Combining field and remote sensing data to estimate forest canopy ...

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions, ...

(PDF) Combining field and remote sensing data to estimate forest ...

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions.

Article on Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical ...

Combining field and remote sensing data to estimate forest canopy ...

As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ...

Combining GEDI and sentinel data to estimate forest canopy mean ...

Remote Sensing-based forest AGB estimation methods can be divided into single and multi-source data. Estimation methods based on single optical data are often ...

Combining remote sensing imagery and forest age inventory for ...

In this study, Landsat ETM+ images and field forest inventory data were used to estimate AGB of forests in Liping County, Guizhou Province, China. Three ...

Modeling Forest Canopy Cover: A Synergistic Use of Sentinel-2 ...

While the combined use of these two remote sensing platforms ... Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China.

Improving estimates of forest disturbance by combining observations ...

In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a ...

Estimating Forest Canopy Cover by Multiscale Remote Sensing in ...

CC data can also be employed for prediction of woody plant composition, tree stand volume, forage production, and for monitoring and assessment ...

A cross-comparison of field, spectral, and lidar estimates of forest ...

Canadian Journal of Remote Sensing. 36(5): 447-459. Download (PDF 1.22 MB) ... forest canopy cover, cross-comparison, reflective spectral satellite data, light ...

"Mapping Forest Canopy Structure with On-Demand Fusion of ...

... remotely sensed data and field data from across the United States. Canopy height profiles, which are highly sensitive to horizontal canopy variability, are ...

Canopy gaps and associated losses of biomass – combining UAV ...

Combining high-resolution remote sensing with forest inventory data ... We believe our approach of combining field with remote sensing data ...

Combining satellite and field data reveals Congo's forest types ...

Although most current remote sensing data rapidly saturate with forest structure (Jha et al., 2021), some studies have shown that the spectral ...

Forest biomass assessment combining field inventorying and ...

... remote sensing data [63]. They are a useful measure for determining the vigor and productivity of the vegetation [64]. VIs have also been ...

Modeling Forest Canopy Cover: A Synergistic Use of Sentinel-2 ...

Here, we present an approach of combining Sentinel-2 data, high-resolution aerial images, and machine learning (ML) algorithms to model FCC in ...

A cross-comparison of field, spectral, and lidar estimates of forest ...

Estimating forest canopy fuel parameters using LIDAR data. ... mixing models to generate fraction images derived from remote sensing multispectral data.

Remote sensing-based high-resolution mapping of the forest ... - GMD

The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques,

Estimation of Forest Canopy Cover by Combining ICESat-2/

Abstract—Accurately estimating forest canopy cover (FCC) is challenging by using traditional remote sensing images at the regional level due to the spectral ...

Forest canopy height retrieval using LiDAR data, medium-resolution ...

to spatially estimate forest canopy ... 2008 Combining national forest inventory field plots and remote sensing data for forest databases.