remote sensing Article Mapping the Natural Distribution of Bamboo and Related Carbon Stocks in the Tropics Using Google Earth Engine, Phenological Behavior, Landsat 8, and Sentinel-2 Manjunatha Venkatappa 1,2,3,* , Sutee Anantsuksomsri 1,2 , Jose Alan Castillo 4, Benjamin Smith 5,6 and Nophea Sasaki 7 1 Regional Urban and Built Environmental Analytics, Faculty of Architecture, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand;
[email protected] 2 Department of Urban and Regional Planning, Faculty of Architecture, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand 3 LEET Intelligence Co., Ltd., Perfect Park, Suan Prikthai, Muang Pathum Thani, Pathum Thani 12000, Thailand 4 Ecosystems Research and Development Bureau, Department of Environment and Natural Resources, Forestry Campus, Los Baños, Laguna 4031, Philippines;
[email protected] 5 Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW 2751, Australia;
[email protected] 6 Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12. S-223 62, Sweden 7 Natural Resources Management, SERD, Asian Institute of Technology. P.O. Box 4, Khlong Luang, Pathumthani 12120, Thailand;
[email protected] * Correspondence:
[email protected] Received: 30 July 2020; Accepted: 15 September 2020; Published: 22 September 2020 Abstract: Although vegetation phenology thresholds have been developed for a wide range of mapping applications, their use for assessing the distribution of natural bamboo and the related carbon stocks is still limited, especially in Southeast Asia. Here, we used Google Earth Engine (GEE) to collect time-series of Landsat 8 Operational Land Imager (OLI) and Sentinel-2 images and employed a phenology-based threshold classification method (PBTC) to map the natural bamboo distribution and estimate carbon stocks in Siem Reap Province, Cambodia.