What is the importance of spatial data?
Spatial data, or geospatial data, tells us important information about the earth and what is contains. Spatial data is intrinsically linked to a specific location. Through spatial analysis, this data allows you to understand the characteristics and qualities of different places. It helps you solve geographic problems and gain insight about the world.
What is habitat mapping?
Habitat mapping uses the information from spatial data to map the different habitats and biodiversity types on earth. It not only detects, but classifies the characteristics of defined regions. These classifications include everything from habitat boundaries to types of plants and the sensitivity of the wildlife.
Why is habitat mapping important?
Habitat mapping has some significant implications for how we run our businesses, our governments and our global behaviours.
First and foremost, habitat mapping helps us understand the natural capital we have available. It provides a detailed picture of our landscapes and what they contain. It can also help detect changes that are happening to that capital both because of our interactions with the environment and those that occur naturally.
This data can be used to generate actionable intelligence for a variety of decision-makers. It also supports additional analysis such as change detection and environmental impact assessments. These methods can ultimately be used to inform sustainable and responsible development. For example, data collected from habitat mapping can be directly related to the UN’s Sustainable Development Goals (SDGs), specifically sustainable cities and communities (11), climate action (13), life below water (14) and life on land (15).
Now, habitat mapping is becoming even more important to the future of commercial and political models. As the technology advances and digitisation increases, habitat knowledge is becoming more accessible to organisations. With this support, global entities have the ability to make environmentally conscious and sustainable decisions.
How was habitat mapping previously performed?
Mapping the earth is an age-old activity. It began as a purely analogue process, putting pen to paper based on what’s in front of your eyes. Over time physical field studies were performed to build up maps and analysis of what we could access.
Aerial imagery was the next stage of development. People could use planes to actively fly over land and water taking images and mapping on sight. This allowed access to more areas than before and getting a new perspective on the land. However, this process requires a lot of man hours, is expensive to carry out and still doesn’t unlock global access.
What kinds of technology exists that can be used for habitat mapping?
The technology surrounding the habitat mapping sphere has accelerated from the days of physical mapping. While ground truthing and physical surveys are still used, they aren’t always appropriate, or possible to carry out. There are instances throughout the globe where inhospitable regions, dangerous landscapes or political tensions prevent physical data collection. Plus, using these methods alone would be extremely inefficient.
That’s why multiple technologies and data fusion techniques have advanced in response to this challenge and can be used in habitat mapping:
Satellite imagery and remote sensing: Satellites can be used to capture high quality images from space – with no physical, earthly interaction. Resolutions currently reach around 0.5m which provides extremely good detail and accuracy. This is likely to expand to 0.3m, or even 0.1m, in the near future.
SAR: Synthetic-Aperture Radar is a remote sensing technique that generates images using radar satellites. This approach to habitat imaging has specific benefits. These include the ability to see through cloud cover day or night, display greater habitat boundary clarity, and can identify canopy structure.
Machine Learning (ML) and automation: ML models can segment broader habitats into more specific classes, like vegetation, water and so on. This allows users to see more detailed classifications. ML models could also be used to inform data fusion for further classification.
The benefits of using remote sensing technology for habitat mapping data collection:
- Remote sensing is non-invasive and environmentally sustainable
- Resource requirements, including equipment and man-power, are reduced
- Mapping and data collection can be performed much quicker
- More areas and larger scale areas can be mapped easily
- Remote locations can be accessed
- Satellite imagery can be captured over geographical and political boundaries
- Using remote techniques are less dangerous, as the health and safety element of putting people in the field is removed
- Imagery maintains the accuracy and detail necessary to achieve insights
- The resolution of imagery is constantly increasing
- Software improvements increase the accuracy of georeferencing image data
- Multiple spectral bands can be leveraged to see different information and create a more comprehensive picture
Will analogue data collection processes become obsolete?
One key challenge of habitat mapping is that boundaries can be subjective. The natural earth doesn’t have defined lines – and quantitative data often isn’t enough to make a definition. So analogue ground truthing will always be needed to solve this problem.
Ground truthing involves collecting information about local people’s perspectives, governance and cultural priorities into the work of habitat mapping. It uses the knowledge of local ecological experts who understand the area to validate and add to the data captured from satellite imagery.
This is extremely valuable as technology can make mistakes, or not understand the nuances of qualitative facts. Ground truthing therefore validates and adds intelligence to the work of technology and of science. In this sense, human involvement will never be obsolete because it creates a more comprehensive picture of a given region.
How will habitat mapping advance in the next 5 years?
The technology used in Habitat mapping will continue to advance over the next few years. Machine learning will become more sophisticated and data quality will improve. This will exponentially speed up the data collection and habitat mapping process, making it easier to repeat, quickly detect and changes within the environment and to monitor conservation and protection efforts.
As satellite technology also continues to advance and develop, imagery will become more detailed and accuracy levels will increase, which will mean even more information will be able to be held within habitat maps.