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RESEARCH PRODUCT

Mapping Carbon Stocks In Central And South America With Smap Vegetation Optical Depth

Alessandro CescattiGregory DuveillerDavid ChaparroAdriano CampsMaria PilesDara EntekhabiM. Vall-llossera

subject

CanopyL bandTeledetecció010504 meteorology & atmospheric sciencesRadiofreqüència0208 environmental biotechnologyClimate changeOptical radar02 engineering and technology01 natural sciencesComunicacions òptiquesCarboniImage resolution0105 earth and related environmental sciencesRemote sensingVegetation mappingVegetationOptical communicationsTropicsEnhanced vegetation indexRemote sensing:Enginyeria de la telecomunicació [Àrees temàtiques de la UPC]Carbon020801 environmental engineering:Enginyeria de la telecomunicació::Telecomunicació òptica [Àrees temàtiques de la UPC]Climate change mitigationRemote sensing by laser beamSpatial ecologyEnvironmental scienceSistemes de gestió mediambiental

description

Mapping carbon stocks in the tropics is essential for climate change mitigation. Passive microwave remote sensing allows estimating carbon from deep canopy layers through the Vegetation Optical Depth (VOD) parameter. Although their spatial resolution is coarser than that of optical vegetation indices or airborne Lidar data, microwaves present a higher penetration capacity at low frequencies (L-band) and avoid cloud masking. This work compares the relationships of airborne carbon maps in Central and South America with both (i) SMAP L-band VOD at 9 km gridding and (ii) MODIS Enhanced Vegetation Index (EVI). Models to estimate carbon stocks are built from these two satellite-derived variables. Results show that L-band VOD has a greater capacity to model carbon variability than EVI. The resulting VOD-derived carbon estimates are further presented at a detailed (9 km) spatial scale. The L-band VOD data are available from the authors upon request. This study has been supported by the Spanish government through the projects ESP2015-67549-C3-1-R and ESP2017-89463-C3-2-R, and through the award "Unidad de Excelencia María de Maeztu" MDM-2016-0600, financed by the "Agencia Estatal de Investigación" (Spain). The study has been supported also by the European Regional development Fund (ERDF). Maria Piles is supported by a Ramón y Cajal contract (MINECO) and by the project RTI2018-096765-A-100 (MCIU/AEI/FEDER, UE). We thank the Carnegie Airborne Observatory for making the AGB maps available. Peer Reviewed

yearjournalcountryeditionlanguage
2019-01-01IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
https://doi.org/10.1109/igarss.2019.8900244