Project Funding: 2017 - 2020

NRA: 2016 NASA: Carbon Monitoring System   

Funded by NASA

Abstract:
The proposed research focuses on the application and further development of C Stock mapping and estimation from multiple satellite and airborne remote sensing platforms, with a focus on mangrove and tropical peatland forests. One main goal of this proposed project is to develop a standardized MRV (monitoring, reporting and verification) methodology that incorporates canopy height measurements from multiple Remote Sensing sources (TanDEM-X, High Resoluiton stereo, Lidar where available) to estimate extent, stocks and both spatial and vertical changes that can be incorporated and approved not only for scientific applications, but also for MRV (monitoring, reporting, verification) in voluntary Carbon markets. Here we propose to help advance the field of carbon standards and MRV methodologies, by incorporating the new set of methods using active InSAR, Polarimetric InSAR, Lidar and optical stereo data. We will also propose to begin the integration of remote sensing observations of forest canopy height and biomass within a mangrove ecosystem model to advance the Tier-3 certification process for tropical forest wetlands. Mangrove and Peatland forests are experiencing rapid decline, either through land conversion for commodity production (aquaculture, rice, oil palm), unsustainable harvesting for timber and charcoal, or poor management. To counter this trend, a large focus is in restoration and reforestation and the determining what types of observations are required to monitor the successful regeneration of forests. Thus, we also propose to further our ongoing work in estimating mangrove forest rates of change from TanDEM-X and Very High Resolution Stereo data 1) to monitor and evaluate the efficacy of existing mangrove and peatland restoration projects and 2) provide quantitative historical data on mangrove and adjoining peatland forest extent that will aid in development phase of planned restoration projects. One main goal of this proposed project is to develop a standardized MRV (monitoring, reporting and verification) methodology that incorporates canopy height measurements from multiple RS sources (TanDEM-X, VHRS, Lidar or other data) to estimate extent, stocks and both spatial and vertical changes that can be incorporated and approved not only for scientific applications, but also for MRV in voluntary Carbon markets. The objectives for this proposed project are: 1. Reduce the uncertainty and increase the Application Readiness Level (ARL) of mangrove and peatland forest extent, vertical structure and change (gain, loss, growth rates) maps in Africa and South-East Asia using multi-sensor data 2. Improve total carbon stock estimates and emissions for mangroves and peatland forests using forest vertical structure and relationships of soil C with geophysical factors, with propagated sources and estimates of error. 3. Prototype the development of MRV systems for mangrove forests that are compliant with IPCC Tier 3 emissions through the integration of remote sensing observations of forest canopy height into a NPP model that allocates carbon increment to specific C pools. 4. Develop a MRV Certification Prototypes for Mangrove and Peatlands that advances more traditional MRV methods to include forest structure from multiple remotely sensed datasets. This project is an extension of a current CMS project ending in 2017 (CMS I) focused on Total C estimation in Blue Carbon ecosystems (specifically mangroves) in three countries of Africa Gabon, Tanzania, Mozambique. We will expand the current geographical focus of the project to coastal areas in West Africa and South-East Asia. In addition, we are also expanding our focus from mangroves, to adjoining tropical freshwater peat forests (primarily in Indonesia, but also in Ghana). Our collaborators and stakeholders are existing REDD project developers in Asia and Africa, sustainable logging companies, Universities and International Biodiversity and conservation projects.

Publications:

Campbell, A. D., Fatoyinbo, L., Goldberg, L., Lagomasino, D. 2022. Global hotspots of salt marsh change and carbon emissions. Nature. DOI: 10.1038/s41586-022-05355-z

Campbell, A. D., Fatoyinbo, T., Charles, S. P., Bourgeau-Chavez, L. L., Goes, J., Gomes, H., Halabisky, M., Holmquist, J., Lohrenz, S., Mitchell, C., Moskal, L. M., Poulter, B., Qiu, H., Resende De Sousa, C. H., Sayers, M., Simard, M., Stewart, A. J., Singh, D., Trettin, C., Wu, J., Zhang, X., Lagomasino, D. 2022. A review of carbon monitoring in wet carbon systems using remote sensing. Environmental Research Letters. 17(2), 025009. DOI: 10.1088/1748-9326/ac4d4d

Fatoyinbo, T., Feliciano, E. A., Lagomasino, D., Lee, S. K., Trettin, C. 2018. Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta. Environmental Research Letters. 13(2), 025012. DOI: 10.1088/1748-9326/aa9f03

Lagomasino, D., Fatoyinbo, T., Lee, S., Feliciano, E., Trettin, C., Shapiro, A., Mangora, M. M. 2019. Measuring mangrove carbon loss and gain in deltas. Environmental Research Letters. 14(2), 025002. DOI: 10.1088/1748-9326/aaf0de

Lee, S., Fatoyinbo, T. E., Lagomasino, D., Feliciano, E., Trettin, C. 2018. Multibaseline TanDEM-X Mangrove Height Estimation: The Selection of the Vertical Wavenumber. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(10), 3434-3442. DOI: 10.1109/JSTARS.2018.2835647

Mondal, P., Liu, X., Fatoyinbo, T. E., Lagomasino, D. 2019. Evaluating Combinations of Sentinel-2 Data and Machine-Learning Algorithms for Mangrove Mapping in West Africa. Remote Sensing. 11(24), 2928. DOI: 10.3390/rs11242928

Simard, M., Fatoyinbo, L., Smetanka, C., Rivera-Monroy, V. H., Castaneda-Moya, E., Thomas, N., Van der Stocken, T. 2018. Mangrove canopy height globally related to precipitation, temperature and cyclone frequency. Nature Geoscience. 12(1), 40-45. DOI: 10.1038/s41561-018-0279-1

Thomas, N., Bunting, P., Lucas, R., Hardy, A., Rosenqvist, A., Fatoyinbo, T. 2018. Mapping Mangrove Extent and Change: A Globally Applicable Approach. Remote Sensing. 10(9), 1466. DOI: 10.3390/rs10091466

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile
• NASA Carbon Monitoring System (CMS) Project Profile