There’s a way to accurately identify, map and classify different types of land coverage through the use of satellite imagery. An advanced technology that allows you to monitor and manage natural resources with ease. A solution that helps you make informed decisions to make the most of land use and development.
We are talking about Land Classification, our platform’s algorithm used to assign a category or designation to a land, or a land area, based on its physical, biological, economic and social characteristics.
This technology, called “LULC” (Land Use Land Cover), is used for a number of purposes, including:
- territorial planning and management of natural resources;
- biodiversity conservation;
- real estate assessment.
Through this algorithm you can accurately identify urban areas, forests, agricultural lands and waterbodies in order to plan and develop urban development projects.
LULC: the algorithm that makes Land Classification possible
As explained above, the algorithm that allows Land Classification is called “Land Use Land Cover”. It consists of two separate activities, Land Use and Land Cover, which coexist within the LULC algorithm, allowing:
- the categorization and classification of human activities and natural elements of the land;
- the use of a scientific and statistical method to better understand the aspects of land use;
- the planning of development programs and the safeguarding of the land.
With the term Land Use we refer to the actual destination that is given to a certain area of land, to carry out a specific human activity. In particular, Land Use refers to the context and socio-economic purpose for which a land is used, for example, land uses in the field:
Our algorithm takes into account multiple factors including the availability of natural resources, laws, regulations, the proximity of a certain area to services and infrastructures, and market demand.
Land Cover, on the other hand, refers to land coverage and, therefore, to natural and non-physically present and visible elements that cover the earth’s surface, such as vegetation, built areas and water masses.
The analysis of land cover maps allows you to obtain fundamental information to understand:
- the extent, availability and conditions of a specific area;
- how a particular area has changed over time and the impact of natural phenomena on it;
- Chemicals and pollutants’ diffusion and effects in certain areas.
Unlike Land Use, Land Cover does not describe how the land is used by humans, but indicates the physical and material characteristics of the land’s surface.
Both activities are critical to obtain extremely useful data for the implementation of urban development projects.
Making Actionable Data a Reality
What urban development projects can you achieve with Land Classification?
Do you want to identify areas where it is best to build green infrastructures or identify the areas most exposed to the effects of urban heat islands?
Urban planning projects are the base of smart cities All goes through their development: it’s the only way to imagine a sustainable, modern and enjoyable city to live in.
In addition to identification, our platform – thanks to the integration of this algorithm – focuses on monitoring and managing natural resources. After accurately identifying and mapping the different types of land cover, it can monitor the changes that occur over time in land use, such as areas where deforestation or land conversion has occurred, in order to promptly intervene to protect and preserve the valuable resources that nature provides us with.
LULC can also be used:
- in agriculture, to identify arable lands and to scientifically monitor crop health with extreme care and accuracy;
- in environmental monitoring, to identify and monitor wetlands, coastal areas, and ecologically sensitive places.
By choosing Latitudo 40 you know you can rely on a layer, that of Land Classification, which is versatile, powerful and extremely intelligent, designed to offer you support in decision making and in choosing sustainable solutions to safeguard the environment.