Keywords:Backscatter, Classification, Coherence, Land cover, SAR
Abstract: In Indonesia, tropical rain forest is one of the major natural resource covering
60% of the total area. Much of the rain forests have been destroyed, while the rate of
deforestation is not well known in many regions. It is therefore necessary to observe land cover
frequently to monitor the rate of the changes. In a region under frequent cloud cover, like
Indonesia, it is hard to obtain cloud-free images by optical band sensors. The authors tried to
monitor the land cover by JERS-1 and ERS-1/-2 SAR data including both backscatter and
coherence images. The study area is situated in Sumatra island, Indonesia, where five land cover
categories (plantation type 1, plantation type 2, forest area, deforested area, and bare soil) exist.
The methodologies used were as follow: 1) Evaluating the performance of backscatter and
coherence images, obtained by each sensor, in identification of land cover. 2) Finding out the
best combination of SAR sensors and images in land cover classification. Following results
were obtained: 1) Only two broad categories (i.e. vegetated area and non-vegetated area) were
satisfactorily identified with the backscatter image by ERS-1/-2, while four categories were
classified by combining the backscatter image with the coherence image by ERS-1/-2. 2) Three
to four categories were classified with the backscatter image by JERS-1 and adding coherence
data failed to improve the accuracy of classification. 3) Four to five categories were classified
by combining backscatter image of ERS-1/-2 with the same of JERS-1. For the purpose of
assessing land cover, in the terms of operation, it is hard to obtain a coherence image, for
ERS-1/-2 should be in tandem operator mode and finding a “good pair” of JERS-1 data is not
always feasible. Combining backscatter image of ERS-1/-2 with the same of JERS-1 therefore
seems the beat practical way to identify the land cover of the study area, for it does not require
coherence images.
1. Background:
Use of coherence data from operational satellite based SAR sensors (e.g. on ERS-1/-2 or
JERS-1), in addition to ordinary backscatter data, has been experimented both on C and L band
to identify landcover in tropics (Ribbes et. al., 1999; Siegert and Nakayama, 1999).
While coherence data proved useful to improve accuracy in landcover identification, such
data are not readily available. It is because ERS-1 and –2 should be in tandem operation mode to
secure a pair of ERS SAR data suitable for interferometry in tropics (Stussi, et. al., 1996), and
repeat-pass interferometry by JERS-1 SAR data is often not feasible due to a large distance
between two orbits.
On the other hand, integrated use of backcatter data by multiple satellites is readily
feasible. The very question to be asked is whether integration of backscatter data on multiple
bands (e.g. C and L band) is either inferior or superior to use of coherence data. Most of
previous researches, on use of coherence data for landcover identification in tropics,
concentrated on use of data on single band. We therefore still do not have a solid clue to answer
to the very question.
The aim of this study is to evaluate the performance of "integrated use" of backscatter data
on C and L band (by ERS and JERS respectively) to identify landcover, vis-a-vis the same by
combination of backscatter and coherence data by single satellite.
