In recent years, industrial plantations have been rapidly expanding in many parts of the world due to a number of factors: paper companies require a stable supply of pulp, electric power companies are interested in producing biofuel feed-stocks and other companies anticipate the expansion of carbon-trading. Plantation expansions seem inevitable because of the annually increasing global demand for paper. Therefore, it is becoming increasingly clear that the sustainable use of industrial plantations requires continuous investigation to monitor their land productivity and estimate the forest stand volume for commercial purposes.
Earth surface surveys currently take full advantage of remote satellite sensing technology. Both optical and microwave satellites provide key information on forest resources that are very important for the sustainable management of the environment. However, the persistent presence of water vapor and clouds makes continuous monitoring using optical satellite data unfeasible particularly over tropical regions.
Microwave radar imaging satellites are therefore expected to conduct periodic forest monitoring. Polarimetric synthetic aperture radar (POLSAR) is an advanced technology that provides image data with phase (scattering matrix) information, which has made it a center of attention in recent years as an effective instrument for identifying land cover and estimating forest biomass [1
In POLSAR data analysis, the normalized radar cross section (σ0
) is used as a calculated parameter [5
]. However, there is a great deal of interest in making effective use of other parameters derived from the decomposition of the polarimetric information from the target. The target decomposition theorem has been developed to extract surface features from radar polarimetry data. Both the three-component scattering model developed in [10
] and the entropy/alpha decomposition method developed in [11
] have been commonly used and are currently being improved for more accurate target classification [12
]. The Freeman and Durden approach [16
] was developed based on the three-component scattering model, which represents the surface, double-bounce and volume (canopy) scatterings. This scheme was further improved by the addition of a helix scattering term as a fourth component and the modification of the volume scattering model [12
]. Furthermore, Yamaguchi et al
] improved the four-component decomposition scheme using matrix rotation to enhance the results by allowing oriented urban areas previously and mistakenly included in the volume scattering component as double-bounce scattering to be distinguished. In addition to the POLSAR data, there has been an increase in research on the use of Polarimetric Interferometry SAR (POLinSAR) techniques [2
] particularly for tree height estimations.
In this study, we examine the polarimetric SAR image decomposition scheme. A few studies have attempted to retrieve forest structural parameters, such as the tree diameter, tree height and timber volume, using polarimetric decomposition theorems. Garestier et al
] conducted an eigenvector decomposition scheme that showed a linear correlation between the anisotropy and tree height using a P-band over pine trees. Gonçalves et al
] reported the usefulness of the volume scattering derived from the Freeman and Durden decomposition and several other backscattering coefficients for tropical forests using the L-band. Notably, targets in both of these studies [1
] had thick stems, and the studied tropical forests [4
] had a dense canopy. Moreover, very few studies have examined the fast-growing tree forests with thin stems and low canopy densities. Fast-growing trees in the commercial Eucalyptus plantations were investigated using backscattering coefficients from the JERS-1 single-polarization SAR image [17
] and by interferometry SAR [2
] for biomass estimation.
It is well known that the accuracy of forest biometric parameter estimations is site-dependent [8
] and affected by the forest structure [19
], shape and dimensions of leaves and stems [21
], and the ground conditions. Little is known about the backscattering characteristics of Acacia trees under a power decomposition scheme.
In our previous work [22
], we obtained the following characteristic features for the backscattering cross section of an L-band SAR over planted Acacia forests: (i) the regression between the normalized radar cross section (σ0
) and the forest stand parameter fits a negative quadratic curve because of the stronger backscattering from approximately two year old trees, and the weaker backscattering from both trees younger than two years and more mature trees; (ii) the optical NDVI values for trees older than two years tend to decrease. These findings suggest that the L-band SAR is strongly affected by the acacia tree foliage.
Therefore, the aim of this study was to extract tree trunk information for the planted Acacia Mangium forests via the decomposition of multi-polarimetric SAR data, and find out the relationship between the decomposition powers and the in-situ forest biometric data through an integrated analysis. From the above findings, we attempted to formulate a methodology for estimating the forest stand volume.
2. Study Area
The study area is located in the southeastern part of the island of Sumatra, Indonesia (Figure 1(a)
). There are approximately 10 units in the plantation area managed by the plantation company with each one being considered a maximum management unit. Our targeted area was the unit (Unit V) situated between 3°36′48″S and 3°58′54″S latitude and 103°50′42″E and 103°58′23″E longitude (Figure 1(b)
). It covers approximately 282.9 km2
with an altitude ranging from 41 to 253 m (average of 111.5 m) above sea level and a slope varying from 0 to 14.9 degree (3.4° on average).
The total plantation area covers 134.7 km2 (equivalent to 47.9%) of the total area of Unit V (the unit area is not used exclusively for industrial plantations). The mean annual rainfall varies between 2,000 and 3,000 mm per year. This area has a tropical climate; a dry season prevails between June and September, and a rainy season prevails between October and May with two rainfall peaks in December–January and March–April. The average daily temperature is 29 °C, the average minimum temperature is 21 °C and the average maximum temperature is 32 °C.
The plantation area consists of a single-layer forest of Acacia Mangium
, which is a fast-growing tree normally harvested between 6 and 7 years after planting the seedlings. Tree planting in this area began in 1990 with the approval of the Indonesian Government on initially unproductive sites where alang-alang (Imperata cylindrica
) grass and poor secondary forests dominated [23