论文信息 - Semi-Automatic Deforestation Detection Algorithm with PALSAR-2/ScanSAR HH/HV Polarizations

Semi-Automatic Deforestation Detection Algorithm with PALSAR-2/ScanSAR HH/HV Polarizations

A preliminary version of the semi-automatic deforestation detection algorithm was developed for the JJ-FAST system, which monitors deforestation and forest changes in tropical regions for approximately every 1.5 months and covers 77 countries. PALSAR-2/ScanSAR HH, HV, HH and HV ratio were used to detect various deforestation stages. Multitemporal data were used to suppress the effect of seasonality and rainfall. Moreover, the deforestation accuracies for the active deforestation spots in Brazil and Peru were estimated. The user's accuracies achieved as 80.5% in the dry season, but these decreased to 11.1% in the rainy season.

[1] Manabu Watanabe,et al. Multitemporal Fluctuations in L-Band Backscatter From a Japanese Forest , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[2] João Roberto dos Santos,et al. Evaluation and perspectives of using multitemporal L-band SAR data to monitor deforestation in the Brazilian Amazo/spl circ/nia , 2005, IEEE Geoscience and Remote Sensing Letters.

[3] Masanobu Shimada,et al. An Evaluation of the ALOS PALSAR L-Band Backscatter—Above Ground Biomass Relationship Queensland, Australia: Impacts of Surface Moisture Condition and Vegetation Structure , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4] Manabu Watanabe,et al. Early-Stage Deforestation Detection in the Tropics With L-band SAR , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[5] R. Lucas,et al. New global forest/non-forest maps from ALOS PALSAR data (2007–2010) , 2014 .

[6] John A. Richards,et al. The effect of changing environmental conditions on microwave signatures of forest ecosystems - Preliminary results of the March 1988 Alaskan aircraft SAR experiment , 1990 .