Summary, Introduction, Methods, Analysis, Results, Discussion, References, Acknowledgements, Photos, Links

Analysis

Spatial analysis of satellite imagery and Marona clumps was undertaken using Arc/Info® (see Appendix 1 for associated .aml files). UTM positions for Marona clumps were used to generate a point coverage, which was subsequently buffered by 20 m. This was used to generate a supervised classification using the reflectance characteristics in the vicinity of Marona clumps. Other reflectance classes were also incorporated for comparison. The image classes were: 1 floodplain forest with high likelihood of Marona; 2 floodplain forest with low likelihood of Marona; 3 water bodies and cloud shadows; 4 beaches, goldmines ("chupaderas", Valega 1999), short grass and clouds; 5 forest of high reflectance dominated by secondary vegetation, G. weberbaueri, G. sarcocarpa or bambusoids; 6 terra firme forest; 7 palm dominated swamp forest. Arc/View® was also used as a mapping tool. The software packages MS Excel® and SPSS® 10.0 were used to undertake the statistical analyses of clump characteristics, which included non-parametric (Mann-Whitney U, Kruskall Wallis and Chi²) as well as parametric ANOVA, regression and correlation methods. Marona density along transects was calculated using the following standard equation:

D = (N / 2WL) / 100; where D = density (clumps/ha), N = number of clumps encountered, W = detection distance (km), L = transect length (km).

Summary, Introduction, Methods, Analysis, Results, Discussion, References, Acknowledgements, Photos, Links