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Forestry
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Separation (Recognition) of tree species or species composition in an old growth forest
Plantation in Peninsular Malaysis using the Vegetation Index approach
Result
The VI values were found to correlate with 6 species, namely Pinus insulariis, Pinus caribeae, Pterocarpus sp., Dryobalanops sp., Dipterocarpus sp. And Shorea sp. It was also possible to determine the range of values for each of these species. However, their values varied tremendouslyfor different VIs and the two images. Nonetheless, the values do not overlap. Between the 6 species only P. insularies and Pterocarpus sp. Show some overlap when NDVI and F2 methods were used. It is also interesting to note that there are several instances where VIs produced a singly value. A comparison of these VI values is presented in Table 1.
Table 1. Values of the difference VIs for the 6 species recognizable from the two images used in the study.
The confusion matrix shows that accuracy varies for the different VIs and the two different years. Accuracy ranged from slightly above 40% to almost 80 percent. The 1988 data resulted in higher accuracy as compared to the 1993 data. The comparison of the different VIs shows that for eh 1988 image SVI and F1 produced the highest accuracy of different VIs in classifying the 6 species from the 2 images is presented in Table 2.
Table 2. Overall average accuracy for different Vis
| |
1988 |
1993 |
| Average |
Average |
| SVI |
74.54 |
60.92 |
| RVI |
55.87 |
64.35 |
| NDVI |
56.21 |
62.40 |
| TVI |
61.33 |
65.01 |
| F1 |
77.53 |
53.12 |
| F2 |
60.32 |
41.31 |
Summary
The VIs were found to be significant in helping to recognize and map forest species where the mixture of species are not as complex as in a natural forest. With the increase in the scale of reforestation and esablishment of forest plantations carried out in Malaysia and throughout the region, remote sensing can become a very useful survey and mapping approach for the management of future forest or natural resources. Even though under this study the classification was generalized and limited to only 6 species, it could, nevertheless, indicate that a more detailed analysis may uncover new potentials for using remote sensing data to map forest resources at a much refined scale suitable for various practical management uses. One of the disadvantages of TM data is in its spatial resolution at a much refined scale suitable for various practical management uses. One of the disadvantages of TM data is in its spatial resolution which results in mixed pixels. It is impossible to classify these mixed pixels down to species level. With the availability of a new higher resolution sensor, the problem of mixed pixels may be resolved. The authors feel very strongly that with higher spatial resolution data, the success rate in mapping forest resources, especially forest plantation areas, at species level will be much higher.
Acknowledgement
The authors wish to record our appreciation to En Anan Ahmad for carrying out the mapping and digital processing work.
Reference
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Elvidge, C.D. and Chen, Z. (1995). Comparison of broad-band and narrow-band Red and Near-Infrared Vegetation Indices. Remote Sens. Environ. 54,38-48.
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