elevation to Be Several Hundred Meters | above | Long-Term Average in 2022 |
| Effect of field plot location on estimating tropical forest | above | -ground biomass in Nepal using airborne laser scanning data |
| Efficient Multiregion FEM-BIM for Composite Scattering From an Arbitrary Dielectric Target | above | Dielectric Rough Sea Surfaces, An |
| Enhancing Wheat | above | -Ground Biomass Estimation Using UAV RGB Images and Machine Learning: Multi-Feature Combinations, Flight Height, and Algorithm Implications |
| Equal Value String and Copy | above | String Based String Prediction for SCC in AVS3 |
| Estimate of winter-wheat | above | -ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices |
| Estimating | above | -Ground Biomass in Sub-Tropical Buffer Zone Community Forests, Nepal, Using Sentinel 2 Data |
| Estimating | above | -Ground Biomass of Maize Using Features Derived from UAV-Based RGB Imagery |
| Estimating | above | -Ground Biomass of Potato Using Random Forest and Optimized Hyperspectral Indices |
| Estimating Individual Tree | above | -Ground Biomass of Chinese Fir Plantation: Exploring the Combination of Multi-Dimensional Features from UAV Oblique Photos |
| Estimating Maize | above | -Ground Biomass Using 3D Point Clouds of Multi-Source Unmanned Aerial Vehicle Data at Multi-Spatial Scales |
| Estimating Mangrove | above | -Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam |
| Estimating Mangrove Canopy Height and | above | -Ground Biomass in the Everglades National Park with Airborne LiDAR and TanDEM-X Data |
| Estimating Stand Volume and | above | -Ground Biomass of Urban Forests Using LiDAR |
| Estimating the | above | -Ground Biomass in Miombo Savanna Woodlands (Mozambique, East Africa) Using L-Band Synthetic Aperture Radar Data |
| Estimation and mapping of | above | -ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery |
| Estimation of | above | Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data |
| Estimation of | above | -Ground Biomass of Winter Wheat Based on Consumer-Grade Multi-Spectral UAV |
| Estimation of | above | -Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
| Estimation of Deformation Intensity | above | a Flooded Potash Mine Near Berezniki (Perm Krai, Russia) with SAR Interferometry |
| Estimation of Potato | above | -Ground Biomass Based on Vegetation Indices and Green-Edge Parameters Obtained from UAVs |
| Estimation of Potato | above | -Ground Biomass Using UAV-Based Hyperspectral images and Machine-Learning Regression |
| Estimation of Winter Wheat | above | -Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models |
| Evaluation of GRACE/GRACE Follow-On Time-Variable Gravity Field Models for Earthquake Detection | above | Mw8.0s in Spectral Domain |
| Evaluation of Remote Sensing Inversion Error for the | above | -Ground Biomass of Alpine Meadow Grassland Based on Multi-Source Satellite Data |
| Evaluation of the Sensitivity of SMOS L-VOD to Forest | above | -Ground Biomass at Global Scale |
| Examining the potential of Sentinel-2 MSI spectral resolution in quantifying | above | ground biomass across different fertilizer treatments |
| Example of Monte Carlo Method Uncertainty Evaluation for | above | -Water Ocean Colour Radiometry |
| Exploring the Inclusion of Small Regenerating Trees to Improve | above | -Ground Forest Biomass Estimation Using Geospatial Data |
| Fast EPILE Combined With FBM for Electromagnetic Scattering From Dielectric Targets | above | and Below the Dielectric Rough Surface, The |
| Fast Iterative Approach to Difference Scattering From the Target | above | a Rough Surface |
| Field Spectroscopy For Vegetation Evaluation Along The Nutrient And Elevation Gradient | above | The Tree Line In The Krkonose Mountains National Park |
| Forest | above | Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data |
| Forest | above | -Ground Biomass Inversion Using Optical and SAR Images Based on a Multi-Step Feature Optimized Inversion Model |
| Freshwater Fish Habitat Complexity Mapping Using | above | and Underwater Structure-From-Motion Photogrammetry |
| Full Polarimetric Bistatic Radar Imaging Experiments on Sets of Dielectric Cylinders | above | a Conductive Circular Plate |
| Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust | above | the Eastern Mediterranean |
| High-Resolution Airborne Color-Infrared Camera Water Mask for the NASA | above | Campaign, A |
| Hyperspectral Monitoring Driven by Machine Learning Methods for Grassland | above | -Ground Biomass |
| Identifying Absorbing Aerosols | above | Clouds From the Spinning Enhanced Visible and Infrared Imager Coupled With NASA A-Train Multiple Sensors |
| Improved Method for Pan-Tropical | above | -Ground Biomass and Canopy Height Retrieval Using CYGNSS, An |
| Improving Estimates and Change Detection of Forest | above | -Ground Biomass Using Statistical Methods |
| Improving the Estimation of | above | Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran) |
| Incorporating a Hyperspectral Direct-Diffuse Pyranometer in an | above | -Water Reflectance Algorithm |
| Interferometric Ground Cancellation for | above | Ground Biomass Estimation |
| Inversion of Forest | above | Ground Biomass in Mountainous Region Based on PolSAR Data after Terrain Correction: A Case Study from Saihanba, China |
| Joint Alignment of Underwater and | above | -The-Water Photogrammetric 3D Models by Independent Models Adjustment |
| LiDAR-Assisted Multi-Source Program (LAMP) for Measuring | above | Ground Biomass and Forest Carbon |
| Limiting Accuracy of Height Measurement for a Precision Radar Altimeter in a Low Altitude Flying Vehicle | above | the Sea Surface |
| Looking from | above | : When Earth Observation Meets Vision |
| Mapping | above | -Ground Biomass by Integrating Optical and SAR Imagery: A Case Study of Xixi National Wetland Park, China |
| Mapping | above | -Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth |
| Mapping | above | -Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions |
| Mid-air interactions | above | stereoscopic interactive tables |
| Modelling | above | Ground Biomass in Tanzanian Miombo Woodlands Using TanDEM-X WorldDEM and Field Data |
| Monitoring Non-Linear Ground Motion | above | Underground Gas Storage Using GNSS and PSInSAR Based on Sentinel-1 Data |
| Multi-Scale Forest | above | -Ground Biomass Mapping Approach: Employing a Step-by-Step Spatial Downscaling Method with Bias-Corrected Ensemble Machine Learning, A |
| Multifrequency and Full-Polarimetric SAR Assessment for Estimating | above | Ground Biomass and Leaf Area Index in the Amazon Varzea Wetlands |
| New Global View of | above | -Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements |
| New Textural Indicators for Assessing | above | -Ground Cotton Biomass Extracted from Optical Imagery Obtained via Unmanned Aerial Vehicle |
| Novel Approach for Estimation of | above | -Ground Biomass of Sugar Beet Based on Wavelength Selection and Optimized Support Vector Machine, A |
| Novel Method for Estimating Spatial Distribution of Forest | above | -Ground Biomass Based on Multispectral Fusion Data and Ensemble Learning Algorithm, A |
| Optimal Combination of Predictors and Algorithms for Forest | above | -Ground Biomass Mapping from Sentinel and SRTM Data |
| Overview of Using Unmanned Aerial System Mounted Sensors to Measure Plant | above | -Ground Biomass, An |
| Parking space inventory from | above | : Detection on aerial images and estimation for unobserved regions |
| Potential of ALOS2 and NDVI to Estimate Forest | above | -Ground Biomass, and Comparison with Lidar-Derived Estimates |
| Potential of Fully Polarized ALOS-2 Data for Estimating Forest | above | -Ground Biomass, The |
| Predictive Modeling of | above | -Ground Biomass in Brachiaria Pastures from Satellite and UAV Imagery Using Machine Learning Approaches |
| Quantification of | above | -Ground Biomass over the Cross-River State, Nigeria, Using Sentinel-2 Data |
| Rapid Evaluation and Validation Method of | above | Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India |
| Remote Sensing of | above | -Ground Biomass |
| Research Pathways of Forest | above | -Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations |
| Retrieval of Salt Marsh | above | -Ground Biomass from High-Spatial Resolution Hyperspectral Imagery Using PROSAIL |
| SAR-Based Estimation of | above | -Ground Biomass and Its Changes in Tropical Forests of Kalimantan Using L- and C-Band |
| Satellite-based Mapping of | above | -ground Blue Carbon Storage in Seagrass Habitat Within The Shallow Coastal Water |
| SeaDroneSim: Simulation of Aerial Images for Detection of Objects | above | Water |
| Semi-Empirical Retrieval Method of | above | -Ground Live Forest Fuel Loads by Combining SAR and Optical Data, A |
| Sentinel-2 Images Based Modeling of Grassland | above | -Ground Biomass Using Random Forest Algorithm: A Case Study on the Tibetan Plateau |
| simple and effective method for removing residual reflected skylight in | above | -water remote sensing reflectance measurements, A |
| Snow Virga | above | the Swiss Plateau Observed by a Micro Rain Radar |
| Statistical Observation of Thunderstorm-Induced Ionospheric Gravity Waves | above | Low-Latitude Areas in the Northern Hemisphere |
| Study of Atomic Oxygen Airglow Intensities and Air Temperature near Mesopause Obtained by Ground-Based and Satellite Instruments | above | Baikal Natural Territory |
| TanDEM-X digital surface models in boreal forest | above | -ground biomass change detection |
| Three-Dimensional Conceptual Model for Estimating the | above | -Ground Biomass of Winter Wheat Using Digital and Multispectral Unmanned Aerial Vehicle Images at Various Growth Stages, A |
| UAV-Based LiDAR for High-Throughput Determination of Plant Height and | above | -Ground Biomass of the Bioenergy Grass Arundo donax |
| Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data: Prolonged | above | -Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel |
| Urban | above | -Ground Biomass Estimation Using GEDI Laser Data and Optical Remote Sensing Images |
| Use of Oblique RGB Imagery and Apparent Surface Area of Plants for Early Estimation of | above | -Ground Corn Biomass |
| Using Landsat-8 and Sentinel-1 data for | above | Ground Biomass assessment in the Tamar valley and Dartmoor |
| Using multi-frequency radar and discrete-return LiDAR measurements to estimate | above | -ground biomass and biomass components in a coastal temperate forest |
| Utility of Sentinel-2 Spectral Data in Quantifying | above | -Ground Carbon Stock in an Urban Reforested Landscape, The |
| Validated and Accurate Method for Quantifying and Extrapolating Mangrove | above | -Ground Biomass Using LiDAR Data, A |
| Woody | above | -Ground Biomass Estimation on Abandoned Agriculture Land Using Sentinel-1 and Sentinel-2 Data |
132 for above
| _ | aboveground | _ |
|---|
| Ability of Landsat-8 OLI Derived Texture Metrics In Estimating | aboveground | Carbon Stocks Of Coppice Oak Forests |
| aboveground | Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data |
| aboveground | Biomass Dynamics of a Coastal Wetland Ecosystem Driven by Land Use/Land Cover Transformation |
| aboveground | Biomass Estimation and Time Series Analyses in Mongolian Grasslands Utilizing PlanetScope Imagery |
| aboveground | Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil |
| aboveground | Biomass Estimation of Individual Trees in a Coastal Planted Forest Using Full-Waveform Airborne Laser Scanning Data |
| aboveground | Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery |
| aboveground | Biomass Prediction of Arid Shrub-Dominated Community Based on Airborne LiDAR through Parametric and Nonparametric Methods |
| aboveground | Forest Biomass Estimation by the Integration of TLS and ALOS PALSAR Data Using Machine Learning |
| aboveground | Forest Biomass Estimation Combining L- and P-Band SAR Acquisitions |
| aboveground | Forest Biomass Estimation Using Tent Mapping Atom Search Optimized Backpropagation Neural Network with Landsat 8 and Sentinel-1A Data |
| aboveground | total and green biomass of dryland shrub derived from terrestrial laser scanning |
| aboveground | Tree Biomass Estimation of Sparse Subalpine Coniferous Forest with UAV Oblique Photography |
| aboveground | -Biomass Estimation of a Complex Tropical Forest in India Using Lidar |
| Accurate Measurement of Tropical Forest Canopy Heights and | aboveground | Carbon Using Structure From Motion |
| Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated | aboveground | Biomass Density |
| Airborne Lidar Estimation of | aboveground | Forest Biomass in the Absence of Field Inventory |
| Airborne Lidar Sampling Strategies to Enhance Forest | aboveground | Biomass Estimation from Landsat Imagery |
| Airborne LIDAR-Derived | aboveground | Biomass Estimates Using a Hierarchical Bayesian Approach |
| Analyzing the Uncertainty of Estimating Forest | aboveground | Biomass Using Optical Imagery and Spaceborne LiDAR |
| Assessing the Accuracy of GEDI Data for Canopy Height and | aboveground | Biomass Estimates in Mediterranean Forests |
| Assessing the Impacts of Tidal Creeks on the Spatial Patterns of Coastal Salt Marsh Vegetation and Its | aboveground | Biomass |
| Can Machine Learning Algorithms Successfully Predict Grassland | aboveground | Biomass? |
| Characterising the | aboveground | Carbon Content of Saltmarsh in Jervis Bay, NSW, Using ArborCam and PlanetScope |
| Characterization of | aboveground | biomass in an unmanaged boreal forest using Landsat temporal segmentation metrics |
| Combining Multiple Geospatial Data for Estimating | aboveground | Biomass in North Carolina Forests |
| Combining Radiative Transfer Model and Regression Algorithms for Estimating | aboveground | Biomass of Grassland in West Ujimqin, China |
| Combining Sample Plot Stratification and Machine Learning Algorithms to Improve Forest | aboveground | Carbon Density Estimation in Northeast China Using Airborne LiDAR Data |
| Comparative Analysis of Modeling Algorithms for Forest | aboveground | Biomass Estimation in a Subtropical Region |
| Comparison of Statistical Modelling Approaches for Estimating Tropical Forest | aboveground | Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data |
| Deep Learning Based Retrieval of Forest | aboveground | Biomass from Combined LiDAR and Landsat 8 Data |
| Democratic Republic of the Congo Tropical Forest Canopy Height and | aboveground | Biomass Estimation with Landsat-8 Operational Land Imager (OLI) and Airborne LiDAR Data: The Effect of Seasonal Landsat Image Selection |
| Determinants of | aboveground | Biomass across an Afromontane Landscape Mosaic in Kenya |
| Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species | aboveground | Biomass Estimation in South Africa |
| Development of a System of Compatible Individual Tree Diameter and | aboveground | Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data |
| Dynamic estimation of rice | aboveground | biomass based on spectral and spatial information extracted from hyperspectral remote sensing images at different combinations of growth stages |
| Dynamic Harvest Index Estimation of Winter Wheat Based on UAV Hyperspectral Remote Sensing Considering Crop | aboveground | Biomass Change and the Grain Filling Process |
| Effects of Driving Factors on Forest | aboveground | Biomass (AGB) in China's Loess Plateau by Using Spatial Regression Models |
| Effects of Sample Plot Size and GPS Location Errors on | aboveground | Biomass Estimates from LiDAR in Tropical Dry Forests |
| Enhancing | aboveground | Biomass Estimation for Three Pinus Forests in Yunnan, SW China, Using Landsat 8 |
| Estimates of | aboveground | Biomass from Texture Analysis of Landsat Imagery |
| Estimating 3D Green Volume and | aboveground | Biomass of Urban Forest Trees by UAV-Lidar |
| Estimating | aboveground | Biomass and Its Spatial Distribution in Coastal Wetlands Utilizing Planet Multispectral Imagery |
| Estimating | aboveground | Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations |
| Estimating | aboveground | Biomass in Zagros Forest, Iran, Using Sentinel-2 Data |
| Estimating | aboveground | Biomass of Two Different Forest Types in Myanmar from Sentinel-2 Data with Machine Learning and Geostatistical Algorithms |
| Estimating | aboveground | Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data |
| Estimating Forest | aboveground | Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China |
| Estimating Forest | aboveground | Biomass Using Gaofen-1 Images, Sentinel-1 Images, and Machine Learning Algorithms: A Case Study of the Dabie Mountain Region, China |
| Estimating leaf area index and | aboveground | biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images |
| Estimating Sugarcane | aboveground | Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms |
| Estimating the | aboveground | Biomass for Planted Forests Based on Stand Age and Environmental Variables |
| Estimating the | aboveground | Biomass of Various Forest Types with High Heterogeneity at the Provincial Scale Based on Multi-Source Data |
| Estimating total | aboveground | , stem and branch biomass using multi-frequency SAR |
| Estimation of | aboveground | Biomass of Potatoes Based on Characteristic Variables Extracted from UAV Hyperspectral Imagery |
| Estimation of | aboveground | Carbon Density of Forests Using Deep Learning and Multisource Remote Sensing |
| Estimation of Bamboo Forest | aboveground | Carbon Using the RGLM Model Based on Object-Based Multiscale Segmentation of SPOT-6 Imagery |
| Estimation of Forest | aboveground | Biomass in Changbai Mountain Region Using ICESat/GLAS and Landsat/TM Data |
| Estimation of Forest | aboveground | Biomass in Karst Areas Using Multi-Source Remote Sensing Data and the K-DBN Algorithm |
| Estimation of Forest | aboveground | Biomass of Two Major Conifers in Ibaraki Prefecture, Japan, from PALSAR-2 and Sentinel-2 Data |
| Estimation of Forest Canopy Height and | aboveground | Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland |
| Estimation of Grassland Canopy Height and | aboveground | Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle |
| Estimation of National Forest | aboveground | Biomass from Multi-Source Remotely Sensed Dataset with Machine Learning Algorithms in China |
| Estimation Of Regional Forest | aboveground | Biomass Combining Icesat-glas Waveforms And Hj-1a/hsi Hyperspectral Imageries |
| Estimation of the forest stand mean height and | aboveground | biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery |
| Estimation of the Grassland | aboveground | Biomass of the Inner Mongolia Plateau Using the Simulated Spectra of Sentinel-2 Images |
| Evaluating k-Nearest Neighbor (kNN) Imputation Models for Species-Level | aboveground | Forest Biomass Mapping in Northeast China |
| Evaluating Site-Specific and Generic Spatial Models of | aboveground | Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA |
| Evaluating the Potential of ALS Data to Increase the Efficiency of | aboveground | Biomass Estimates in Tropical Peat-Swamp Forests |
| Evaluating the Transferability of Spectral Variables and Prediction Models for Mapping Forest | aboveground | Biomass Using Transfer Learning Methods |
| Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying | aboveground | biomass in uMgeni catchment, South Africa |
| Evaluation of Eight Machine Learning Regression Algorithms for Forest | aboveground | Biomass Estimation from Multiple Satellite Data Products, An |
| Evaluation of FORMOSAT-2 and PlanetScope Imagery for | aboveground | Oil Palm Biomass Estimation in a Mature Plantation in the Congo Basin |
| Evaluation of Radiometric and Atmospheric Correction Algorithms for | aboveground | Forest Biomass Estimation Using Landsat 5 TM Data |
| Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest | aboveground | Biomass Estimation |
| Examining the Potential of Sentinel Imagery and Ensemble Algorithms for Estimating | aboveground | Biomass in a Tropical Dry Forest |
| Exploring Bamboo Forest | aboveground | Biomass Estimation Using Sentinel-2 Data |
| Extraction and Textural Characterization of | aboveground | Areas from Aerial Stereo Pairs: A Quality Assessment |
| Forest | aboveground | Biomass Estimation Using Machine Learning Ensembles: Active Learning Strategies for Model Transfer and Field Sampling Reduction |
| Forest | aboveground | Biomass Estimation Using Multi-Features Extracted by Fitting Vertical Backscattered Power Profile of Tomographic SAR |
| Forest | aboveground | Biomass Estimation Using Multisource Remote Sensing Data and Deep Learning Algorithms: A Case Study over Hangzhou Area in China |
| Fusion of LiDAR and Multispectral Data for | aboveground | Biomass Estimation in Mountain Grassland |
| Fusion of Multiple Gridded Biomass Datasets for Generating a Global Forest | aboveground | Biomass Map |
| Generalized Hierarchical Model-Based Estimation for | aboveground | Biomass Assessment Using GEDI and Landsat Data |
| Grassland | aboveground | Biomass Estimation through Assimilating Remote Sensing Data into a Grass Simulation Model |
| Image-Based Dynamic Quantification of | aboveground | Structure of Sugar Beet in Field |
| impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species | aboveground | biomass and carbon stocks in uMgeni Catchment, South Africa, The |
| Impacts of Spatial Variability on | aboveground | Biomass Estimation from L-Band Radar in a Temperate Forest |
| Impacts Of Tree Height-DBH Allometry On Lidar-based Tree | aboveground | Biomass Modeling |
| Improved Estimation of | aboveground | Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity |
| Improved Estimation of Winter Wheat | aboveground | Biomass Using Multiscale Textures Extracted from UAV-Based Digital Images and Hyperspectral Feature Analysis |
| Improved Object-Based Estimation of Forest | aboveground | Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region |
| Improved Object-Based Mapping of | aboveground | Biomass Using Geographic Stratification with GEDI Data and Multi-Sensor Imagery |
| Improving | aboveground | Biomass Estimation in Lowland Tropical Forests across Aspect and Age Stratification: A Case Study in Xishuangbanna |
| Improving | aboveground | Biomass Estimation of Pinus densata Forests in Yunnan Using Landsat 8 Imagery by Incorporating Age Dummy Variable and Method Comparison |
| Improving | aboveground | Forest Biomass Maps: From High-Resolution to National Scale |
| Improving Accuracy Estimation of Forest | aboveground | Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran) |
| Improving Estimation of Woody | aboveground | Biomass of Sparse Mixed Forest over Dryland Ecosystem by Combining Landsat-8, GaoFen-2, and UAV Imagery |
| Improving Forest | aboveground | Biomass Estimation of Pinus densata Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images |
| Improving Forest | aboveground | Biomass Estimation Using Seasonal Landsat NDVI Time-Series |
| Individual Tree-Scale | aboveground | Biomass Estimation of Woody Vegetation in a Semi-Arid Savanna Using 3D Data |
| Influence of UAS Flight Altitude and Speed on | aboveground | Biomass Prediction |
| Integrating Airborne LiDAR and Optical Data to Estimate Forest | aboveground | Biomass in Arid and Semi-Arid Regions of China |
| Integrating Imaging Spectrometer and Synthetic Aperture Radar Data for Estimating Wetland Vegetation | aboveground | Biomass in Coastal Louisiana |
| Integrating Multi-Source Remote Sensing to Assess Forest | aboveground | Biomass in the Khingan Mountains of North-Eastern China Using Machine-Learning Algorithms |
| Integrating SAR and Optical Data for | aboveground | Biomass Estimation of Coastal Wetlands Using Machine Learning: Multi-Scale Approach |
| Integrating the PROSAIL and SVR Models to Facilitate the Inversion of Grassland | aboveground | Biomass: A Case Study of Zoigª Plateau, China |
| Integrating the Textural and Spectral Information of UAV Hyperspectral Images for the Improved Estimation of Rice | aboveground | Biomass |
| Integration of GF2 Optical, GF3 SAR, and UAV Data for Estimating | aboveground | Biomass of China's Largest Artificially Planted Mangroves |
| Integration of UAV, Sentinel-1, and Sentinel-2 Data for Mangrove Plantation | aboveground | Biomass Monitoring in Senegal |
| Integration of ZiYuan-3 Multispectral and Stereo Data for Modeling | aboveground | Biomass of Larch Plantations in North China |
| Inverting | aboveground | Biomass-Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery |
| Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest | aboveground | biomass in resource constrained areas |
| L-Band SAR Backscatter Related to Forest Cover, Height and | aboveground | Biomass at Multiple Spatial Scales across Denmark |
| Landsat Time-Series for Estimating Forest | aboveground | Biomass and Its Dynamics across Space and Time: A Review |
| Landscape-Scale | aboveground | Biomass Estimation in Buffer Zone Community Forests of Central Nepal: Coupling In Situ Measurements with Landsat 8 Satellite Data |
| Large Area | aboveground | Biomass and Carbon Stock Mapping in Woodlands in Mozambique with L-Band Radar: Improving Accuracy by Accounting for Soil Moisture Effects Using the Water Cloud Model |
| Lidar | aboveground | Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales |
| Lidar-Based | aboveground | Biomass Estimations for the Maya Archaeological Site of Yaxnohcah, Campeche, Mexico |
| Mapping | aboveground | Biomass in Northern Japanese Forests Using the ALOS PRISM Digital Surface Model |
| Mapping | aboveground | Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China |
| Mapping | aboveground | Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches |
| Mapping | aboveground | Woody Biomass on Abandoned Agricultural Land Based on Airborne Laser Scanning Data |
| Mapping and Estimating | aboveground | Biomass in an Alpine Treeline Ecotone under Model-Based Inference |
| Mapping Forest | aboveground | Biomass Using Multisource Remotely Sensed Data |
| Mapping Forest | aboveground | Biomass with MODIS and Fengyun-3C VIRR Imageries in Yunnan Province, Southwest China Using Linear Regression, K-Nearest Neighbor and Random Forest |
| Mapping Global Forest | aboveground | Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data |
| Mapping Height and | aboveground | Biomass of Mangrove Forests on Hainan Island Using UAV-LiDAR Sampling |
| Mapping Phragmites australis | aboveground | Biomass in the Momoge Wetland Ramsar Site Based on Sentinel-1/2 Images |
| Mapping Plant Nitrogen Concentration and | aboveground | Biomass of Potato Crops from Sentinel-2 Data Using Ensemble Learning Models |
| Mapping Spatiotemporal Changes in Forest Type and | aboveground | Biomass from Landsat Long-Term Time-Series Analysis: A Case Study from Yaoluoping National Nature Reserve, Anhui Province of Eastern China |
| Mapping the Global Mangrove Forest | aboveground | Biomass Using Multisource Remote Sensing Data |
| Mapping the Spatial Distribution of Colombia's Forest | aboveground | Biomass Using SAR and Optical Data |
| Mapping Tree Canopy Cover and | aboveground | Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest |
| Mapping Two Decades of New York State Forest | aboveground | Biomass Change Using Remote Sensing |
| Modeling | aboveground | Biomass in Dense Tropical Submontane Rainforest Using Airborne Laser Scanner Data |
| Modeling | aboveground | tree woody biomass using national-scale allometric methods and airborne lidar |
| Modeling and Mapping Agroforestry | aboveground | Biomass in the Brazilian Amazon Using Airborne Lidar Data |
| Modeling Forest | aboveground | Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest |
| Modeling Forest | aboveground | Carbon Density in the Brazilian Amazon with Integration of MODIS and Airborne LiDAR Data |
| Modelling | aboveground | Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data |
| Monitoring Pasture | aboveground | Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery |
| Multi-Platform LiDAR for Non-Destructive Individual | aboveground | Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian Approach |
| National Forest | aboveground | Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China |
| National, Detailed Map of Forest | aboveground | Carbon Stocks in Mexico, A |
| New Approach for the Extraction of | aboveground | Circular Structures From Near-Nadir VHR Satellite Imagery, A |
| New Forest | aboveground | Biomass Maps of China Integrating Multiple Datasets |
| Novel Hybrid GOA-XGB Model for Estimating Wheat | aboveground | Biomass Using UAV-Based Multispectral Vegetation Indices, A |
| Object-Based Mapping of | aboveground | Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data |
| Optimising three-band spectral indices to assess aerial N concentration, N uptake and | aboveground | biomass of winter wheat remotely in China and Germany |
| Optimization of Samples for Remote Sensing Estimation of Forest | aboveground | Biomass at the Regional Scale |
| Polinsar Based Scattering Information Retrieval for Forest | aboveground | Biomass Estimation |
| PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest | aboveground | Biomass Estimation |
| Precipitation Conditions Constrain the Sensitivity of | aboveground | Net Primary Productivity in Tibetan Plateau Grasslands to Climate Change |
| Prediction of | aboveground | Biomass of Three Cassava (Manihot esculenta) Genotypes Using a Terrestrial Laser Scanner |
| Prediction of Forest | aboveground | Biomass Using Multitemporal Multispectral Remote Sensing Data |
| Prediction of Urban Forest | aboveground | Carbon Using Machine Learning Based on Landsat 8 and Sentinel-2: A Case Study of Shanghai, China |
| Progress in the remote sensing of C3 and C4 grass species | aboveground | biomass over time and space |
| Proposed Ensemble Feature Selection Method for Estimating Forest | aboveground | Biomass from Multiple Satellite Data, A |
| Quantifying | aboveground | Biomass of Shrubs Using Spectral and Structural Metrics Derived from UAS Imagery |
| Quantifying Live | aboveground | Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data |
| Quantifying Post-Fire Changes in the | aboveground | Biomass of an Amazonian Forest Based on Field and Remote Sensing Data |
| Quantifying the Spatial Heterogeneity and Driving Factors of | aboveground | Forest Biomass in the Urban Area of Xi'an, China |
| Quick | aboveground | Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle |
| Reducing Uncertainty in Mapping of Mangrove | aboveground | Biomass Using Airborne Discrete Return Lidar Data |
| Reduction in Uncertainty in Forest | aboveground | Biomass Estimation Using Sentinel-2 Images: A Case Study of Pinus densata Forests in Shangri-La City, China |
| Refined | aboveground | Biomass Estimation of Moso Bamboo Forest Using Culm Lengths Extracted from TLS Point Cloud |
| Regional Tropical | aboveground | Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels |
| Regional-Scale High Spatial Resolution Mapping of | aboveground | Net Primary Productivity (ANPP) from Field Survey and Landsat Data: A Case Study for the Country of Wales |
| Relationships of S-Band Radar Backscatter and Forest | aboveground | Biomass in Different Forest Types |
| Remote Estimation of Mangrove | aboveground | Carbon Stock at the Species Level Using a Low-Cost Unmanned Aerial Vehicle System |
| Remote Sensing Estimates of Grassland | aboveground | Biomass Based on MODIS Net Primary Productivity (NPP): A Case Study in the Xilingol Grassland of Northern China |
| remote sensing-based model of tidal marsh | aboveground | carbon stocks for the conterminous United States, A |
| Retrieval of Forest | aboveground | Biomass and Stem Volume with Airborne Scanning LiDAR |
| Retrieval of Grassland | aboveground | Biomass through Inversion of the PROSAIL Model with MODIS Imagery |
| Retrieval of Mangrove | aboveground | Biomass at the Individual Species Level with WorldView-2 Images |
| Retrieving Secondary Forest | aboveground | Biomass from Polarimetric ALOS-2 PALSAR-2 Data in the Brazilian Amazon |
| Review of Estimation Methods for | aboveground | Biomass in Grasslands Using UAV, A |
| Satellite-Derived Estimation of Grassland | aboveground | Biomass in the Three-River Headwaters Region of China during 1982-2018 |
| Seamless Upscaling of the Field-Measured Grassland | aboveground | Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance |
| Sensitivity of L-Band SAR Backscatter to | aboveground | Biomass of Global Forests |
| Sensitivity of Multi-Source SAR Backscatter to Changes in Forest | aboveground | Biomass |
| Signatures of Wetland Impact: Spatial Distribution of Forest | aboveground | Biomass in Tumen River Basin |
| Simulation of the Grazing Effects on Grassland | aboveground | Net Primary Production Using DNDC Model Combined with Time-Series Remote Sensing Data: A Case Study in Zoige Plateau, China |
| Small Field Plots Can Cause Substantial Uncertainty in Gridded | aboveground | Biomass Products from Airborne Lidar Data |
| Spatial Scale Effect and Correction of Forest | aboveground | Biomass Estimation Using Remote Sensing |
| Spatial-Temporal Characteristics and Driving Forces of | aboveground | Biomass in Desert Steppes of Inner Mongolia, China in the Past 20 Years |
| Spatially-Explicit Testing of a General | aboveground | Carbon Density Estimation Model in a Western Amazonian Forest Using Airborne LiDAR |
| Spatio-Temporal Variation Characteristics of | aboveground | Biomass in the Headwater of the Yellow River Based on Machine Learning |
| Spatiotemporal Estimation of Bamboo Forest | aboveground | Carbon Storage Based on Landsat Data in Zhejiang, China |
| Stratification-Based Forest | aboveground | Biomass Estimation in a Subtropical Region Using Airborne Lidar Data |
| Synergy of ICESat-2 and Landsat for Mapping Forest | aboveground | Biomass with Deep Learning |
| Synthesis of Leaf-on and Leaf-off Unmanned Aerial Vehicle (UAV) Stereo Imagery for the Inventory of | aboveground | Biomass of Deciduous Forests |
| Systematic Review of the Factors Influencing the Estimation of Vegetation | aboveground | Biomass Using Unmanned Aerial Systems, A |
| TerraSAR-X Stereo Radargrammetry and Airborne Scanning LiDAR Height Metrics in Imputation of Forest | aboveground | Biomass and Stem Volume |
| Terrestrial Laser Scanning for Non-Destructive Estimation of | aboveground | Biomass in Short-Rotation Poplar Coppices |
| Towards Prediction and Mapping of Grassland | aboveground | Biomass Using Handheld LiDAR |
| Trees, Forest, Stem Volume, | aboveground | Biomass Measurements |
| Trends of | aboveground | Net Primary Productivity of Patagonian Meadows, the Omitted Ecosystem in Desertification Studies |
| Two-Stream Dense Feature Fusion Network Based on RGB-D Data for the Real-Time Prediction of Weed | aboveground | Fresh Weight in a Field Environment |
| Use of Remotely Sensed Data to Enhance Estimation of | aboveground | Biomass for the Dry Afromontane Forest in South-Central Ethiopia |
| Using Airborne Lidar, Multispectral Imagery, and Field Inventory Data to Estimate Basal Area, Volume, and | aboveground | Biomass in Heterogeneous Mixed Species Forests: A Case Study in Southern Alabama |
| Using APAR to Predict | aboveground | Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ |
| Using ICESat-2 to Estimate and Map Forest | aboveground | Biomass: A First Example |
| Using Landsat OLI and Random Forest to Assess Grassland Degradation with | aboveground | Net Primary Production and Electrical Conductivity Data |
| Variables Selection for | aboveground | Biomass Estimations Using Satellite Data: A Comparison between Relative Importance Approach and Stepwise Akaike's Information Criterion |
| Woody | aboveground | Biomass Mapping of the Brazilian Savanna with a Multi-Sensor and Machine Learning Approach |
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