Leal, Ligaya Rubas (2015-05). Application of Remote Sensing Technology and Ecological Modeling of Forest Carbon Stocks in Mt. Apo Natural Park, Philippines. Doctoral Dissertation. Thesis uri icon

abstract

  • This dissertation work explored the application of remote sensing technology for the assessment of forest carbon storage in Mt. Apo Natural Park. Biomass estimation is traditionally conducted using destructive sampling with high levels of uncertainty. A more accurate and non-destructive method for assessment of biomass level is imperative to characterize remaining forest cover. This research study aimed to: 1) examine the vegetation profile and estimate species-specific biomass of Mt. Apo Natural Park, 2) develop an algorithm to assess biomass in plot-level using a terrestrial lidar system (TLS), and 3) generate landscape-level biomass estimates using interferometric synthetic aperture radar (IFSAR). This research endeavors to provide answers to these questions: 1) how the 3 tropical allometries compare in estimating field collected species-level biomass and carbon stocks in three management zones?, 2) what are the significant terrestrial laser scanning-derived metrics to assess plot-level biomass?, and 3) to what degree of uncertainty can IFSAR estimate biomass at the landscape level? Field data was gathered from 1382 trees, covering 52 local species during fieldwork in July and August 2013. Twenty-six plots (30 m x 30 m) were sampled on three management zones: multiple use, strict protection and restoration. Local insurgency problems restricted the research team from sampling additional plots. Destructive sampling was not permitted inside the protected area, thus requiring biomass to be estimated via the use of referenced biomass from 3 allometric equations by relating tree height, diameter-at-breast height, and wood specificity volume. A vegetation profile across the park was generated using a canopy height map (CHM). Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC's Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities. Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC's Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities.
  • This dissertation work explored the application of remote sensing technology for the assessment of forest carbon storage in Mt. Apo Natural Park. Biomass estimation is traditionally conducted using destructive sampling with high levels of uncertainty. A more accurate and non-destructive method for assessment of biomass level is imperative to characterize remaining forest cover. This research study aimed to: 1) examine the vegetation profile and estimate species-specific biomass of Mt. Apo Natural Park, 2) develop an algorithm to assess biomass in plot-level using a terrestrial lidar system (TLS), and 3) generate landscape-level biomass estimates using interferometric synthetic aperture radar (IFSAR). This research endeavors to provide answers to these questions: 1) how the 3 tropical allometries compare in estimating field collected species-level biomass and carbon stocks in three management zones?, 2) what are the significant terrestrial laser scanning-derived metrics to assess plot-level biomass?, and 3) to what degree of uncertainty can IFSAR estimate biomass at the landscape level? Field data was gathered from 1382 trees, covering 52 local species during fieldwork in July and August 2013. Twenty-six plots (30 m x 30 m) were sampled on three management zones: multiple use, strict protection and restoration. Local insurgency problems restricted the research team from sampling additional plots. Destructive sampling was not permitted inside the protected area, thus requiring biomass to be estimated via the use of referenced biomass from 3 allometric equations by relating tree height, diameter-at-breast height, and wood specificity volume. A vegetation profile across the park was generated using a canopy height map (CHM).



    Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC's Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities.





    Results showed that resampled IFSAR products can be used to characterize biomass and carbon storage at the landscape level. This research has demonstrated the adoption of IPCC's Tier 2, a combination of field and remote sensing data in the assessment of available biomass levels in a tropical forest. The maps created can assist in providing information for biomass and carbon level in MANP for monitoring, reporting and verification in compliance with REDD requirements. Furthermore, this study can provide helpful information regarding policy implications for reforestation and afforestation activities.

publication date

  • May 2015