Development of Forest Canopy Density Mapping and Monitoring Model using Indices of Vegetation, Bare soil and Shadow
b. Vegetation Density; VD
It is the procedure to synthesize VI and BI.. Processing method is using principal component analysis. Because essentially, VI and BI have hight correlation of negative. After that, set the scaling of zero percent point and a hundred percent point. Details in (A. Rikimaru, 1996)
c. Black Soil Detection
SI data is extracted from the low irradiance area of each visible band. Where the soil black or appear to be black due to recent slash-and-burn, low irradiance data may confuse shadow phenomenon with black soil conditions. This is because black soil usually has high temperature due to its high absorption rate of sun energy. But shadow lead to a decrease in soil temperature. By overlying TI data this confusion can be avoided. Overlays are
also useful when evaluating the relative irradiance of different parcels of land characterized by various shades of black soil.
d. Advance Shadow Index; ASI
When the forest canopy is very dense, satellite data is not always be able to indicate the relative intensity of the shadow. Consequently, crown density might be underestimated. To deal with this problem, the new methods include those described below for determining the spatial distribution of shadow information. Details in (A.Rikimaru.1996).
e. Scaled Shadow Index; SSSI
The shadow index (SI) is a relative value. Its normalized value can be utilized for calculation with other parameters; The SSI was developed in order to integrate VI values and SI values. In areas where the SSI value is zero, this corresponds with forests that have the lowest shadow value (i.e.0%). In areas were the SSI value is 100, this corresponds with forests that have the highest possible shadow value (i.e.100%).SSI is obtained by linear transformation of SI. With development of the SSI one can now clearly differentiate between vegetation in the canopy and vegetation on the ground. This constitutes one of the major advantage of the new methods. It significantly improves the capability to provided more accurate result from data analysis than was possible in the past.
f. Integration process to achieve FCD model
Integration of VD and SSI means transformation for forest canopy density value. Both parameter has dimension and has percentage scale unit of density. It is possible to synthesize both indices safely by means of corresponding scale and unit of each
FCD=(VD+SSI+1) 1/2-1
5.Result and Comments
The accuracy of methodology is checked in field test. The case of Sumatra Indonesia, The correlation coefficient value between FCD model and field check shows 0.922. It indicates very high correlation and results means high accuracy.
FCD model is very useful for monitoring and management for the future with less ground truth survey.
Acknowledgment
This work was carried out with the project of International Tropical Timber Organization (ITTO). The authors would like to express gratitude to Dr. Surachai NRCT Thailand Agung Ministry of Foresty Indonesia, Dr. P.S.Roy IIRS India, Dr.Virgilio F.Basa Philippines, Mr. K.B. Chitrakar Institute of Foresty Nepal, Mr. Patric C.Dugan and all of counterpart persons for their ITTO project support.
Reference
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JOFCA.1991. Classification system on logged-over forest. A workshop for the ITTO projects PD2/87(F) Subproject II. Rehabilitation of logged-over forest in Asia/Pacific. Manila, Philippines, December 1991.
- JOFCA.1993.rehabilitation of logged-over forest in Asia/Pacific region, final report of sub-projects II. Prepared for ITTO. March 1993. Part II pp.1-41
- JOFCA.1995. Proceedings of the workshop on utilization of remote sensing in site assessment and planning for rehabilitation of logged-over forest. Cisarua, Bogor. Indonesia, September 25-28,1995.
- JOFCA.1996. Proceedings of the workshop on utilization remote sensing in site assessment and planning for rehabilitation of logged-over forest. Bangkok, Thailand , July30- August 1,1996.
- A.Rikimaru. 1996. LAMDSAT TM Data Processing Guide for forest Canopy Density Mapping and Monitoring Model. ITTO workshop on utilization of remote sensing in site assessment and planning for rehabilitation of logged-over forest. Bangkok, Thailand, July 30- August 1,1996.pp.1-8
- JOFCA. 1997. Utilization of remote sensing in site assessment and planning for rehabilitation of logged-over forests. Project report on PD32/93 Rev.2(F) Rehabilitation of logged-over forest in Asia/ Pacific region, Sub-project III Prepared for ITTO. January 1997.
