Browsing by Author "Ameray, Abderrahmane"
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- Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approachesPublication . Ameray, Abderrahmane; Castro, Marina; Bouhaloua, M.; Castro, João PauloReducing 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.
- Carbon mapping in Portugal forest and agroforestry systems using direct remote sensing and combine assign approachesPublication . Ameray, Abderrahmane; Castro, Marina; Bouhaloua, M.; Castro, João PauloReducing 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.
- Climate change mitigation: annual carbon balance accounting and mapping in the national forest ecosystems (continental Portugal)Publication . Ameray, Abderrahmane; Castro, João Paulo; Bouhaloua, MhammedWe present in this article the carbon balance accounting and mapping in the Portugal continental forests (Mediterranean forest), which occupies 36% of the national territory, mostly private (93%). These forests are characterized by their economic, social and environmental importance values, but during these last years, they are undergoing natural and anthropogenic disturbances and also a strong wood demand for supplying the industry sector. The first goal of this study was to quantify the different components of the carbon (C) cycle, gain and losses, using atmospheric flow approach (gain-loss approach) developed by Intergovernmental Panel on Climate Change (IPCC). The carbon gain reflects the yearly photosynthetic sequestration. The carbon losses reflect the different yearly disturbances like fires, forest logging, pests and diseases attacks. This method allows us to assess the carbon balance evolution from 1995 until 2014 and to identify the most important species in climate change mitigation regarding the air purification or the greenhouse gases emissions contribution. Our second purpose is mapping the carbon-density areas with two different approaches, firstly the direct Remote Sensing (DRS) approach using MODIS images, secondly the indirect approach named Combine and Assign (CA) Approach. MODIS images allow the accounting of Net Primary Productivity (NPP) which presents the quantity of carbon absorbed by vegetation cover during a period of time 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 IPCC. Our third objective is to link the NPP in 2017 derived from MOD17A3 (MODIS product) with abiotic factors (precipitation, temperature, elevation), to find the best conditions for carbon sequestration. Several geostatistical technics were tested to interpolate climatic factors for all the country. Towards the end, mitigation measures will be proposed.
- A new approach to quantify grazing pressure under Mediterranean pastoral systems using GIS and remote sensingPublication . Castro, Marina; Ameray, Abderrahmane; Castro, João PauloPastoral systems based on grazing itineraries, very common along the Mediterranean region, provides an opportunity to search feeding resources at landscape scale under a silvopastoral system called by San Miguel (2004) as “Mosaic of different land uses within one management unit”. However daily and seasonal movements of flocks bring on different Grazing Pressure (GP) over the landscape. This study presents an approach to modeling sheep GP under a Mediterranean pastoral system in Northeast of Portugal. The pressure of grazing in a given location depends on Distance from the stable to the border of the parish, Distance to the stable, Stocking Density (SD) (sheep/ha) and preferences for land use and land cover (LULC) (Castro et al., 2004). Geoprocessing integrates several geodatabases, a) land use (COS2015), b) parishes boundaries (DGT, 2017), c) stables location (0108_OTSA_2_E), and d) Sentinel-2 data. SD was performed by Multiple Ring Buffer tool and Ordinary kriging. Homogeneous LULC units (Permanent Crops; Annual crops; Forest; Shrubland; Grassland; Waterland) were obtained by Supervised classification algorithms. The COS2015 was used to establish a mask of the urban area and ungrazed forests. The best performing preferences classifier was Randon Forest (kappa=89,3%; global accuracy=91%). Integrating the LULC grazing and the SD (Weighted Overlay tool) allows to calculate and to map the GP (figure 1). The most common GP in grazing classes is about 4.7 sheep/ha.
- A new approach to quantify grazing pressure under mediterranean pastoral systems using GIS and remote sensingPublication . Castro, Marina; Ameray, Abderrahmane; Castro, João PauloPastoral systems based on grazing itineraries are very common along the Mediterranean region and provide an opportunity to manage the fuel load and reduce fire risk in the ecosystem. Daily and seasonal movements of flocks bring on different grazing pressure (GP) (sheep ha−1) over the landscape. This study presents an approach to model sheep GP under a Mediterranean pastoral system in the Northeast of Portugal. The GP in a given location depends on the distance from the stable to the parish border, the distance to the stable, the heads of livestock and their preference for land use and cover (LUC). The geoprocessing we applied in this study integrated several spatial databases: the latest official Portuguese vector mapping of land use and cover (COS2015) and administrative boundaries (CAOP2018), the livestock stables location, and Sentinel-2 Multispectral Images. During the geoprocessing, the stocking density (SD) (sheep ha−1) were calculated and spatially interpolated. Homogeneous LUC units (permanent crops; annual crops; forest; shrubland; grassland; water bodies) were obtained by Random Forest supervised classification algorithm (kappa = 89.3%; global accuracy = 91.2%). Boolean overlapping of the LUC classes obtained by the supervised classifier with the mask created from COS2015 provides the potentially grazed LUC classes. Integrating LUC preferences with SD allows calculating and mapping the GP. The most common GP class is 0–0.25 sheep ha−1. Seeing the GP per LUC class, a value of 1.84 sheep ha−1 was found in permanent crops, 1.73 in annual crops, and 1.25 in grassland, 0.88 in grazed forests and 0.84 in shrublands. The GP modelling and mapping could assist in the implementation of herding programmes aimed at reducing fire hazards at a parish or at a regional scale.
- A new approach to quantify grazing pressure under Mediterranean pastoral systems using GIS and remote sensingPublication . Castro, Marina; Ameray, Abderrahmane; Castro, João PauloPastoral systems based on grazing itineraries, very common along the Mediterranean region, provides an opportunity to search feeding resources at landscape scale under a silvopastoral system called by San Miguel (2004) as “Mosaic of different land uses within one management unit”. However daily and seasonal movements of flocks bring on different Grazing Pressure (GP) over the landscape. The GP in a given location depends on the distance from the stable to the parish border, the distance to the stable, the heads of livestock and their preferences for land use and land cover (LULC).
- Potential greenhouse gas emissions mitigation through increased grazing pressure: a case study in North PortugalPublication . Ameray, Abderrahmane; Castro, João Paulo; Castro, MarinaWildfires have been an important process affecting forests and rangelands worldwide. In the Mediterranean region, wildfires burn about half a million hectares of forest and scrubland every year. Fuel loads are the main factor controlling fire risk and its propagation. The reduction of fuel loads by grazing could help to decrease the spread and intensity of wildfires in this region. This study aims to assess the contribution of sheep grazing on fuel load management and their role to the mitigation of wildfire greenhouse gas (GHG) emissions. The methodological approach is based on a simulation of the grazing pressure required to reduce a given quantity of fuel, under the assumption that if it is not consumed, it becomes fuel. Following, a simulation model was designed to estimate the total GHG emissions prevented through grazing, by reducing the risk of fire. These emissions were estimated based on the Intergovernmental Panel on Climate Change (IPCC) framework. The accumulated fuels were estimated to be 3126.65 kg dry matter (DM) ha-1 and the biomass potentially consumed by sheep was 1416.03 kg DM ha-1 yr-1, corresponding to 45.29% of accumulated fuel loads. Our findings suggest a value of 3.88 sheep ha-1 day-1 as the ideal to reduce 4833.63 kg CO2eq ha-1 yr-1 of emissions, distributed between CO2 (-2221.76 kg CO2eq ha-1 yr-1; 45.96%), NOx (-1873.41 kg CO2eq ha-1 yr-1; 38.76%), CO (-454.55 kg CO2eq ha-1 yr-1; 9.40%), CH4 (-186.35 kg CO2eq ha-1 yr-1; 3.86%) and N2O (-97.56 kg CO2eq ha-1 yr-1; 2%). The results of this study also underline that livestock can help to mitigate climate change in areas prone to wildfires.