Understanding and diagnosing plant responses to stress will benefit greatly from three-dimensional (3D) measurement and analysis of plant properties because plant responses are strongly related to their 3D structures. Light detection and ranging (lidar) has recently emerged as a powerful tool for direct 3D measurement of plant structure. Here the use of 3D lidar imaging to estimate plant properties such as canopy height, canopy structure, carbon stock, and species is demonstrated, and plant growth and shape responses are assessed by reviewing the development of lidar systems and their applications from the leaf level to canopy remote sensing. In addition, the recent creation of accurate 3D lidar images combined with natural colour, chlorophyll fluorescence, photochemical reflectance index, and leaf temperature images is demonstrated, thereby providing information on responses of pigments, photosynthesis, transpiration, stomatal opening, and shape to environmental stresses; these data can be integrated with 3D images of the plants using computer graphics techniques. Future lidar applications that provide more accurate dynamic estimation of various plant properties should improve our understanding of plant responses to stress and of interactions between plants and their environment. Moreover, combining 3D lidar with other passive and active imaging techniques will potentially improve the accuracy of airborne and satellite remote sensing, and make it possible to analyse 3D information on ecophysiological responses and levels of various substances in agricultural and ecological applications and in observations of the global biosphere.

The color of crop leaves is closely correlated with nitrogen (N) status and can be quantified easily with a digital still color camera and image processing software. The establishment of the relationship between image color indices and N status under natural light is important for crop monitoring and N diagnosis in the field. In our study, a digital still color camera was used to take pictures of the canopies of 6 rice (Oryza sativa L.) cultivars with N treatments ranging from 0 to 315 kg N ha-1 in the field under sunny and overcast conditions in 2010 and 2011, respectively. Significant correlations were observed between SPAD readings, leaf N concentration (LNC) and 13 image color indices calculated from digital camera images using three color models: RGB, widely used additive color model; HSV, a cylindrical-coordinate similar to the human perception of colors; and the L * a * b * system of the International Commission on Illumination. Among these color indices, the index b * , which represents the visual perception of yellow-blue chroma, has the closest linear relationship with SPAD reading and LNC. However, the relationships between LNC and color indices were affected by the developmental phase. Linear regression models were used to predict LNC and SPAD from color indices and phasic development. After that, the models were validated with independent data. Generally, acceptable performance and prediction were found between the color index b * , SPAD reading and LNC with different cultivars and sampling dates under different natural light conditions. Our study showed that digital color image analysis could be a simple method of assessing rice N status under natural light conditions for different cultivars and different developmental stages.

Factors that contribute to the accuracy of estimating woody canopy's leaf area density (LAD) using 3D portable lidar imaging were investigated. The 3D point cloud data for a Japanese zelkova canopy [Zelkova serrata (Thunberg) Makino] were collected using a portable scanning lidar from several points established on the ground and at 10 m above the ground. The LAD profiles were computed using voxel-based canopy profiling (VCP). The best LAD results [a root-mean-square error (RMSE) of 0.21 m² m⁻³] for the measurement plot (corresponding to an absolute LAI error of 9.5%) were obtained by compositing the ground-level and 10 m measurements. The factors that most strongly affected estimation accuracy included the presence of non-photosynthetic tissues, distribution of leaf inclination angles, number (N) of incident laser beams in each region within the canopy, and G(θ_m) (the mean projection of a unit leaf area on a plane perpendicular to the direction of the laser beam at the measurement zenith angle of θ_m). The influences of non-photosynthetic tissues and leaf inclination angle on the estimates amounted to 4.2–32.7% and 7.2–94.2%, respectively. The RMSE of the LAD estimations was expressed using a function of N and G(θ_m).

In the present study, an attempt was made to produce a precise 3D image of a tomato canopy using a portable high-resolution scanning lidar. The tomato canopy was scanned by the lidar from three positions surrounding it. Through the scanning, the point cloud data of the canopy were obtained and they were co-registered. Then, points corresponding to leaves were extracted and converted into polygon images. From the polygon images, leaf areas were accurately estimated with a mean absolute percent error of 4.6%. Vertical profile of leaf area density (LAD) and leaf area index (LAI) could be also estimated by summing up each leaf area derived from the polygon images. Leaf inclination angle could be also estimated from the 3-D polygon image. It was shown that leaf inclination angles had different values at each part of a leaf.

A new imaging system capable of simultaneously measuring stomatal conductance and fluorescence parameters, non-photochemical quenching (NPQ) and photochemical yield of photosystem II (Φ_PSII), in intact leaves under aerobic conditions by both thermal imaging and chlorophyll fluorescence imaging was developed. Changes in distributions of stomatal conductance and fluorescence parameters across Phaseolus vulgaris L. leaves induced by abscisic acid treatment were analyzed. A decrease in stomatal conductance expanded in all directions from the treatment site, then mainly spread along the lateral vein toward the leaf edge, depending on the ABA concentration gradient and the transpiration stream. The relationships between stomatal conductance and fluorescence parameters depended on the actinic light intensity, i.e. NPQ was greater and Φ_PSII was lower at high light intensity. The fluorescence parameters did not change, regardless of stomatal closure levels at a photosynthetically active photon flux (PPF) of 270 µmol m^–2 s^–1; however, they drastically changed at PPF values of 350 and 700 µmol m^–2 s^–1, when the total stomatal conductance decreased to less than 80 and 200 mmol m^–2 s^–1, respectively. This study has, for the first time, quantitatively analyzed relationships between spatiotemporal variations in stomatal conductance and fluorescence parameters in intact leaves under aerobic conditions.