Toward Efficient Land Cover Mapping: An Overview of the National Land Representation System and Land Cover Map 2015 of Bangladesh

• Main Authors: Rashed Jalal, Zaheer Iqbal, Matieu Henry, Gianluca Franceschini, Mohammad S. Islam, Mariam Akhter, Zarin T. Khan, Mohammad A. Hadi, Mohammed A. Hossain, M. Golam Mahboob, Tasnuva S. Udita, Tariq Aziz, Syed M. Masum, Liam Costello, Champa R. Saha, Abdullah A. M. Chowdhury, Abdus Salam, Farzana Shahrin, Fazle R. Sumon, Mahbubur Rahman, Mohammad A. Siddique, Mohammad M. Rahman, Md N. Jahan, Mir F. Shaunak, Mohammad S. Rahman, Mohammad R. Islam, Nicola Mosca, Remi D'Annunzio, Shrabanti Hira, Antonio Di Gregorio
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Subjects: Consistency; harmonization; interoperability; land cover ontology; standardization
• Online Access: https://ieeexplore.ieee.org/document/8901226/

In response to prevailing classification inconsistency between land cover maps, developed by different organizations in different times at different scales, an object-based National Land Representation System (NLRS) for Bangladesh has been developed. The process, which began in 2013 and was completed in 2016, brought together several national organizations and involved an extensive process of consultation, data collection, translation, and analysis of existing land cover/use classification systems. The process focused on the interpretation of three legends from historic national land cover/use maps. Field inventory data were collected from over 1000 sites across the country to assist the process of land characterization and the development of a dynamic and representative overview of land cover and land use in Bangladesh. The system has been applied to the development of a wall-to-wall national land cover map for the year 2015. In this article, the methodological process and results of NLRS formulation and land cover map 2015 are presented. We also provide examples of how this interoperable system and the land cover dataset are being used for variety of applications including national forest resources assessment, estimation of REDD+ activity data, integration of biophysical and socioeconomic information, and semantic similarity assessment.