Strategies for Incorporating High-Resolution Google Earth Databases to Guide and Validate Classifications: Understanding Deforestation in Borneo

Remote Sensing

Alexis Dorais¹ 

[1] Université de Montréal, 440-520 ch de la Côte-Ste-Catherine, Montréal, QC H2V 2B8, Canada; E-Mail

关键词: deforestation;    Google Earth;    Borneo;    EVI;    REDD;    MODIS;   

DOI  :  10.3390/rs3061157

来源: mdpi

【 摘 要 】

International climate change mitigation initiatives such as REDD-plus have fuelled the need for forest monitoring efforts that focus especially on the carbon rich natural ecosystems that are found in the humid tropics. Such monitoring efforts must tackle challenges intrinsic to these regions, such as high atmospheric contamination from particulates and persistent cloud cover. The emergence of new high-resolution platforms like Google Earth offers new potential scientific uses that can help meet these challenges. Using data from MODIS and detailed observation of Google Earth images, we have produced a yearly time series of deforestation hotspots for the island of Borneo for the 2000 to 2009 period. Our workflow and results demonstrate how multiple free data sources can be combined to greatly enhance the individual capacities of each. The methodology employed to produce this time series demonstrates simple, low-expense techniques that can be used to circumvent the obstacles that typically hinder systematic remote sensing in Borneo and other heavily clouded areas.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.