Biodiversity Monitoring
- Measure biodiversity net gain impact (BNG)
- Evaluate and classify habitats to inform restoration strategies
- Generate baseline & post-dev hab survey report & map
- Assess and reduce operational environmental risks
- Comply with environmental regulations without a hustle
Inherent Drawbacks of
Direct Observations and On-Site Field Surveys
In the field of biodiversity monitoring, the reliance on direct observations and on-site field surveys has been a longstanding practice. However, these methods exhibit inherent drawbacks that can hinder the attainment of a comprehensive understanding of ecosystems.
One notable limitation is the manual nature of data collection. Researchers often gather data point by point, which is not only labor-intensive but also susceptible to errors and inconsistencies. Human observers may introduce subjectivity into the data collection process, leading to biased results and undermining the reliability and accuracy of the dataset.
Moreover, the scope of on-site surveys is inherently limited. It is often impractical to comprehensively cover large areas, leaving significant portions of ecosystems unmonitored and impeding our understanding of biodiversity patterns and trends. The resource-intensive nature of direct observations and field surveys presents challenges. These methods require substantial financial and human resources, which may not always be available, particularly in resource-constrained environments.
Furthermore, the analysis of data collected through direct observations and field surveys can be complex and time-consuming. Researchers must sift through large volumes of data manually, which increases the likelihood of human error and delays the generation of actionable insights.
Sometimes, poor data connectivity further complicates matters, especially in remote or inaccessible areas. Limited communication infrastructure can hinder the transmission and access of data, delaying analysis and decision-making processes.
Overall, while direct observations and on-site field surveys have been valuable tools in biodiversity monitoring, their limitations necessitate the exploration of innovative approaches to enhance data collection, analysis, and interpretation.
Say 'Hi' to Efficient and Scalable Biodiversity Data Collection, Analysis, and Reporting
Leveraging remotely sensed data and machine learning algorithms, Spottitt’s technology introduces a paradigm shift in how biodiversity is observed, classified and preserved:
✅ Comprehensive view of large and often inaccessible areas, providing a broader spatial perspective and more holistic understanding of biodiversity distribution
✅ Frequent and continuous updates on dynamic environmental changes and events, which is crucial for effective conservation efforts
✅ Early detection of habitat degradation and loss, invasive species encroachment, and other threats to ecosystems, which allows for proactive intervention before these threats become more severe
✅ Digital data consistency, which is in integration with ground-truthing activities, ensures a high level of accuracy and reliability in the information gathered
✅ Automated efficiency as AI enhances data processing and interpretation, offering advanced analytical capabilities and a robust foundation for decision-making
✅ Cost-efficiency as satellite-based remote sensing reduces the need for costly on-site surveys and manned missions, making biodiversity monitoring more economically viable and scalable, but also non-intrusive
Who Benefits From this Technology
► Developers of sites and infrastructure projects
► Land managers, owners and agents
► Local planning authority (LPA)
► Local environmental record centres
► Conservation Trusts and foundations
► Asset and O&M managers
► Sustainability and compliance officers
AI-Powered Geospatial Innovation for Monitoring, Classifying and Protecting Ecosystem Diversity
Spottitt Metrics Factory allows to monitor the following indicators, accurately, remotely and at scale:
► Coniferous trees ► Broadleaf Trees ► Cropland ► Heat & Scrub ► Modified Grassland ► Other Grassland
► Rivers and Lakes ► Urban Area ► Urban Buildings ► Agricultural Area ► Sparsely Vegetated
Download the brochure to learn more
More and more Companies
are Expected to Monitor Biodiversity
Despite the believe that only environmental organizations request biodiversity monitoring services, more and more power and gas TSOs and DSOs, road and rail transport operators, and renewable energy companies express their interest in these types of services. This is because their operations span large areas and could potentially affect ecosystems..
Here are a few reasons why these organizations are committed to monitoring biodiversity in their operational areas:
Compliance and Regulatory Requirements: They need to comply with environmental regulations and permits, which often require monitoring, assessment and mitigating their impact on biodiversity.
Risk Management: Monitoring biodiversity helps identify and mitigate risks associated with their operations, such as habitat destruction, fragmentation, or pollution, which could lead to legal, financial, or reputational consequences.
Stakeholder Expectations: Stakeholders, including local communities, environmental groups, and investors, increasingly expect these organizations to demonstrate responsible environmental stewardship, including biodiversity conservation.
Resource Management: Biodiversity monitoring can inform resource management decisions, such as land use planning, vegetation management, and infrastructure development, to minimize negative impacts on ecosystems and species.
Climate Change Adaptation: Biodiversity monitoring may be part of broader efforts to adapt to climate change, as changes in biodiversity can indicate shifts in ecosystem health and resilience.
Powered by Spottitt Metrics Factory
AI-Based One Stop Geospatial Analytics for Decision Makers
Data Acquisition
Supporting different commercial and open source geospatial data
AI-Powered Data Analysis
To identify and extract all the relevant analytics from patterns, land features and objects
Customised Reporting
Enabling multiple user views, easy extraction and integration to GIS and other software
Relevant Blog Articles
Behind the Spottitt MF Curtains: Role of Machine Learning in Analyzing Satellite Imagery
Spottitt is known for utilising satellite data to offer infrastructure owners valuable insights into the diverse external risks affecting their assets. But how precisely do we derive these insights from satellite imagery? The answer is – machine learning, and today we’re inviting you behind the curtains of our product to unveil the whole process.
Spottitt Metrics Factory Advances to the Next Level
As more organizations turned to Spottitt for monitoring growing numbers of assets, we recognized that the traditional geospatial platform’s map view, which was effective for small-scale monitoring, became cumbersome when dealing with larger datasets. So, we embarked on the development of Spottitt Metrics Factory. Since its beta launch in late 2022, ten organizations from around the world have been delighting in the ability to view and interact with their asset monitoring data using the product.
Top Tips for Choosing the Right Satellite Analytics Provider for Your Needs
Satellite-derived analytics is rapidly gaining ground as an essential tool for monitoring and managing risks in the power, utility, and infrastructure industries. It has been recognised as a key tool to improve safety, reliability, and optimal performance of critical assets by providing insights into their health, risks, and other key operational parameters.
