Collaborative LTREB: Experimental and observational studies of mangrove forest structure and gap dynamics

National Science Foundation Award # 0810933 #0614040

Oct. 1, 2006 – Sept. 30, 2011


2000 IKONOS Imagery illustrating three different mangrove species in our study site at Panama

Principal Investigator:

Le Wang

Department of Geography

State University of New York at Buffalo

Collaborative Investigator:

Wayne P. Sousa

Department of Integrative Biology

University of California at Buffalo



Mangroves, once occupied 75% of the world’s tropical and subtropical coastlines, are a unique forest type that provide critical “ecosystem services”, one of which was recently evidenced in the 2004 Indian Ocean Tsunami, i.e. areas with intact seaward mangrove forests suffered much less human death and property destruction than otherwise. Unfortunately, the persistence of these important and distinctive coastal ecosystems is gravely threatened by a plethora of human-caused environmental perturbations.  Previous research estimated that as much as a third of the world’s mangrove forest have been lost in the past 50 years.  In the Caribbean, the region of our current research on mangrove forest dynamics, the rate of mainland mangrove deforestation is estimated to be 1.4-1.7% annually ,comparable to the rates documented for threatened tropical rainforests and adjacent coral reefs.  In this research, we propose to map and monitor the spatial distribution, species composition, and health of coastal mangrove forests through high spatial resolution and hyperspectral remote sensing imagery.



  1. Wang, L., and W. Sousa. Distinguishing mangrove species with laboratory measurements of hyperspectral leaf reflectance, International Journal of Remote Sensing, in press.
  2. Wang, L., J. Silvan, and W. Sousa. 2008. Neural network classification of mangrove species from multiseasonal IKONOS imagery, Photogrammetric Engineering and Remote Sensing, 74(7): 921-927.
  3. Wang, L., W. Sousa, and P. Gong. 2004. Integration of object-based and pixel-based classification for mangrove mapping with IKONOS imagery, International Journal of Remote Sensing 25(24): 5655-5668.(the #1 mostly downloaded paper in 2005 with IJRS)
  4. Wang, L., W. Sousa, P. Gong, G.S. Biging. 2004. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama, Remote Sensing of Environment 91(3-4): 432-440 (the #22 mostly downloaded paper in 2004 with RSE).