Jia Sun

TL;DR: In this article, the authors focused on clarifying the major factors influencing the ecosystem services (ESs) in different regions of China, which will be key to manage ecosystems sustainably.

TL;DR: A novel technique, i.e., hyperspectral LIDAR (HL) which worked based on wide spectrum emission and a 32-channel detector was introduced, and its potential in vegetation detection was evaluated, and it was shown that the reflectance intensity of the selected characteristic wavelengths of HL system has high correlation with different nitrogen contents levels of rice.

TL;DR: It is demonstrated that HSL provided the best indicator for predicting rice LNC, yielding a coefficient of determination (R2) of 0.74 and a root mean square error of 2.80 mg/g with a support vector machine, similar to the performance of ASD.

TL;DR: In this paper, a five-wavelength combination was established to estimate leaf chlorophyll and water contents: 680, 716, 1104, 1882 and 1920nm, and the consistency of the selected wavelengths selected were tested by running different versions of the PROSPECT model.

TL;DR: BPNN provided generally satisfactory performance in estimating rice LNC using the three kinds of passive and active reflectance spectra, and support vector regression of different types/kernels/parameter values.