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Journal ArticleDOI

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

TLDR
A survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables fromRemote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure.
Abstract
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This...

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Nationwide native forest structure maps for Argentina based on forest inventory data, SAR Sentinel-1 and vegetation metrics from Sentinel-2 imagery

TL;DR: In this article , the authors used synthetic aperture radar (SAR) and optical remote sensing (ORS) to map forest structure attributes (diameter at breast height, basal area, mean height, dominant height, wood volume and canopy cover) at 30-m resolution across the diverse 463,000 km2 of native forests of Argentina based on SAR Sentinel-1, vegetation metrics from Sentinel-2 and geographic coordinates.
Journal ArticleDOI

Mapping Woody Volume of Mediterranean Forests by Using SAR and Machine Learning: A Case Study in Central Italy

TL;DR: In this paper, an approach based on an artificial neural network (ANN) was implemented to estimate forest biomass in Tuscany, in Central Italy, using ground measurements of woody volume (WV, in m3/ha).
Journal ArticleDOI

Mapping Forest Vertical Structure in Sogwang-ri Forest from Full-Waveform Lidar Point Clouds Using Deep Neural Network

TL;DR: Li et al. as mentioned in this paper proposed a method for estimating the vertical structure of forests based on full-wave-form light detection and ranging (FW LiDAR) data in this study.

Monitoring miombo woodlands of Southern Africa with multi-source information in a model-based framework

TL;DR: In this article, the authors present a Table of Table of contents for the table of contents of the table: https://www.tableoffeatures.com/table-of-features/
Journal ArticleDOI

Exploring the inclusion of small regenerating trees to improve above-ground forest biomass estimation using geospatial data

TL;DR: This study suggests that for young, open forests where there are many small regenerating trees, the contribution of understory biomass should be taken into consideration to improve total AGB estimation.
References
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Journal ArticleDOI

Random Forests

TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Journal ArticleDOI

Maximum entropy modeling of species geographic distributions

TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
Journal ArticleDOI

High-Resolution Global Maps of 21st-Century Forest Cover Change

TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
Journal ArticleDOI

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
BookDOI

Assessing the accuracy of remotely sensed data : principles and practices

TL;DR: This chapter discusses Accuracy Assessment, which examines the impact of sample design on cost, statistical Validity, and measuring Variability in the context of data collection and analysis.
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