Results 11 to 20 of about 93,282 (261)

Improved Model-Based Forest Height Inversion Using Airborne L-Band Repeat-Pass Dual-Baseline Pol-InSAR Data

Remote Sensing, 2022
This paper proposes an improved model-based forest height inversion method for airborne L-band dual-baseline repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) collections.
Qi Zhang, Scott Hensley, Ruiheng Zhang, Chang Liu, Linlin Ge   +4 more
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On factorization forests of finite height

Theoretical Computer Science, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jérémie Chalopin, Hing Leung
openaire   +3 more sources

Evaluating Variable Selection and Machine Learning Algorithms for Estimating Forest Heights by Combining Lidar and Hyperspectral Data

ISPRS International Journal of Geo-Information, 2020
Machine learning has been employed for various mapping and modeling tasks using input variables from different sources of remote sensing data. For feature selection involving high- spatial and spectral dimensionality data, various methods have been ...
Sanjiwana Arjasakusuma, Sandiaga Swahyu Kusuma, Stuart Phinn   +2 more
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Investigation the Effect of the Forest Height and Forest Density on the Accuracy of Forest Height Estimation Methods Using PolInSAR Data [PDF]

علوم، فناوری و کاربردهای فضایی, 2022
Forest biomass is one of the most important parameters in the ecosystem changes assessment and global carbon cycle modelling. In the other hand, the forest height is an effective parameter in the allometric equations which are used for biomass estimation.
Tayebe Managhebi, Akram JafarAghaee
doaj   +1 more source

An Improved Forest Height Model Using L-Band Single-Baseline Polarimetric InSAR Data for Various Forest Densities

Remote Sensing, 2022
Forest density affects the inversion of forest height by influencing the penetration and attenuation of synthetic aperture radar (SAR) signals. Traditional forest height inversion methods often fail in low-density forest areas.
Ao Sui, Opelele Omeno Michel, Yu Mao, Wenyi Fan   +3 more
doaj   +1 more source

A Modified Dual-Baseline PolInSAR Method for Forest Height Estimation

Remote Sensing, 2017
This paper investigates the potentials and limitations of a simple dual-baseline PolInSAR (DBPI) method for forest height inversion. This DBPI method follows the classical three-stage inversion method’s idea used in single baseline PolInSAR (SBPI ...
Qinghua Xie, Jianjun Zhu, Changcheng Wang, Haiqiang Fu, Juan M. Lopez-Sanchez, J. David Ballester-Berman   +5 more
doaj   +1 more source

Estimation of change in forest height growth [PDF]

Forestry Studies, 2017
Abstract Forest height increment rate is related to the forest growth conditions. Data bases of previous forest inventories contain information about forest heightage relationship on large number of forest stands while repeated measurements of permanent sample plots provide an excellent reference for comparison.
Lang Mait, Arumäe Tauri, Laarmann Diana, Kiviste Andres   +3 more
openaire   +2 more sources

The BIOMASS Level 2 Prototype Processor: Design and Experimental Results of Above-Ground Biomass Estimation

Remote Sensing, 2020
BIOMASS is ESA’s seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes.
Francesco Banda, Davide Giudici, Thuy Le Toan, Mauro Mariotti d’Alessandro, Kostas Papathanassiou, Shaun Quegan, Guido Riembauer, Klaus Scipal, Maciej Soja, Stefano Tebaldini, Lars Ulander, Ludovic Villard   +11 more
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Forest Height Mapping Using Feature Selection and Machine Learning by Integrating Multi-Source Satellite Data in Baoding City, North China

Remote Sensing, 2022
Accurate estimation of forest height is crucial for the estimation of forest aboveground biomass and monitoring of forest resources. Remote sensing technology makes it achievable to produce high-resolution forest height maps in large geographical areas ...
Nan Zhang, Mingjie Chen, Fan Yang, Cancan Yang, Penghui Yang, Yushan Gao, Yue Shang, Daoli Peng   +7 more
doaj   +1 more source

Constructing a Finer-Resolution Forest Height in China Using ICESat/GLAS, Landsat and ALOS PALSAR Data and Height Patterns of Natural Forests and Plantations

Remote Sensing, 2019
Monitoring forest height is crucial to determine the structure and biodiversity of forest ecosystems. However, detailed spatial patterns of forest height from 30 m resolution remotely sensed data are currently unavailable. In this study, we present a new
Huabing Huang, Caixia Liu, Xiaoyi Wang
doaj   +1 more source