Globally, 18% of the annual worldwide GHG emissions are attributable to livestock production (FAO, 2006). Estimation of GHGs is pivotal in the efforts to reduce GHGs from the livestock sector to continue supporting economic services in a sustainable way (Kipling et al., 2016). Recent advancements in using Remote Sensing and Machine learning to automate data collection processes promise to achieve reliable results for GHG emissions estimation. These methods, however, haven’t been sufficiently applied in Africa. None the less, application of Artificial Intelligence (AI) is known to increase adaptation and mitigation capacity, in turn, improving the precision of evidence-based decision making. The proposed study products will inform where greater efforts can be supported for reduced climate change impact. The products will contribute to reliable national commitments to international GHG emissions reporting.
The research products will contribute to realizing African Union development aspirations enshrined in the Agenda 2063, which aspires for a Prosperous Africa based on inclusive Growth and Sustainable Development through “environmentally sustainable and climate resilient economies and communities”. The project aligns excellently with the National Development Plan III that recognizes the risks due to climate change as emerging issues that need to be mitigated to increase chances of success of the Plan. The research contributes to realization of SDG 13 by developing technologies that strengthen residence and adaptive capacity. The research products will improve management of the impacts of climate extremes. This will directly and positively impact the Climate Change Department (CCD) to support their accounting on the Paris Agreement.