In this article, Shashin Mishra, VP of EMEA, AiDash, explores how AI technology can bridge skills gaps, improve mapping accuracy, and enable ecologists to focus on high-value tasks, ultimately supporting the successful implementation of BNG
The mandating of Biodiversity Net Gain (BNG) was welcomed across the UK in hopes of boosting the country’s severely depleted nature and wildlife.
BNG must be successfully implemented from the start to reverse decades of ecological damage while unlocking and enabling sustainable development.
The mandatory 10% for new developments is a critical step to nature recovery, and it is crucial that we get it right.
Concerns have been raised about feasibility. Complying with the new legislation is a massive undertaking.
Viability, resourcing and costs have left the industry on the back foot
Issues such as viability, resourcing, costs, efficiency, accuracy, and credibility have left the industry on the back foot, jeopardising the feasibility of a fully functioning system.
UK developers are confronted with the daunting and costly tasks of acquiring appropriate and timely expertise and support against a backdrop of chronic skills shortage.
Ecologists, developers, planners, architects, and local authorities are all feeling the pressure to deliver BNG at the required scale and speed.
Only by adopting practical, modern solutions can this be done. Innovative technologies such as artificial intelligence (AI) and satellites are essential to resolve the issues of speed, scale, and resourcing threatening the success of BNG.
The issue: skill shortage
There is a concerning shortage of qualified ecologists available to undertake the volume of necessary work.
With around 150,000 BNG projects expected to be submitted annually, AiDash estimates that the UK would need an additional 40% more ecologists, equivalent to 4,000 to 6,000 professionals, to meet this demand.
This shortage was highlighted in DEFRA’s study, commissioned to assess the resources required to carry out BNG.
Out of the 337 individuals across 192 planning authorities (LPAs) surveyed, a mere 5% of respondents indicated that their current ecological resources were adequate to thoroughly evaluate all applications that might affect biodiversity.
Over 90% expressed a lack of capacity, with minimal or non-existent resources, to adequately deliver BNG.
A shortfall in resources and expertise for assessing BNG could lead to failures to comply with the new legislation or the creation of BNG plans that do not deliver the requirements in practice.
BNG requires the mapping of habitats with high positional accuracy, often relying on ground-based ecological surveys. However, this process is not only time-consuming and costly but also frequently impractical.
For instance, certain habitats are inaccessible on foot, while others are too vast to be accurately mapped using traditional methods.
The expansive nature of certain habitats can make it difficult to estimate coverage accurately during field assessments, and without the appropriate capabilities, the boundaries may be mapped incorrectly.
Additionally, data misalignment can occur in large scale projects tackled by ecologists who are constrained by time and resources. Errors in the early stage of the biodiversity baselining can compound the error in final measurements, compromising the quality of surveys at an early stage.
How AI and tech can help
AI can bridge this skills shortage, transforming weeks of work into days and enabling ecologists to significantly increase the quantity and quality of their output.
As a valuable time-saving tool, AI can alleviate the administrative burdens faced by ecologists, allowing them to focus on the high value tasks and decision making that only skilled ecologists can perform.
AI and satellite imagery can update maps more frequently, adapt to changing habitats, and access remote or inaccessible areas.
Moreover, AI offers efficient methods for mapping habitats at scale, delivering precise, real-time insights that can track changes in biodiversity and inform adaptive management strategies.
Over the last 20 years, England has on average built around 187,000 new homes each year. With the government aiming to increase this to 300,000 homes per year, and thousands more commercial developments underway, supporting ecologists to manage their workloads and spend time on the most critical tasks, can accelerate project timelines and ensure that delivering 10% BNG is possible for every project.
The issue: inadequate volume and quality of data
BNG is a complex process that necessitates the gathering of specific data. Habitat mapping forms the baseline data, and any inaccuracies at this stage risk compromising net gain calculations from the outset.
Complying with the new rules is a huge undertaking, and with limited resources, the importance of ensuring the accuracy of surveys may be overlooked.
While free tools are available to build these maps, they lack the necessary detail and alignment with DEFRA’s definitions for BNG.
Even minor discrepancies can potentially lead to development projects proceeding without adequate consideration of their impact on habitats and species and resulting in the implementation of biodiversity strategies that later fail to meet the required net gain.
Traditional approaches to habitat mapping involve decisions made individually by ecologists at the site and, due to subjectivity, often yield varying results despite surveying the same location simultaneously.
Enhancing ecological mapping with technology: AI and satellite solutions
While on-the-ground mapping remains essential for ecologists, technology can save valuable time by swiftly processing vast amounts of data and monitoring change at scale.
This ensures there are no gaps, accounting for every square meter. AI’s standardised method precisely defines habitat boundaries to remove inherent biases and varied interpretations.
Additionally, satellite imagery offers a solution to significantly enhance accuracy, boasting a resolution 460 times higher than free maps.
Not only can it produce highly accurate preliminary maps that can be used to assess prospect locations early on, but satellite data can also keep track of dynamic and rapidly changing habitats—areas where traditional mapping may fall short in capturing such fluctuations.
Habitat maps operate as the backbone for a BNG project, yet the complexity of habitats often poses challenges in classification.
By utilising AI and satellite technology, it is possible to establish a single point of truth, facilitating the development of an impactful biodiversity plan.
AI serves as a tool, working hand in hand with ecologists to complement and enhance vital work.
By integrating AI and satellite technology to create habitat maps, it becomes possible to assess large areas quickly and efficiently, addressing skill shortages, and ensuring accurate data, all while aligning with the new BNG framework.
