Remotely sensed indicators of habitat heterogeneity: Use of synthetic aperture radar in mapping vegetation structure and bird habitat

An integrated remote sensing/field ecology project linked the use of synthetic aperture radar (SAR) and aerial photography to studies of landscape spatial heterogeneity and bird community ecology. P-, L-, and C-band SAR data, collected over a section of Kakadu National Park in Australia's Northern Territory during the Joint NASA/Australia DC-8 data acquisition campaign, were analyzed in light of field data integrating vegetation structure and floristics with bird abundances across a heterogeneous study site. Results indicate that SAR data are able to discern structural differences relevant to bird habitat quality within floristically homogeneous stands, while multispectral sensors successfully identified floristic differences among habitat types. Simplifying indices of bird diversity showed ambiguous changes across the site; however, the abundances of individual species were observed to change significantly across both floristic and structural gradients. These results suggest that efforts to map bird diversity should focus on species-specific habitat relationships and that some measure of vegetation structure is needed to understand bird habitat. The approach employed here advances the use of SAR data in the three-dimensional mapping of animal habitats from remotely sensed data, and extends current capabilities for mapping and modeling large-scale patterns in the distribution of biological diversity.

[1]  J. Woinarski,et al.  The Bird Fauna of a Deciduous Woodland in the Wet-Dry Tropics of Northern Australia. , 1991 .

[2]  D. Bowman,et al.  Biogeographic patterns, environmental correlates and conservation of avifauna in the Northern Territory, Australia , 1992 .

[3]  Richard T. Reynolds,et al.  A Variable Circular-Plot Method for Estimating Bird Numbers , 1980 .

[4]  Marc L. Imhoff A theoretical analysis of the effect of forest structure on synthetic aperture radar backscatter and the remote sensing of biomass , 1995 .

[5]  Kamal Sarabandi,et al.  Estimation of forest biophysical characteristics in Northern Michigan with SIR-C/X-SAR , 1995, IEEE Trans. Geosci. Remote. Sens..

[6]  Thuy Le Toan,et al.  Relating forest biomass to SAR data , 1992, IEEE Trans. Geosci. Remote. Sens..

[7]  Guoqing Sun,et al.  Northern forest classification using temporal multifrequency and multipolarimetric SAR images , 1994 .

[8]  E. C. Pielou The measurement of diversity in different types of biological collections , 1966 .

[9]  W. Lawrence,et al.  Utilization of SAR and optical remote sensing data for habitat conservation in the tropical forest of Brazil , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[10]  M. Soulé,et al.  Conservation Biology: The Science of Scarcity and Diversity , 1987 .

[11]  Marc L. Imhoff,et al.  Radar backscatter and biomass saturation: ramifications for global biomass inventory , 1995 .

[12]  Eric S. Kasischke,et al.  Connecting forest ecosystem and microwave backscatter models , 1990 .

[13]  John A. Wiens,et al.  The Ecology Of Bird Communities , 1989 .

[14]  J. Paris,et al.  Probing Thick Vegetation Canopies with a Field Microwave Scatterometer , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Guoqing Sun,et al.  Boreal forest ecosystem characterization with SIR-C/XSAR , 1995, IEEE Trans. Geosci. Remote. Sens..

[16]  F. Amar,et al.  Biomass and structure estimation of primary and secondary tropical rain forests using AirSAR data , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[17]  Jack F. Paris,et al.  Radar remote sensing of forest and wetland ecosystems in the Central American tropics , 1994 .

[18]  Jan Askne,et al.  Potential of SAR for forest bole volume estimation , 1994 .

[19]  Thuy Le Toan,et al.  Dependence of radar backscatter on coniferous forest biomass , 1992, IEEE Trans. Geosci. Remote. Sens..