Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest

2012 ◽  
Vol 69 ◽  
pp. 121-133 ◽  
Author(s):  
Olivier W. Tsui ◽  
Nicholas C. Coops ◽  
Michael A. Wulder ◽  
Peter L. Marshall ◽  
Adrian McCardle
Keyword(s):  
Temperate Forest ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Lidar Measurements ◽  
Biomass Components

Biomass dynamics of central Siberian Scots pine forests following surface fires of varying severity

2014 ◽  
Vol 23 (6) ◽  
pp. 872 ◽  
Author(s):  
Elena A. Kukavskaya ◽  
Galina A. Ivanova ◽  
Susan G. Conard ◽  
Douglas J. McRae ◽  
Valery A. Ivanov
Keyword(s):  
Scots Pine ◽  
Pine Forest ◽  
Prescribed Fires ◽  
Above Ground Biomass ◽  
Fuel Loading ◽  
High Severity ◽  
Ground Biomass ◽  
Scots Pine Forests ◽  
Biomass Components ◽  
Scots Pine Forest

In 2000–2002 nine 4-ha prescribed fires of various severities were conducted on experimental plots in mature Scots pine forest in the central Siberian taiga, Russia. Total above-ground living biomass decreased after low- and moderate-severity fires by 10 and 15%, whereas high-severity fire reduced living above-ground biomass by 83%. We monitored changes in fuel structure and biomass for 6–8 years following these fires. By 6–8 years after burning the ground fuel loading had recovered to 101, 96 and 82% of pre-fire levels after fires of low-, moderate- and high-severity. Down woody fuel loading increased by 0.18±0.04kgm–2year–1. We developed regressions relating time since fire to changes in above-ground biomass components for fires of different severity for feather moss–lichen Scots pine forest of Siberia. Our results demonstrate the importance of both burn severity and composition of pre-fire surface vegetation in determining rates and patterns of post-fire vegetation recovery on dry Scots pine sites in central Siberia.

scholarly journals Above-Ground Biomass and Biomass Components Estimation Using LiDAR Data in a Coniferous Forest

Forests ◽  
2013 ◽  
Vol 4 (4) ◽  
pp. 984-1002 ◽  
Author(s):  
Qisheng He ◽  
Erxue Chen ◽  
Ru An ◽  
Yong Li
Keyword(s):  
Coniferous Forest ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Biomass Components

scholarly journals Allometric Equations for Estimation of Biomass and Carbon Stocks in Temperate Forests of North-Western Mexico

2017 ◽  
Author(s):  
Benedicto Vargas-Larreta ◽  
Carlos Antonio López-Sánchez ◽  
José Javier Corral-Rivas ◽  
Jorge Omar López-Martínez ◽  
Cristóbal Gerardo Aguirre-Calderón ◽  
...  
Keyword(s):  
Temperate Forests ◽  
Generalized Method Of Moments ◽  
Stem Bark ◽  
Machine Learning Techniques ◽  
Above Ground Biomass ◽  
Data Set ◽  
Stem Wood ◽  
Ground Biomass ◽  
Biomass Components ◽  
Northwestern Mexico

This paper presents new above-ground biomass (AGB) and biomass components equations for seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. Generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. Additionally, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The fitted equations accounted for on average 91, 83, 84 and 78% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of h or d2h as additional predictor in the d-only based equations systems slightly improved estimates of stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The fitted equations were used to estimate AGB stocks at stand level from a database on growing stock from 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were applied to map the AGB and carbon distributions in the study area, which yielded mean values of 129.84 Mg ha-1 and 63.80 Mg ha-1, respectively.

ESTIMATION OF ABOVE GROUND BIOMASS OF THE THREE SITES (GRAZED SITE, PROTECTED SITE AND SEED SOWN SITE) FOR COMPARING THEIR PRODUCTIVITY IN KASHMIR VALLEY

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  
Keyword(s):  
Protected Areas ◽  
Aboveground Biomass ◽  
Plant Biomass ◽  
Summer Season ◽  
Above Ground Biomass ◽  
Spring Season ◽  
Kashmir Valley ◽  
Ground Biomass ◽  
Maximum Value ◽  
Protected Site

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.

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