Progress of the ISS Based Vegetation LiDAR Mission, Moli - Japan's First Space-Based LiDAR

Sakaizawa, Daisuke; Trung, Nguyen Tat; Mitsuhashi, Rei; Sawada, Yoshito; Imai, Tadashi; Kimura, Tomoki

doi:10.1109/igarss39084.2020.9323332

Cited by 6 publications

(8 citation statements)

References 4 publications

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“…It will mark the inaugural forest observation system to concurrently employ LiDAR and an imager, enabling multiple footprint observations simultaneously. This sensor will be installed aboard the International Space Station and will consist of a 1064 nm dual-beam LiDAR with a pulse repetition frequency of 150 Hz for yielding two parallel paths separated by 50 m on the ground and footprints of 25 m at 50 m intervals along track [ 56 ]. Note that it is possible to measure the slope angle by analyzing triangular triplets of footprints to correct canopy height and ground elevation errors due to slope.…”

Section: Discussionmentioning

confidence: 99%

“…Previous simulations in the MOLI system have expected to obtain estimates of canopy height with an error of ±3 m (canopy height less than 15 m) and a relative error of ±20% (canopy height greater than 15 m). In the same way, AGB will be estimated with an error of ± 25 t/ha (AGB below 100 t/ha) and ±25% relative error (AGB above 100 t/ha) [ 56 ]. Finally, the LiDAR Surface Topography (LIST; NASA), which is scheduled to launch in 2025, will mount a very powerful photon-counting detection system with 1000 beams to achieve footprints of 5 m in diameter separated by about 0.7 m on the ground (swath mapping).…”

Section: Discussionmentioning

confidence: 99%

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Forestry Applications of Space-Borne LiDAR Sensors: A Worldwide Bibliometric Analysis

Aguilar,

Rodríguez,

Aguilar

et al. 2024

Sensors

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The 21st century has seen the launch of new space-borne sensors based on LiDAR (light detection and ranging) technology developed in the second half of the 20th century. Nowadays, these sensors offer novel opportunities for mapping terrain and canopy heights and estimating aboveground biomass (AGB) across local to regional scales. This study aims to analyze the scientific impact of these sensors on large-scale forest mapping to retrieve 3D canopy information, monitor forest degradation, estimate AGB, and model key ecosystem variables such as primary productivity and biodiversity. A worldwide bibliometric analysis of this topic was carried out based on up to 412 publications indexed in the Scopus database during the period 2004–2022. The results showed that the number of published documents increased exponentially in the last five years, coinciding with the commissioning of two new LiDAR space missions: Ice, Cloud, and Land Elevation Satellite (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI). These missions have been providing data since 2018 and 2019, respectively. The journal that demonstrated the highest productivity in this field was “Remote Sensing” and among the leading contributors, the top five countries in terms of publications were the USA, China, the UK, France, and Germany. The upward trajectory in the number of publications categorizes this subject as a highly trending research topic, particularly in the context of improving forest resource management and participating in global climate treaty frameworks that require monitoring and reporting on forest carbon stocks. In this context, the integration of space-borne data, including imagery, SAR, and LiDAR, is anticipated to steer the trajectory of this research in the upcoming years.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Forestry Applications of Space-Borne LiDAR Sensors: A Worldwide Bibliometric Analysis

Aguilar,

Rodríguez,

Aguilar

et al. 2024

Sensors

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“…Lidars have also been deployed on non-sun-synchronous orbits. Examples include the Cloud-Aerosol Transport System (CATS;active between 2015Yorks et al, 2016), the Global Ecosystem Dynamics Investigation (GEDI; active since 2018; Tang et al, 2019), or the Multi-footprint Observation Lidar and Imager (MOLI; planned for 2022; Daisuke et al, 2020), which have all been designed as host payloads for the International Space Station. The inclination of the Station's orbit restricts observations to latitudes between 51.6 • N and 51.6 • S, while its non-synchronous nature makes it possible to detect diurnal cloud cycles (Noel et al, 2018) -which cannot be achieved by polar-orbiting lidar missions that operate along a fixed ground track.…”

Section: Missionmentioning

confidence: 99%

Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions

Kotarba

2022

Atmos. Meas. Tech.

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Abstract. Space profiling lidars offer a unique insight into cloud properties in Earth's atmosphere and are considered the most reliable source of total (column-integrated) cloud amount (CA), and true (geometrical) cloud top height (CTH). However, lidar-based cloud climatologies suffer from infrequent sampling: every n days, and only along the ground track. This study therefore evaluated four lidar missions, namely CALIPSO (revisit every n=16 d), EarthCARE (n=25), Aeolus (n=7), and ICESat-2 (n=91), to test the hypothesis that each mission provides accurate data on CA and CTH. CA/CTH values for a hypothetical daily revisit mission were used as reference (data simulated with Meteosat 15 min cloud observations, assumed to be a proxy for ground truth). Our results demonstrated that this hypothesis is invalid, unless individual lidar transects are averaged over an area 10×10∘ in longitude and latitude (or larger). If this is not the case, the required accuracy of 1 % (for CA) or 150 m (for CTH) cannot be met, either for a single-year annual or monthly mean, or for a >10 year climatology. A CALIPSO-focused test demonstrated that the annual mean CA estimate is very sensitive to infrequent sampling, and that this factor alone can result in 14 % or 7 % average uncertainty with 1 or 2.5∘ resolution data, respectively. Consequently, applications that use gridded lidar data should consider calculating confidence intervals, or a similar measure of uncertainty. Our results suggest that CALIPSO, and its follow-on mission EarthCARE, are very likely to produce consistent cloud records despite the difference in sampling frequency.

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“…While boreal forest AGB estimation with NASA's Ice, Cloud, and Land Elevation Satellite-2 has been made available in 2021 (Duncanson et al, 2021a(Duncanson et al, , 2021b, 1 km gridded AGB data for tropical and temperate forests are available in the year 2021 from NASA Global Ecosystem Dynamics Investigation (GEDI) mission (Dubayah et al, 2020). Upon completion of the GEDI mission in 2021, Japan Aerospace Exploration Agency's (JAXA) forthcoming Multi-footprint Observation Lidar and Imager will continue to provide the gridded AGB data (Daisuke et al, 2020). Moreover, the upcoming NASA-ISRO SAR mission in 2023 will provide global biomass datasets using L-band SAR at the temporal resolution twice every twelve days (NASA, 2021).…”

Section: Introductionmentioning

confidence: 99%

Exploring characteristics of national forest inventories for integration with global space-based forest biomass data

Nesha

Herold

Bruin

et al. 2022

Science of The Total Environment

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Progress of the ISS Based Vegetation LiDAR Mission, Moli - Japan's First Space-Based LiDAR

Cited by 6 publications

References 4 publications

Forestry Applications of Space-Borne LiDAR Sensors: A Worldwide Bibliometric Analysis

Forestry Applications of Space-Borne LiDAR Sensors: A Worldwide Bibliometric Analysis

Impact of the revisit frequency on cloud climatology for CALIPSO, EarthCARE, Aeolus, and ICESat-2 satellite lidar missions

Exploring characteristics of national forest inventories for integration with global space-based forest biomass data

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