Retrieving the Infected Area of Pine Wilt Disease-Disturbed Pine Forests from Medium-Resolution Satellite Images Using the Stochastic Radiative Transfer Theory

Pine wilt disease (PWD) is a global destructive threat to forests which has been widely spread and has caused severe tree mortality all over the world. It is important to establish an effective method for forest managers to detect the infected area in a large region. Remote sensing is a feasible tool to detect PWD, but the traditional empirical methods lack the ability to explain the signals and can hardly be extended to large scales. The studies using physically-based models either ignore the within-canopy heterogeneity or rely too much on prior knowledge. In this study, we propose an approach to retrieve PWD infected areas from medium-resolution satellite images of two phases based on the simulations of an extended stochastic radiative transfer model for forests infected by pests (SRTP). A small amount of prior knowledge was used, and a change of background soil was considered in this approach. The performance was evaluated in different study sites. The inversion method performs best in the three-dimensional model LESS simulation sample plots (R2 = 0.88, RMSE = 0.059), and the inversion accuracy decreases in the real forest sample plots. For Jiangxi masson pine stand with large coverage and serious damage, R2 = 0.57, RMSE = 0.074; and for Shandong black pine stand with sparse and a small number of single plant damage, R2 = 0.48, RMSE = 0.063. This study indicates that the SRTP model is more feasible for pest damage inversion over different regions compared with empirical methods. The stochastic radiative transfer theory provides a potential approach for future monitoring of terrestrial vegetation parameters.

Assessing the Usefulness of LiDAR for Monitoring the Structure of a Montane Forest on a Subtropical Oceanic Island

The monitoring of ecosystems and forests is an urgent requirement in the current framework of global change. It is particularly necessary on oceanic islands where their rich biodiversity is highly vulnerable, with many narrow-ranged endemic species. Quantifying and mapping forest health through key ecological variables are essential steps for management, but it will also be challenging and may require a lot of resources. Remote sensing has the potential to be a very useful tool to assess the development and conservation status of forests. We assessed the applicability of the light detection and ranging (LiDAR) on the laurel forests of La Gomera, making allometric equations for various measurements of the forest structure, linking field inventory from 2019 and 2017 LiDAR data through standard linear regressions. Decision trees and logistic regressions were also used to assess the performance of LiDAR in the recognition of young-growth and old-growth laurel forests. The obtained allometric models were a good fit in general and their predictions were in line with already known data. Likewise, decision tree and logistic regression to distinguish young-growth and old-growth forests had a similar performance in both cases, with a high to medium-high degree of accuracy. Therefore, LiDAR was revealed to be a useful tool for the monitoring of the laurel forest by the managers.

Fractal solar cell array for enhanced energy production: applying rules underlying tree shape to photovoltaics

Plants and photovoltaics share the same purpose as harvesting sunlight. Therefore, botanical studies could lead to new breakthroughs in photovoltaics. However, the basic mechanism of photosynthesis is different to semiconductor-based photovoltaics and the gap between photosynthesis and solar cells must be bridged before we can apply the botanical principles to photovoltaics. In this study, we analysed the role of the fractal structures found in plants in light harvesting based on a simplified model, rotated the structures by 90° and applied them to fractal-structured photovoltaic Si solar cell arrays. Adoption of botanically inspired fractal structures can result in solar cell arrays with omnidirectional properties, and in this case, yielded a 25% enhancement in electric energy production. The fractal structure used in this study was two-dimensional and symmetric; investigating and optimizing three-dimensional asymmetric fractal structures would further enhance the performance of photovoltaics. Furthermore, this study represents only the first step towards the development of a new type of photovoltaics based on botanical principles, and points to further aspects of botanical knowledge that could be exploited, in addition to plant fractal structures. For example, leaf anatomy, phyllotaxis and chloroplastic mechanisms could be applied to the design of new types of photovoltaics.

Evaluation of a turbid medium model to simulate light interception by walnut trees (hybrid NG38 × RA and Juglans regia) and sorghum canopies (Sorghum bicolor) at three spatial scales

Light is one of the most important components to be included in functional-structural plant models that simulate the biophysical processes, such as photosynthesis, evapotranspiration and photomorphogenesis, involved in plant growth and development. In general, in these models, light is treated using a turbid medium approach in which radiation attenuation is described by the Beer-Lambert law. In the present study, we assessed the hypothesis of leaf random dispersion in the Beer-Lambert law at the whole-canopy, horizontal-layer and local scales. We compared two calculation methods of radiation attenuation: a 3D turbid medium model using the Beer-Lambert law and the other based on a projective method. The two models were compared by applying the calculations to two walnut trees and two sorghum canopies, which have contrasting structural characteristics. The structures of these canopies were measured in 3D to take into account the arrangement and orientation features of the plant elements. The assumptions made by the Beer-Lambert law allowed adequate simulation of light interception in a structure with little overlapping at the horizontal-layer and whole-canopy scales. At the local scale, discrepancies between the turbid medium model and the model based on a virtual plant were reduced with an adequate choice of structural parameters, such as the leaf inclination distribution function.

On the extinction of radiation by a homogeneous but spatially correlated random medium

Exponential extinction of incoherent radiation intensity in a random medium (sometimes referred to as the Beer-Lambert law) arises early in the development of several branches of science and underlies much of radiative transfer theory and propagation in turbid media with applications in astronomy, atmospheric science, and oceanography. We adopt a stochastic approach to exponential extinction and connect it to the underlying Poisson statistics of extinction events. We then show that when a dilute random medium is statistically homogeneous but spatially correlated, the attenuation of incoherent radiation with depth is often slower than exponential. This occurs because spatial correlations among obstacles of the medium spread out the probability distribution of photon extinction events. Therefore the probability of transmission (no extinction) is increased.