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

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.

[1]  K. Wallace Classification of ecosystem services: Problems and solutions , 2007 .

[2]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .

[3]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[4]  Dirk Tiede,et al.  Semantic and syntactic interoperability in online processing of big Earth observation data , 2017, Int. J. Digit. Earth.

[5]  Arno Schäpe,et al.  Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .

[6]  Peter F. Fisher,et al.  Integrating land-cover data with different ontologies: identifying change from inconsistency , 2004, Int. J. Geogr. Inf. Sci..

[7]  Kabir Uddin,et al.  Development of 2010 national land cover database for the Nepal. , 2015, Journal of environmental management.

[8]  G. Foody Assessing the accuracy of land cover change with imperfect ground reference data , 2010 .

[9]  Matthew C. Hansen,et al.  Comprehensive monitoring of Bangladesh tree cover inside and outside of forests, 2000–2014 , 2017 .

[10]  C. Woodcock,et al.  Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation , 2013 .

[11]  Geoffrey J. Hay,et al.  Image objects and geographic objects , 2008 .

[12]  Martin Herold,et al.  A joint initiative for harmonization and validation of land cover datasets , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[13]  S. Goetz,et al.  Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps , 2012 .

[14]  Chen-Chieh Feng,et al.  Assessment of semantic similarity between land use/land cover classification systems , 2004, Comput. Environ. Urban Syst..

[15]  Jun Chen,et al.  The Standardization and Harmonization of Land Cover Classification Systems towards Harmonized Datasets: A Review , 2017, ISPRS Int. J. Geo Inf..

[16]  G. Powell,et al.  High-resolution forest carbon stocks and emissions in the Amazon , 2010, Proceedings of the National Academy of Sciences.

[17]  F. Achard,et al.  Determination of tropical deforestation rates and related carbon losses from 1990 to 2010 , 2014, Global change biology.

[18]  S. Goetz,et al.  Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps , 2013, Carbon Balance and Management.

[19]  W. Salas,et al.  Benchmark map of forest carbon stocks in tropical regions across three continents , 2011, Proceedings of the National Academy of Sciences.

[20]  R. D. Groot,et al.  A typology for the classification, description and valuation of ecosystem functions, goods and services , 2002 .