scholarly journals Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

2016 ◽  
Vol 8 (7) ◽  
pp. 565 ◽  
Author(s):  
Tianyu Hu ◽  
Yanjun Su ◽  
Baolin Xue ◽  
Jin Liu ◽  
Xiaoqian Zhao ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Forest Inventory ◽  
Inventory Data ◽  
Forest Inventory Data ◽  
Optical Imagery ◽  
Forest Aboveground Biomass

scholarly journals Synthesising Existing Forest Inventory Datasets for Estimating Historical Aboveground Biomass Stocks, Growth and Mortality in Logged-over Tropical Dipterocarp Forests of Kalimantan, Indonesia

2020 ◽  
Author(s):  
Solichin Manuri ◽  
Cris Brack ◽  
Nurul Silva ◽  
Fatmi Noor'an
Keyword(s):  
Land Cover ◽  
Aboveground Biomass ◽  
Forest Inventory ◽  
Emission Factors ◽  
Forest Monitoring ◽  
Inventory Data ◽  
Permanent Sample Plots ◽  
Forest Inventory Data ◽  
Dipterocarp Forests ◽  
The Mean

Abstract Background: Extensive forest inventory data is available from commercial timber companies. For this study, over 20,000 plots were compiled for North, East and West Kalimantan provinces, with more than 17,000 of these exceeding our quality assurance tests. This study aimed to: (1) explore the potential use of existing permanent sample plots and forest inventory data established and measured by timber concessions; (2) assess uncertainties of aboveground biomass (AGB) estimates using various allometric models; (3) analyse the dynamics of AGB in logged-over dipterocarp forests; (4) analyse AGB stocks and emission factors in tropical dipterocarp ecosystems. Methods: Two types of forest monitoring datasets measured by timber companies in Indonesia were compiled and assessed in this study: permanent sample plots (PSPs) (24 1-ha plots), and the overall periodic timber inventory (OPTI) (17,301 plots). We compared various allometric equations for estimating AGB of the plots and developed a simple AGB equation using basal area (BA) as predictor. We further evaluated the AGB growth and mortality using the PSP plots. Results: We found that the model using only tree diameter (D) as a predictor variable tended to be unbiased when aggregating the estimates at larger plots. We also found that BA per hectare could explain the variation of AGB at plot level (adjusted r2 = 0.911; root mean square error [RMSE]: 27.8). We overlaid the OPTI plot with the land cover map and estimated the mean AGB of the associated land cover classes. The mean AGB of primary dryland forest, secondary dryland forest and bush classes were 281.1 + 4.0 Mg/ha, 231.5 + 1.7 Mg/ha and 179.0 + 5.0 Mg/ha, respectively. Nine years after logging, the mean AGB is still lower than the mean AGB two years after logging. The growth rate (2.5%) was still lower than the mortality rate (3.1%), and recruitment (0.2%) did not occur until seven years after logging. Conclusions: The results of this study suggest that the existing forest monitoring data should be incorporated into the carbon accounting system at district, province and national level to improve the estimation of forest biomass and emission factors related to forest degradation and deforestation. However, there is a need for data quality assessment prior the analysis and a standardised platform for nation-wide forest inventory database is therefore required.

Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

2016 ◽  
Vol 186 ◽  
pp. 626-636 ◽  
Author(s):  
Liviu Theodor Ene ◽  
Erik Næsset ◽  
Terje Gobakken ◽  
Ernest William Mauya ◽  
Ole Martin Bollandsås ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Large Scale ◽  
National Forest Inventory ◽  
National Forest ◽  
Miombo Woodlands ◽  
Inventory Data ◽  
Forest Inventory Data ◽  
Airborne Laser

scholarly journals Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

2013 ◽  
Vol 6 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Carlos A. Aguirre-Salado ◽  
Eduardo J. Treviño-Garza ◽  
Oscar A. Aguirre-Calderón ◽  
Javier Jiménez-Pérez ◽  
Marco A. González-Tagle ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Forest Inventory ◽  
Nearest Neighbor ◽  
Central Mexico ◽  
Inventory Data ◽  
K Nearest Neighbor ◽  
North Central ◽  
Forest Inventory Data

scholarly journals Rapid Assessment of Tree Damage Resulting from a 2020 Windstorm in Iowa, USA

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 555
Author(s):  
Thomas C. Goff ◽  
Mark D. Nelson ◽  
Greg C. Liknes ◽  
Tivon E. Feeley ◽  
Scott A. Pugh ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Damage Zone ◽  
Satellite Image ◽  
Rapid Assessment ◽  
Aerial Survey ◽  
Inventory Data ◽  
Tree Damage ◽  
Forest Inventory Data ◽  
Damage Susceptibility ◽  
The Impact

A need to quantify the impact of a particular wind disturbance on forest resources may require rapid yet reliable estimates of damage. We present an approach for combining pre-disturbance forest inventory data with post-disturbance aerial survey data to produce design-based estimates of affected forest area and number and volume of trees damaged or killed. The approach borrows strength from an indirect estimator to adjust estimates from a direct estimator when post-disturbance remeasurement data are unavailable. We demonstrate this approach with an example application from a recent windstorm, known as the 2020 Midwest Derecho, which struck Iowa, USA, and adjacent states on 10–11 August 2020, delivering catastrophic damage to structures, crops, and trees. We estimate that 2.67 million trees and 1.67 million m3 of sound bole volume were damaged or killed on 23 thousand ha of Iowa forest land affected by the 2020 derecho. Damage rates for volume were slightly higher than for number of trees, and damage on live trees due to stem breakage was more prevalent than branch breakage, both likely due to higher damage probability in the dominant canopy of larger trees. The absence of post-storm observations in the damage zone limited direct estimation of storm impacts. Further analysis of forest inventory data will improve understanding of tree damage susceptibility under varying levels of storm severity. We recommend approaches for improving estimates, including increasing spatial or temporal extents of reference data used for indirect estimation, and incorporating ancillary satellite image-based products.

Sign in / Sign up

Export Citation Format

Share Document