مجموعة أدوات الغطاء الأرضي
Land cover mapping is a complex and multistage data processing and analysis system. It requires a set of tools from defining legend to assess the accuracy.
FAO has a set of software tools for supporting :
- legend generation
- data processing
- interpretation
- statistical analyses

The software package includes:
Tools for land cover and land use legend generation
LCHS is an online latest tool, developed in 2023, that enables the guided classification of land cover features enforcing the updated Land Cover Meta-Language (LCML) standard in 2023 i.e., ISO 19144-2:2023. This tool contains all the functionality of the Land Cover Classification System version 3 (LCCSv3) with the addition of online functionality such as the integration of the FAO Land Cover Legend Registry (LCLR).
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A user-friendly tool, developed in 2010, with a graphical user interface that allows the classification of the land cover features in a comprehensive system, applying the LCML standard i.e., ISO 19144-2:2012. This enables the comparison and correlation of land cover classes regardless of mapping scale, land cover type, data collection method or geographical location.

Elements of a mangrove land cover are described using the LCML componen
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The legend is prepared using the LCHS Software
System for Earth Observation, Data Access, Processing & Analysis for Land Monitoring (SEPAL)
The System for Earth Observation, Data Access, Processing & Analysis for Land Monitoring (SEPAL) is a cloud computing–based platform for autonomous land monitoring using remotely sensed data. It is a combination of many open–source geospatial tools and libraries that are needed for land monitoring including modern geospatial data infrastructures like Google Earth Engine. It allows users to access and process satellite data quickly and efficiently for sophisticated data processing and analyses.
Collect Earth Online (CEO)
Collect Earth Online (CEO) is the next generation of web–based, crowd–sourced technology for earth science analyses. It allows users to collect reference data for land cover mapping using simultaneous visual interpretations of various sources of satellite images and big-data analysis through Google Earth Engine. Multiple users can simultaneously collect reference information with feature to perform quality control of the collected reference data.

