The Value of Determining Global Land Cover for Assessing Climate Change Mitigation Options

2012 ◽  
pp. 193-230
Author(s):  
Steffen Fritz ◽  
Sabine Fuss ◽  
Petr Havlík ◽  
Jana Szolgayová ◽  
Ian McCallum ◽  
...  
Author(s):  
John Tzilivakis ◽  
Kathleen Lewis ◽  
Andrew Green ◽  
Douglas Warner

Purpose – In order to achieve reductions in greenhouse gas (GHG) emissions, it is essential that all industry sectors have the appropriate knowledge and tools to contribute. This includes agriculture, which is considered to contribute about a third of emissions globally. This paper reports on one such tool: IMPACCT: Integrated Management oPtions for Agricultural Climate Change miTigation. The paper aims to discuss these issues. Design/methodology/approach – IMPACCT focuses on GHGs, carbon sequestration and associated mitigation options. However, it also attempts to include information on economic and other environmental impacts in order to provide a more holistic perspective. The model identifies mitigation options, likely economic impacts and any synergies and trade-offs with other environmental objectives. The model has been applied on 22 case study farms in seven Member States. Findings – The tool presents some useful concepts for developing carbon calculators in the future. It has highlighted that calculators need to evolve from simply calculating emissions to identifying cost-effective and integrated emissions reduction options. Practical implications – IMPACCT has potential to become an effective means of provided targeted guidance, as part of a broader knowledge transfer programme based on an integrated suite of guidance, tools and advice delivered via different media. Originality/value – IMPACCT is a new model that demonstrates how to take a more integrated approach to mitigating GHGs on farms across Europe. It is a holistic carbon calculator that presents mitigation options in the context other environmental and economic objectives in the search for more sustainable methods of food production.


EuroChoices ◽  
2015 ◽  
Vol 14 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Silvia Coderoni ◽  
Laura Valli ◽  
Maurizio Canavari

2019 ◽  
Vol 11 (12) ◽  
pp. 1396 ◽  
Author(s):  
Li Liang ◽  
Qingsheng Liu ◽  
Gaohuan Liu ◽  
He Li ◽  
Chong Huang

Land cover is a fundamental component of crucial importance in the earth sciences. To date, many excellent international teams have created a variety of land cover products covering the entire globe. To provide a reference for researchers studying the Arctic, this paper evaluates four commonly used land cover products. First, we compare and analyze the four land cover products from the perspectives of land cover type, distribution and spatial heterogeneity. Second, we evaluate the accuracy of such products by using two sets of sample points collected from the Arctic region. Finally, we obtain the spatial consistency distribution of the products by means of superposition analysis. The results show the following: (a) among the four land cover products, Climate Change Initiative Land Cover (CCI-LC) has the highest overall accuracy (63.5%) in the Arctic region, GlobeLand30 has an overall accuracy of 62.2% and the overall accuracy of the Global Land Cover by the National Mapping Organization (GLCNMO) is only 48.8%. When applied in the Arctic region, the overall accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) is only 29.5% due to significant variances. Therefore, MODIS and GLCNMO are not recommended in Arctic-related research as their use may lead to major errors. (b) An evaluation of the consistency of the four products indicates that the classification of the large-scale homogeneous regions in the Arctic yields satisfactory results, whereas the classification results in the forest–tundra ecotone are unsatisfactory. The results serve as a reference for future research. (c) Among the four products, GlobeLand30 is the best choice for analyzing finely divided and unevenly distributed surface features such as waters, urban areas and cropland. Climate Change Initiative Land Cover (CCI-LC) has the highest overall accuracy, and its classification accuracy is relatively higher for forests, shrubs, sparse vegetation, snow/ice and water. GlobeLand30 and CCI-LC do not vary much from each other in terms of overall accuracy. They differ the most in the classification accuracy of shrub-covered land; CCI-LC performed better than GlobeLand30 in the classification of shrub-covered land, whereas the latter obtained higher accuracy than that of the former in the classification of urban areas and cropland.


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