455
17.2.3 Carbon Storage
Biomass estimates are fundamental to estimate carbon fluxes and stocks and link
them to carbon credit initiatives. Active RS such as laser scanning provides fundamental data on canopy structure useful to include in allometric equations to estimate
biomass (Chave et al. 2014). For example, the analysis of first returns from laser
scanning is used to estimate canopy height (Bouvet et al. 2017). Recent Terrestrial
Laser Scanning (TLS) technology shows promising advances in more accurate estimates of biomass because it allows for a first-order estimate of diameter at breast
height. Further, TLS analysis is able to provide more precise representation of tree
structure, allowing for moving beyond the assumed cylindrical shape of a tree trunk
used for many biomass estimates. Novel methods also make it possible to fit geometric shapes along not only the trunk but also the branches and stems, giving a
more precise estimate of the woody component of trees and producing more reliable
estimates of biomass.
Another area of active research in carbon storage and credits is the estimation of
tree cover and the number of trees per pixel, because even if the biomass per tree is
correctly estimated, it is scaled to regional or global estimates by a multiplier of tree
density. MODIS offers a tree cover product (as a layer within the Vegetation
Continuous Fields product) systematically and repeatedly at a global scale, but this
product makes some assumptions on the minimum cover of trees needed to be
detected by the MODIS sensors. In addition, it is important to estimate the contribution of non-tree functional types such as shrubs and grasslands to the carbon storage
and credits calculations. Current assessments of the performance of reducing emissions from deforestation and forest degradation (REDD+) programs have shown
varied success; most are linked to the quality of the biomass estimates, which are
fundamental to calculate the carbon potential of a given ecosystem as a fraction
(often assumed around 1/2) of its biomass.
17.2.4 Challenges
Although there is a clear role for RS for monitoring ecosystem functions (see
Serbin and Townsend, Chap. 3; Martin, Chap. 5), there are still many challenges to
be overcome to ensure its full potential is realized. Many acknowledge the lack of
an acceptable framework that brings together the many proxies for ecosystem
functioning that can be directly remotely sensed (e.g., Asner and Olinger 2009; De
Araujo Barbosa et al. 2015). But fundamentally there is a need to improve the RS
estimates of the many proxies that are used to infer the ecosystem functions of
interest. Developments in methodologies for processing, analyzing, and interpreting RS data will serve to improve the mapping accuracy and monitoring opportunities. However, those developments cannot exist in isolation; a dialogue between
computational scientists and those concerned with ecosystem functions must occur
17 Integrating Biodiversity, Remote Sensing, and Auxiliary Information for the Study…
17.2.3 Carbon Storage
Biomass estimates are fundamental to estimate carbon fluxes and stocks and link
them to carbon credit initiatives. Active RS such as laser scanning provides fundamental data on canopy structure useful to include in allometric equations to estimate
biomass (Chave et al. 2014). For example, the analysis of first returns from laser
scanning is used to estimate canopy height (Bouvet et al. 2017). Recent Terrestrial
Laser Scanning (TLS) technology shows promising advances in more accurate estimates of biomass because it allows for a first-order estimate of diameter at breast
height. Further, TLS analysis is able to provide more precise representation of tree
structure, allowing for moving beyond the assumed cylindrical shape of a tree trunk
used for many biomass estimates. Novel methods also make it possible to fit geometric shapes along not only the trunk but also the branches and stems, giving a
more precise estimate of the woody component of trees and producing more reliable
estimates of biomass.
Another area of active research in carbon storage and credits is the estimation of
tree cover and the number of trees per pixel, because even if the biomass per tree is
correctly estimated, it is scaled to regional or global estimates by a multiplier of tree
density. MODIS offers a tree cover product (as a layer within the Vegetation
Continuous Fields product) systematically and repeatedly at a global scale, but this
product makes some assumptions on the minimum cover of trees needed to be
detected by the MODIS sensors. In addition, it is important to estimate the contribution of non-tree functional types such as shrubs and grasslands to the carbon storage
and credits calculations. Current assessments of the performance of reducing emissions from deforestation and forest degradation (REDD+) programs have shown
varied success; most are linked to the quality of the biomass estimates, which are
fundamental to calculate the carbon potential of a given ecosystem as a fraction
(often assumed around 1/2) of its biomass.
17.2.4 Challenges
Although there is a clear role for RS for monitoring ecosystem functions (see
Serbin and Townsend, Chap. 3; Martin, Chap. 5), there are still many challenges to
be overcome to ensure its full potential is realized. Many acknowledge the lack of
an acceptable framework that brings together the many proxies for ecosystem
functioning that can be directly remotely sensed (e.g., Asner and Olinger 2009; De
Araujo Barbosa et al. 2015). But fundamentally there is a need to improve the RS
estimates of the many proxies that are used to infer the ecosystem functions of
interest. Developments in methodologies for processing, analyzing, and interpreting RS data will serve to improve the mapping accuracy and monitoring opportunities. However, those developments cannot exist in isolation; a dialogue between
computational scientists and those concerned with ecosystem functions must occur
17 Integrating Biodiversity, Remote Sensing, and Auxiliary Information for the Study…