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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Environ. Sci. | doi: 10.3389/fenvs.2019.00150

Land cover mapping in data scarce environments: challenges and opportunities

  • 1University of San Francisco, United States
  • 2Independent researcher, United States
  • 3International Centre for Integrated Mountain Development, Nepal
  • 4Asian Disaster Preparedness Center (ADPC), Thailand
  • 5Independent researcher, United States
  • 6University of Alabama in Huntsville, United States
  • 7University of Maryland, College Park, United States
  • 8University of Maryland, Baltimore, United States
  • 9The Center for People and Forests (RECOFTC), Thailand
  • 10Google (United States), United States

Land cover maps are a critical component to make informed policy, development, planning,
and resource management decisions. However, technical, capacity, and institutional challenges inhibit the creation of consistent and relevant land cover maps for use in developing regions. Many developing regions lack coordinated capacity, infrastructure, and technologies to produce a robust land cover monitoring system that meets land management needs. Local capacity may be replaced by external consultants or methods which lack long-term sustainability. In this study, we characterize 9 and respond to the key land cover mapping gaps and challenges encountered in the Lower Mekong (LMR) and Hindu Kush-Himalaya (HKH) region through a needs assessment exercise and a collaborative system design. Needs were assessed using multiple approaches, including focus groups, user engagement workshops, and online surveys. Efforts to understand existing limitations and stakeholder needs resulted in a co-developed and modular land cover monitoring system which utilizes state-of-the-art cloud computing and machine learning which leverages freely available Earth observations. This approach meets the needs of diverse actors and is a model for transnational cooperation.

Keywords: Land cover - land use (LCLU), GIS - Geographic Information System, remote sensing, Lower Mekong Region, Hindu Kush region

Received: 02 Jun 2019; Accepted: 17 Sep 2019.

Copyright: © 2019 Saah, Tenneson, Matin, Uddin, Cutter, Poortinga, Ngyuen, Patterson, Johnson, Markert, Flores, Anderson, Weigel, Ellenburg, Bhagarva, Aekakkararungroj, Bhandari, Khanal, Housman, Potapov, Tyukavina, Maus, Ganz, Clinton and Chishtie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Farrukh Chishtie, Asian Disaster Preparedness Center (ADPC), Bangkok, 10400, Bangkok, Thailand, farrukh.chishtie@adpc.net