Detecting Tropical Deforestation Using Satellite Radar Data:
A Case Study From Central Sumatra, Indonesia
Study Area
The study area is located approximately in 01
o25'00" to 01
o45'00" Latitude South and 102
o15'00" to 102
o45'00" Longitude East, lies in jambi Province, Bungo Tebo Subdistrict (Kabupaten Bungo Tebo), between Kota Jambi and Gunung Kerinci, in the central of Sumatra island, Indonesia. The study area covers about 50 km x 35 km(1750 km
2), and comprises a mountainous nature reserve area in the west and timber concession areas in the east. Apart from timber concession, the study area also contains the orginal Jambi villages along Batang Tebo, Batang hari, and Batang Tabir rivers, transmigration villages (Kuamang Kuning), and oil palm plantatin/oil palm estate.
The forest concession (HPH) has been selectively logged by PT Sylva Gama (30.000 ha). Part of the concession will be clear felled to establish an Industrial Forest Plantation (HTI). Part of the forest has been allocated for research on forest regeneration and management, and for education purposes for Faculty of Forestry Gadijah mada University.
According to the forest land use planning (TGHH) map and forest vegetation and Land cover maps of Jambi (at scale 1:25.000), the TGHK classes of study area are only two: Production Forest (HP), and conversion Forest (HPK), also one Other Land Use (APL). While land cover of the study area are Unproductive dryland (lktp), Agriculture (Ptn), and Lowland forest (Hr). All the classification above are only on the map,, the reality in the field might be not exactly same as those above classification. Based on
the ground verification had been done, there are seven broad classes (main classes) of land cover types and land use combination, in the study area. Each class also has several sub classes. These are: forest classes including: logged over forest, old secondary forest, young secondary forest; rubber classes including: rubber plantation, untreated rubber plantation, jungle rubber, rubber agro forestry; oil palm plantation classes; rice classes including: wet rice field, dry rice field; clear felled classes including: buth fallow, lading and fallow; water classes; other classes including: temporary agriculture land, dry agriculture land, built up area, home graden, alang-alang grassland, grazing area.
Materials and Methods
The following data were used for this research project: Landsat-5 TM data of September 15, 1993, Spot XS data of March 21, 1993, ERS-1 images of October 17, 1993, June6, 1994, and July 7, 1994, and JERS-1 of August 16, 1993. Research methodology is illustrated in Figure 1.
Figure 1. Detailed Research Methodology
Results and Discussions
The wavelength of the radar system involved has a singnificant affect on the depth of penetration of the radar signal into a forest canopy, and therefore on the resulting backscatter. Different wavelengths( different backscatter) will give different interpretation results. The capability of radar to penetrate the forest canopy or surface layers in increased with the longer wavelengths, as can be seen clearly when both singly L-and C- band are interpreted visually. Actually, both of them can be used for detecting the clear cut as one of the present deforestation type in the study area. Howevery, in the dase of other type of deforestation (rubber) ERS-1 radar image with the shorter wavelength(C-bands) can not distinguish those rubber from the forest, while JERS can. Table 1 shows that JERS-1 image the L-bands can recognize more classes than the ERS-1 with C-bands. It should be noted that ERS-1 with shorter wavelength is better for detecting the settlements and oil palm plantation. The settlements are relatively clearly interpretably by shorter wavelength, because of more backscatter from the roof of houses or other buildings (corner reflection). For the JERS, the settlements are not visible, because the backscatters not noly comes from the surface (roof) of the buildings, but also come from the soil. Thus, there is not enough appearance of corner reflection. Oil palm can also be detected more clearly by the shorter wavelength. In the forest, the C-band (5.7 cm) radar signals will be reflected by the small and medium size branches in the canopy, and the incoming L-band (23 cm) radar energy will be reflected by the large branches and poles (tree trunks) of the trees. When interpreting radar surface or foliage of the canopy. Similarly with the oil palm plantation, where the plants are planted in rows, the backscatter from the canopies is affected by those rows (line pattern).
Table 1. Differences of JES-1 and ERS-1 radar images visual interpretation
| JERS (Lband) |
ERS (C band) |
| Recognize 11 classes |
Recognize 8 classes |
| Can separate old secondary forest and young secondary forest |
Can separate old secondary forest and young secondary forest |
| Can distinguish rubber from forest |
Can distinguish rubber from forest |
| Not good to distinguish the settlement |
Good to distinguish settlement |
| Can distinguish annual crop from agriculture land |
Can distinguish annual crop from agriculture land |
| Can detect clear cut |
Can detect clear cut |
| Plantation pattern of oil palm is not so clear |
Plantation pattern of oil palm is not so clear |
JERS can separate the forest into three classes (log over forest, and even old secondary and young secondary forests). Texture, tone, location and association are the most important image elements used for those detection. Similarly with the agriculture area, using the same image elements, JERS can distinguish the agriculture area into agriculture with other vegetation, with houses, and agriculture with the annual crops.
The angle between the radar beam and a line perpendicular to the surface (Hoffer, et al., 1995), defines the relationship between the incoming radar singnal and the actual slope of the ground. Therefore, the slope of the ground plays and important role. However, because the slope of the study area is relatively flat (horizontal surface), the effect of incidence angle is considerably uniform over the whole image.
The effect of incidence angle may only be recognized from the clear cut deforestation. Clear cut are difficult to distinguish from forested areas in incidence angle less than 30o, but nore clear in incidence angle more than 30o (Hoffer, et al., 1995). Clear cut can be seen in both, but in ERS (with incidence angle 23o) clear cut is more difficult to distinguish from the forest, while clear cut in JERS (with incidence angle 35o) can be seen more clearly. This is based on an assumption that the attenuation of microwave energy will increase with the increasing incidence angle. At higher incidence angle, the microwave will have to travel longer distances to reach the surface target, and consequently will lose the energy. Therefore, for the same object (clear cut), the smaller incidence angle (ERS) will give more bright appearance compared with the higher incidence angle (JERS).
Because both JERS and ERS have "Like Polarized" (VV for ERS) and (HH for JERS), it is believed that polarization makes no difference between them. Even during the interaction between the radar energy and the surface, the polarization will be modified based on the property of that surface.
