JpGU-AGU Joint Meeting 2017

Presentation information

[EJ] Oral

S (Solid Earth Sciences) » S-TT Technology & Techniques

[S-TT57] [EJ] Synthetic Aperture Radar

Wed. May 24, 2017 10:45 AM - 12:15 PM 201A (International Conference Hall 2F)

convener:Yosuke Miyagi(National Research Institute for Earth Science and Disaster Resilience), Shoko Kobayashi(Tamagawa University), Tsutomu Yamanokuchi(Remote Sensing Technology Center of JAPAN), Yu Morishita(Geospatial Information Authority of Japan), Chairperson:Yousuke Miyagi(National Research Institute for Earth Science and Disaster Resilience), Chairperson:Yu Morishita(Geospatial Information Authority of Japan)

12:00 PM - 12:15 PM

[STT57-06] Development of early deforestation detection algorithm (advanced) with PALSAR-2/ScanSAR for JICA-JAXA program (JJ-FAST) 3 – Time series analysis in South America –

*Manabu Watanabe1, Christian Koyama1, Masato Hayashi2, Hiroshi Miyoshi2, Masanobu Shimada1,2 (1.School of Science and Engineering, Tokyo denki university, 2.JAXA)

Keywords:Forest monitoring, ALOS-2, Polarimetry

Time series PALSAR-2/ScanSAR data were used for detecting early-stage deforestation. The data were taken 9 times/year, following ALOS-2 systematic observation strategy [1], and it covers global areas, including major tropical forest in the world. By using this data, JICA and JAXA launched a service, “JICA-JAXA Forest Early Warning System in the Tropics (JJ-FAST)” in November 2016 [1]. The system is on the web, and is freely accessible from a smartphone or other devices. Decrease of Gamma0HV are observed after deforestation, and current algorithm uses HV polarization data and two data taken in different timing. HH polarization, and time series data will be used for the future operation. Time series data obtained in South America with HH and HV polarizations were used, and compared it to the Landsat data to clarify the ability to detect the early-stage deforestation, where fallen trees were left on the ground. The Sigma0HH value increased by 1.2 dB in areas undergoing the early stages of deforestation. The detection timing is almost same as that using the optical sensor. On the other hand, the Sigma0HV value decreased by 3.2 dB for late-stage deforestation areas, where fallen trees were removed. The detection timing is about a few month after the detection of deforestation by Sigma0HH, or optical sensor. Many errors of the deforestation detection were observed at wet forest areas. Temporal variations of Gamma0 were observed for the area, which induces the deforestation detection errors. The variations of Gamma0 shows some correlation with precipitation for both HH and HV polarization [3], and flooding, variation of moisture for soil and trees may be the possible cause for the Gamma0 variation.

[1] ALOS-2 systematic observation strategy, Accessed February 16, 2017
[2] JJ-FAST,, February 16, 2017
[3] Manabu Watanabe, et al., Multi-temporal Fluctuations in L-band Backscatter from a Japanese Forest, IEEE Trans. Geosci. Remote Sensing, 53(11), 5799-5813, 2015