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Consistent cross-border land cover assessments prove vital for natural resource management

Last month’s workshop on Regional Land Cover Monitoring in Bangkok saw a strong coordinated effort among participating countries from the Hindu Kush-Himalayan region, to use the same land cover classification systems and produce regionally standardized land cover maps. These are essential for both land cover monitoring and natural resource management.

“Regionally consistent land cover classes and maps are the core for our understanding of human-environmental interactions and impacts on natural resources.” said Kristofer Johnson, who works with FAO Bangladesh on national scale forest monitoring.

He went on to explain how without systems that consistently define land cover across borders, “…countries will always struggle to compare and benefit from their neighbours in determining the most effective natural resource management strategies.”

The workshop that took place from the 2-3 April was organized by the International Centre for Integrated Mountain Development (ICIMOD), Geospatial Technology and Applications Center (GTAC), United States Forest Service (USFS), Asian Disaster Preparedness Center (ADPC) and SilvaCarbon.

It was a forum for discussion and consultation, bringing together national institutes from Afghanistan, Bangladesh, Myanmar and Nepal and regional and international agencies experienced in Land cover and Land use mapping.

The different countries compared their experiences in using FAO’s latest Land Cover Classification System 3 (LCCS3), Collect earth, SEPAL and working with remote sensing data. All the participants were keen to benefit and assist others in producing more effective maps to better manage natural resources.

All agreed that LCCS3 was the most effective tool to consistently classify land cover across the Hindu Kush-Himalayan region. 

Representatives from Bangladesh presented their approaches to monitoring land cover and forestry resources. Henry Matieu, a Chief Technical Advisor from FAO described how an integrated approach like one in Bangladesh, using remote sensing and ground truthing, free and open source software and the FAO LCCS3, could be further developed to benefit other stakeholders in the region.

It is fundamental that national institutes particularly from neighbouring countries continue to come together as they did during this workshop. Sharing evidence and best practices can lead to a consensus in land cover classification. Standardization and harmonization of land cover classification enables the combination of existing land cover datasets to support global land cover data analysis. This in turn promotes the sustainable management of natural resources, environmental protection, and food security.

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