scholarly journals Assessment of Innovative Technologies and Their Readiness for Remote Sensing-Based Estimation of Forest Carbon Stocks and Dynamics

10.1596/35806 ◽  
2021 ◽  
Author(s):  
Keyword(s):  
Remote Sensing ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Innovative Technologies

scholarly journals Overview of Research Trends in Estimation of Forest Carbon Stocks Based on Remote Sensing and GIS

2011 ◽  
Vol 14 (3) ◽  
pp. 236-256 ◽  
Author(s):  
Kyoung-Min Kim ◽  
Jung-Bin Lee ◽  
Eun-Sook Kim ◽  
Hyun-Ju Park ◽  
Young-Hee Roh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing And Gis ◽  
Carbon Stocks ◽  
Research Trends ◽  
Forest Carbon

Accurate Estimation of Forest Carbon Stocks by 3-D Remote Sensing of Individual Trees

2003 ◽  
Vol 37 (6) ◽  
pp. 1198-1201 ◽  
Author(s):  
Kenji Omasa ◽  
Guo Yu Qiu ◽  
Kenichi Watanuki ◽  
Kenji Yoshimi ◽  
Yukihide Akiyama
Keyword(s):  
Remote Sensing ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Accurate Estimation ◽  
Individual Trees

scholarly journals Carbon Measurement: An Overview of Forest Carbon Estimation Methods and the Role of Geographical Information System and Remote Sensing Techniques for REDD+ Implementation

2016 ◽  
Vol 13 (1) ◽  
pp. 69-86 ◽  
Author(s):  
Thakur Bhattarai ◽  
Margaret Skutsch ◽  
David Midmore ◽  
Him Lal Shrestha
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Information System ◽  
Developing Countries ◽  
Geographical Information System ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Geographical Information ◽  
Successful Implementation

Many scientists and policy makers consider payment for environmental services, particularly carbon payment for forest management, a cost-effective and practical solution to climate change and unsustainable development. In recent years an attractive policy has been discussed under the United Nation Framework Convention on Climate Change (UNFCCC): Reducing Emissions from Deforestation and Forest Degradation (REDD+), sustainable management of forest, and conservation and enhancement of carbon in developing countries. This could potentially reward forest-managing communities in developing countries. One of the challenging tasks for the successful implementation of this policy is setting up reliable baseline emissions scenarios based on the historical emissions as input for business as usual projections. Forest biomass measurements, the quantification of carbon stocks, their monitoring, and the observation of these stocks over time, are very important for the development of reference scenario and estimation of carbon stock. This paper reviews a numbers of methods available for estimating forest carbon stocks and growth rates of different forest carbon pools. It also explores the limitations and challenges of these methods for use in different geographical locations, and suggests ways of improving accuracy and precision that reduce uncertainty for the successful implementation of REDD+. Furthermore, the paper assesses the role of remote sensing (RS) and geographical information system (GIS) techniques in the establishment of a long-term carbon inventory.Journal of Forest and Livelihood 13(1) May, 2015, Page:69-86

scholarly journals A 100-year conservation experiment: Impacts on forest carbon stocks and fluxes

2013 ◽  
Vol 310 ◽  
pp. 242-255 ◽  
Author(s):  
Tara Sharma ◽  
Werner A. Kurz ◽  
Graham Stinson ◽  
Marlow G. Pellatt ◽  
Qinglin Li
Keyword(s):  
Carbon Stocks ◽  
Forest Carbon

scholarly journals Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

2016 ◽  
Vol 13 (5) ◽  
pp. 1571-1585 ◽  
Author(s):  
Pierre Ploton ◽  
Nicolas Barbier ◽  
Stéphane Takoudjou Momo ◽  
Maxime Réjou-Méchain ◽  
Faustin Boyemba Bosela ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Reference Model ◽  
Original Data ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Biomass Estimation ◽  
Systematic Bias ◽  
Data Set ◽  
Allometric Models ◽  
Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees  ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

Sign in / Sign up

Export Citation Format

Share Document