Measurement of Mangrove Biophysical Characteristics in the Bocozelle Ecosystem in Haiti Using ASTER Multispectral Data

Abstract Coastal mangrove vegetation in Haiti continues to be threatened and diminished consistently due to uncontrolled logging. Research on Haitian mangroves is required to monitor their state and ensure their sustainable management. Indeed, planners and resource managers have a critical need for accurate inventories of mangrove communities and their biophysical characteristics. This study was performed to assess the usefulness of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data for predicting mangrove biophysical variables. In situ data, such as tree height, diameter at breast height, leaf‐area index (LAI), and percent canopy closure were collected in 32 plots (10 × 10 m) along nine (9) transects located perpendicular to the shoreline in July, 2005. The data were correlated and regressed with remote sensing‐derived vegetation indices determined from an ASTER image acquired on July 18, 2005. All the vegetation parameters were found to have strong correlation with the indices. In particular, percent canopy closure and LAI had correlations of 0.851 and 0.908 with the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI), respectively. This research supports the utility of remote sensing data for mangrove biophysical investigations, especially for determining the percent canopy closure and leaf area index which are respectively indirect estimations of tree density and vegetation biomass.

[1]  J. R. Jensen.  Remote Sensing of the Environment: An Earth Resource Perspective , 2000 .

[2]  J. R. Jensen,et al.  Remote Sensing of Mangrove Wetlands: Relating Canopy Spectra to Site-Specific Data , 1996 .

[3]  E. C. Ashton,et al.  Preliminary assessment of the plant diversity and community ecology of the Sematan mangrove forest, Sarawak, Malaysia , 2002 .

[4]  B. Kjerfve.  Tides of the Caribbean Sea , 1981 .

[5]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[6]  John R. Jensen,et al.  Remote sensing of mangrove biophysical characteristics , 1998 .

[7]  D. Eamus,et al.  The abundance and growth of Avicennia marina and Rhizophora stylosa in the low shore zone of Darwin Harbour, Northern Territory , 1996 .

[8]  John R. Jensen,et al.  Extraction of smooth cordgrass (spartina alterniflora) biomass and leaf area index parameters from high resolution imagery , 1998 .

[9]  N. Koedam,et al.  Application of Remote Sensing and GIS in the Management of Mangrove Forests Within and Adjacent to Kiunga Marine Protected Area, Lamu, Kenya , 2002 .

[10]  P. Mumby,et al.  Remote Sensing Handbook for Tropical Coastal Management , 2000 .

[11]  John R. Jensen.  Introductory Digital Image Processing , 2004 .

[12]  A. C. Ellis,et al.  Estimating leaf area index of mangroves from satellite data , 1997 .

[13]  A. Lugo,et al.  The Ecology of Mangroves , 1974 .

[14]  J. R. Jensen,et al.  The measurement of mangrove characteristics in southwest Florida using spot multispectral data , 1991 .

[15]  M. Glaser.  Interrelations between mangrove ecosystem, local economy and social sustainability in Caeté Estuary, North Brazil , 2003, Wetlands Ecology and Management.

[16]  M. Aubé,et al.  The mangroves of the north coast of Haiti , 2001, Wetlands Ecology and Management.

[17]  John R. Jensen,et al.  Remote Sensing of Biomass, Leaf‐Area‐Index, and Chlorophyll a and b Content in the ACE Basin National Estuarine Research Reserve Using Sub‐meter Digital Camera Imagery , 2002 .

[18]  G. Birth,et al.  Measuring the Color of Growing Turf with a Reflectance Spectrophotometer1 , 1968 .