High-accuracy three-dimensional (3D) information of global area is useful in various fields, such as global observations of canopy height, elevation and ice sheet. Especially, there are pressing needs to advance understanding of how changes in the 3D structure of terrestrial vegetation are affecting the global carbon dynamics and their implications for climate change. Thus new space based observations are needed to measure global maps of the 3D structure of vegetation. Japan Aerospace Exploration Agency has started a conceptual study of the spaceborne vegetation LiDAR called MOLI (Multi- Footprint Observation LiDAR and Imager) which will enable us to obtain high-accuracy 3D information of vegetation areas from the globe. To investigate waveforms and analysis procedure, the waveform-simulator for MOLI was developed. Comparing with previous studies about the canopy height estimation from GLAS waveforms, waveform analysis procedure in which waveforms were fitted with a sum of Gaussian functions was studied. The maximum canopy height error was divided into two components; the basic error (EB) which was not depending on terrain index (TI), which was the vertical difference between the highest and lowest elevation within a footprint, and the error depending on TI (ETI). The total error (ETotal) could be RMS of the two. We propose ETotal in which EB is 1 m and ETI is 1/3*TI as a target observation accuracy of MOLI. According to this error estimation, the observation accuracy of MOLI is 1m at a plane area (TI ≈ 0) and 3 m at slope area up to about 20 degree.
It is very important to watch the spatial distribution of vegetation biomass and changes in biomass over time,
representing invaluable information to improve present assessments and future projections of the terrestrial carbon cycle.
A space lidar is well known as a powerful remote sensing technology for measuring the canopy height accurately. This
paper describes the ISS(International Space Station)-JEM(Japanese Experimental Module)-EF(Exposed Facility) borne
vegetation lidar using a two dimensional array detector in order to reduce the root mean square error (RMSE) of tree
height due to sloped surface.
This paper describes the method and process of developing a forest echo signal simulator to be applied in “iLOVE” : Issjem
LiDAR Observation of Vegetation Environment. The goal of this study was to develop an echo signal simulation
model and to visualize the generation process of echo signals.
The simulator consists of four components: 1) terrain and features, 2) sensor configuration, 3) echo signal generation and
4) visualization. Terrain and feature data were defined to be full polygon object in 3D space. A laser beam refers to
numerous sub laser beams, with each sub laser beam featuring specific intensity based on TEM00. The time-series
intensity change of sub laser beams was based on Gaussian distribution.
At the start of the echo signal generating process, intersections between sub laser beams and target objects were
calculated. Then, echo signal of sub laser beams was calculated from the position of intersections, pulse width and
specific reflectance of target objects. Finally, an echo signal suitable for footprint size was calculated by synthesizing
echo signals of sub laser beams. Meanwhile, intersections were drawn in 3D on the surface of target objects.
The results indicated that the simulator was highly useful for understanding the relationship between the echo signal and
the structure of target objects, and also for developing algorism for forest applications.
Carbon absorption o f plant is one of the essential parameters in assessing terrestrial ecosystem functions with respect to global warning. It is however, not easy to estimate carbon absorption directly on the ground. In this study, an experiment method was designed to estimate the saturated Amax from hyperspectral data in the laboratory and in the field scale. First, we measure the relationship between biochemical concentrations and parameters of 'Blackman' photosynthetic rate model. Secondly, we measure the relationship between biochemical concentration and hyperspectral characteristics. High-resolution reflectance over a range of 333-2507 nm with resolution of about 1.5-10 nm and net Amax-photon flux density (PFD) were measured respectively by the GER 2600 and Li-6400. Also, chlorophyll a, chlorophyll b, chlorophyll a + b and nitrogen concentration were quantitative analyzed from in situ measurement of cucumber's fresh leaves that were cultivated for different biochemical concentration in a greenhouse chamber. Correlation between saturated Amax and chlorophyll a and nitrogen concentration was r2 equals 0.90, and 0.91 respectively. Chlorophyll b did not show any correlation with saturated Amax. Chlorophyll a and nitrogen concentrations were estimated by using the first derivative spectral reflectance of fresh leaf. RF' at 678.011 correlated best with chlorophyll a concentration. RF' at 732.122nm correlated best with nitrogen concentration. Finally net Amax at given PFD was estimated by the photosynthetic rate model. A correlation between the actual net Amax and the estimated net Amax was r2 equals 0.74. In this study, both chlorophyll a and nitrogen concentrations show good correlation with saturated Amax.