777ӰԺ is a global academic hub for the Sustainable Development Goals, which form a key cross-cutting theme of its The Empowerment University strategic plan.
Our 2024 report on all 17 SDGs will show what work the university has been doing through research and engagement in helping to meet those targets and raising awareness of the progress towards the 2030 aims.
Our reports start with the United Nations’ verdict on progress from their 2024 report on SDG 15 Life on Land.
UN PROGRESS REPORT ON SDG 15
A total of 40% of the targets for this SDG are either stagnating or actually regressing on the aims set back in 2015 (20% regressions, 20% stagnation). There has been minimal progress on 40% of the targets and 20% are on track to achieve the goals set for 2030.
The UN 2024 report states: ‘Global trends underscore persistent challenges to biodiversity and forests, despite their critical roles as planetary life-support systems. Global forest area continues to decline, primarily due to agricultural expansion, despite notable progress in sustainable forest management.
“Alarmingly, species are silently becoming extinct, the protection of key biodiversity areas has stalled and global illicit wildlife trafficking has steadily increased, posing serious threats to biodiversity and the benefits it provides to people. Efforts are under way to tackle these challenges. Urgent action is imperative. Addressing pressing environmental challenges and their underlying drivers and interconnections… demands intensified, accelerated efforts, and a comprehensive and integrated approach at local, national and global levels”.
DMU NEWS ON SDG 15 in 2024
Innovative design to help UK bee population puts DMU student in finals of national design competition
THIS year, students were invited to design independently powered products made primarily of plastics, capable of being used off-grid and targeted at either the domestic or sports and leisure markets.
Joe’s design is a smart beehive which can monitor and provide information about the bees’ wellbeing. The device checks on the beehive environment – including temperature and humidity – as this can affect the level of productivity.
The more productive the bees are, the more pollination takes place and the more plants reproduce.
The exact details of how the product works are to remain secret at the moment due to possible patents.
DMU students join forces to tackle litter in and around the city's waterways
STUDENTS from 777ӰԺ (DMU) have helped fill 35 bags worth of rubbish from around a local river to help clean up the city’s waterways.
A group of volunteers from the university helped clear piles of waste from the banks of the River Soar, including shopping trolleys, a bike, a grandfather clock and car keys.
More than 20 students joined forces with Leicester City Council and the Canal and River Trust for the annual litter pick, timed to coincide with the COP29 climate talks in Baku, Azerbaijan.
DMU RESEARCH ON SDG 15 in 2024
Forest Fire Detection Utilizing Ghost Swin Transformer with Attention and Auxiliary Geometric Loss
(Francois Siewe et al)
Forest fires are a devastating natural disaster. Existing fire detection models face limitations in dataset availability, multi-scale feature extraction, and locating obscured or small flames and smoke. To address these issues, we develop a dataset containing real and synthetic forest fire images, sourced from a UAV (Unmanned Aerial Vehicle) perspective. Additionally, we propose the Ghost Convolution Swin Transformer (GCST) module to extract multi-scale flame and smoke features from different receptive fields by integrating parallel Ghost convolution and Swin Transformer.
Extensive experimental results demonstrate that our method provides a significant improvement in accuracy and real-time performance compared to state-of-the-art techniques.
Adapting genetic algorithms for multifunctional landscape decisions: a theoretical case study on wild bees and farmers in the UK
(Ellen Knight, Shengxiang Yang et al)
Spatial modelling approaches to aid land-use decisions which benefit both wildlife and humans are often limited to the comparison of pre-determined landscape scenarios, which may not reflect the true optimum landscape for any end-user. Furthermore, the needs of wildlife are often under-represented when considered alongside human financial interests in these approaches.
Our investigation suggests that optimisation set-up (decision-unit scales, traditional choice of a single biodiversity metric) can bias outcomes towards human-centric solutions. It also demonstrates the importance of representing the individual requirements of different actors with different landscape-level needs when using genetic algorithms to support biodiversity-inclusive decision-making in multi-functional landscapes.
Read the full Sustainable Development Goals 2024 report on all the SDGs here
SDSG 15 Life on Land