Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approaches

Ameray, Abderrahmane; Castro, Marina; Bouhaloua, M.; Castro, João Paulo

Publication

Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approaches

2019Conference object

dc.contributor.author	Ameray, Abderrahmane
dc.contributor.author	Castro, Marina
dc.contributor.author	Bouhaloua, M.
dc.contributor.author	Castro, João Paulo
dc.date.accessioned	2019-06-07T08:31:35Z
dc.date.available	2019-06-07T08:31:35Z
dc.date.issued	2019
dc.description.abstract	Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+) recommend specific approaches for quantifying and spatializing ecosystem services (ES). In the context of climate change, REDD recommends the mapping of carbon stocks and its sequestration by vegetation cover to implement more appropriate environmental management practices and policies against global warming. Forest carbon mapping is a current and important environmental tool for a better land management as successful implementation of climate change mitigation (Saatchi et al., 2011). This study presents the mapping of carbon sequestration using two different approaches. Firstly, the direct Remote Sensing (DRS) approach using MODIS images (product MOD17) (Running & Zhao, 2015). Secondly, the indirect approach named Combine and Assign (CA) Approach (Goetz et al., 2009). MODIS images allow the accounting of Net Primary Productivity (NPP) which presents the quantity of carbon absorbed by vegetation cover during a period as a key indicator of ecosystem performance. The CA Approach combines remote sensing and field data in GIS environment to assess the yearly carbon sequestration for each ecozone and the carbon losses by fires in 2010, using the atmospheric flow proposed by Intergovernmental Panel on Climate Change (IPCC). Both CA and DRS mapping approaches show that the forest stands, generally, Pinus pinaster and Eucalyptus stands, in central and coastal areas have the higher CO2 sequestration potential. However, these two species contribute significantly to CO2 emissions comparing to all other species. The comparison between IPCC methodology and the MODIS product (MOD17) used to follow the carbon dynamic in terrestrial ecosystems has demonstrate that IPCC method can be used as a perfect method to validate MOD17 product.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Ameray, Abderrahmane; Castro, Marina; Bouhaloua, M.; Castro, João Paulo (2019). Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approaches. In 4th World Congress on Agroforestry: book of abstracts	pt_PT
dc.identifier.uri	http://hdl.handle.net/10198/19338
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Climate change	pt_PT
dc.subject	IPCC	pt_PT
dc.subject	Carbon dioxide	pt_PT
dc.subject	Geoprocessing	pt_PT
dc.subject	MODIS	pt_PT
dc.title	Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approaches	pt_PT
dc.type	conference object
dspace.entity.type	Publication
oaire.citation.conferencePlace	Montpellier	pt_PT
oaire.citation.endPage	569	pt_PT
oaire.citation.startPage	569	pt_PT
oaire.citation.title	4th World Congress on Agroforestry	pt_PT
person.familyName	Castro
person.familyName	Castro
person.givenName	Marina
person.givenName	João Paulo
person.identifier	2303569
person.identifier.ciencia-id	6417-7D8D-FD7E
person.identifier.ciencia-id	8D19-DBCC-8EF5
person.identifier.orcid	0000-0002-6368-8098
person.identifier.orcid	0000-0003-0647-8892
person.identifier.rid	B-5197-2016
person.identifier.rid	A-8581-2014
person.identifier.scopus-author-id	56612728000
person.identifier.scopus-author-id	21233448700
rcaap.rights	openAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
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relation.isAuthorOfPublication.latestForDiscovery	a7a3b08e-9d22-4faf-9224-36924d8ce7c8