11:15 〜 11:30
[MSD40-09] Multi-footprint Observation Lidar and Imager (MOLI ) mission for performing highly precise estimation of elevation, forest height & biomass, and also for providing results of clouds & aerosols measurement
キーワード： ライダー、樹冠高、森林バイオマス、LバンドSAR、イメージャ、雲＆エアロゾル
Forests have a strong impact on our survival and are highly relevant to climate change and extreme weather events associated with recent global warming. They, as is well known, are the second largest carbon reservoir on Earth after the oceans because they convert atmospheric CO2 absorbed through photosynthesis into organic biomass for fixation. Most of the forest carbon is contained in living biomass (aboveground biomass (AGB) + aboveground biomass (BGB), 44%) and soil organic matter (45%), with the remainder in dead trees and litter. The total carbon stock is estimated to be 662 Gt in 2020 (FAO). The explosive population growth in the 20th and 21st centuries has resulted in deforestation and forest degradation due to rapid changes in land use associated with increased food production and the need to develop infrastructure such as residential and industrial areas. The amount converted into CO2 by land use change including illegal logging and wildfires is, surprisingly, equivalent to 13% of anthropogenic CO2 emissions. Therefore, there is a strong need for 24-hour global monitoring of our precious forests from space.
L-band SAR (PALSAR/ALOS, PALSAR-2/ALOS-2, etc.) has provided valuable data on forest biomass around the world. However, it is said that the backscatter signal is saturated in dense tropical rainforests where the biomass exceeds 150 Mg/ha. In addition, in closed mature forests, wetland forests and mangrove forests in Japan, there are some problems such as overestimation of biomass estimates due to double reflection by water surface. In this regard, a space lidar based on pulsed laser altimetry can essentially evaluate the height of the forest canopy (DCHM) by calculating the time difference between the scattered signal from the top of the forest canopy (DSM) and the scattered signal from the ground surface (DTM). The AGB in the footprint can also be estimated using full waveform data and multiple regression analysis.
The objectives of MOLI (Multi-footprint Observation Lidar and Imager) mission proposed in this paper is to demonstrate Japan's first space-based lidar and to perform highly precise estimation of elevation, forest canopy height, and three-dimensional structure information necessary for AGB evaluation, but also to provide optical atmospheric parameters. Furthermore, we aim to establish a fusion analysis algorithm with MOLI data, L-band SAR data, and passive spectral data from GCOM-C/SGLI etc., which will contribute to remarkable improvement of global forest biomass monitoring. We are currently working on the development of the laser transmitters for the lidar and algorithms for Level-1 and Level-2 products as follows.
I. Regarding the lidar, the space qualified prototype laser (EM level) maintained output power of 40mJ, repetition rate of 150Hz, and pulse width of 7nsec. A thermal shock test in a thermostatic bath, a thermal vacuum test, and a vibration test showed good results.
II. Development of a method for estimating elevation and slope using MOLI data: In this study, we developed a method for estimating slope and aspect of footprints using AW3D, the global DSM data set. i) The time gap problem was cleared, ii) the developed method can estimate the slope and aspect even in the missing conditions from 1DEM to 3DEM.
III. Development of Level-2 Product Algorithm: The AGB estimation model was validated using point cloud data of 34,000 ha acquired by airborne LiDAR, and it was confirmed that the model could estimate with an accuracy of 47 Mg ha-1, ii) We will improve the accuracy and the model.
IV. Algorithm development to detect cloud layers and retrieve optical properties of atmospheric particles: We focused on i) simulating lidar signals for cloud, aerosol, and clear-sky layer detection, ii) cloud detection using the threshold method, and iii) extinction/backscatter retrieval of aerosols and clouds.
Figure shows a conceptual diagram of MOLI onboard the ISS-JEM-EF.
L-band SAR (PALSAR/ALOS, PALSAR-2/ALOS-2, etc.) has provided valuable data on forest biomass around the world. However, it is said that the backscatter signal is saturated in dense tropical rainforests where the biomass exceeds 150 Mg/ha. In addition, in closed mature forests, wetland forests and mangrove forests in Japan, there are some problems such as overestimation of biomass estimates due to double reflection by water surface. In this regard, a space lidar based on pulsed laser altimetry can essentially evaluate the height of the forest canopy (DCHM) by calculating the time difference between the scattered signal from the top of the forest canopy (DSM) and the scattered signal from the ground surface (DTM). The AGB in the footprint can also be estimated using full waveform data and multiple regression analysis.
The objectives of MOLI (Multi-footprint Observation Lidar and Imager) mission proposed in this paper is to demonstrate Japan's first space-based lidar and to perform highly precise estimation of elevation, forest canopy height, and three-dimensional structure information necessary for AGB evaluation, but also to provide optical atmospheric parameters. Furthermore, we aim to establish a fusion analysis algorithm with MOLI data, L-band SAR data, and passive spectral data from GCOM-C/SGLI etc., which will contribute to remarkable improvement of global forest biomass monitoring. We are currently working on the development of the laser transmitters for the lidar and algorithms for Level-1 and Level-2 products as follows.
I. Regarding the lidar, the space qualified prototype laser (EM level) maintained output power of 40mJ, repetition rate of 150Hz, and pulse width of 7nsec. A thermal shock test in a thermostatic bath, a thermal vacuum test, and a vibration test showed good results.
II. Development of a method for estimating elevation and slope using MOLI data: In this study, we developed a method for estimating slope and aspect of footprints using AW3D, the global DSM data set. i) The time gap problem was cleared, ii) the developed method can estimate the slope and aspect even in the missing conditions from 1DEM to 3DEM.
III. Development of Level-2 Product Algorithm: The AGB estimation model was validated using point cloud data of 34,000 ha acquired by airborne LiDAR, and it was confirmed that the model could estimate with an accuracy of 47 Mg ha-1, ii) We will improve the accuracy and the model.
IV. Algorithm development to detect cloud layers and retrieve optical properties of atmospheric particles: We focused on i) simulating lidar signals for cloud, aerosol, and clear-sky layer detection, ii) cloud detection using the threshold method, and iii) extinction/backscatter retrieval of aerosols and clouds.
Figure shows a conceptual diagram of MOLI onboard the ISS-JEM-EF.