GIScience and remote sensing in natural resource and environmental research:Status quo and future perspectives

Geographic information science(GIScience)and remote sensing have long provided essential data and method-ological support for natural resource challenges and environmental problems research.With increasing advances in information technology,natural resource and environmental science research faces the dual challenges of data and computational intensiveness.Therefore,the role of remote sensing and GIScience in the fields of natural resources and environmental science in this new information era is a key concern of researchers.This study clarifies the definition and frameworks of these two disciplines and discusses their role in natural resource and environmental research.GIScience is the discipline that studies the abstract and formal expressions of the basic concepts and laws of geography,and its research framework mainly consists of geo-modeling,geo-analysis,and geo-computation.Remote sensing is a comprehensive technology that deals with the mechanisms of human ef-fects on the natural ecological environment system by observing the earth surface system.Its main areas include sensors and platforms,information processing and interpretation,and natural resource and environmental appli-cations.GIScience and remote sensing provide data and methodological support for resource and environmental science research.They play essential roles in promoting the development of resource and environmental science and other related technologies.This paper provides forecasts of ten future directions for GIScience and eight future directions for remote sensing,which aim to solve issues related to natural resources and the environment.

Soil property mapping by combining spatial distance information into the Soil Land Inference Model(SoLIM)

The Soil Land Inference Model(SoLIM) was primarily proposed by Zhu et al.(Zhu A X, Band L, Vertessy R, Dutton B. 1997. Derivation of soil properties using a soil land inference model(SoLIM). Soil Sci Soc Am J. 61: 523–533.) and was based on the Third Law of Geography. Based on the assumption that the soil property value at a location of interest will be more similar to that of a given soil sample when the environmental condition at the location of interest is more similar to that at the location from which the sample was taken, SoLIM estimates the soil property value of the location of interest using the soil property values of known samples weighted by the similarity between those samples and the location of interest in terms of an attribute domain of environmental conditions. However, the current SoLIM method ignores information about the spatial distances between the location of interest and those of the sample. In this study, we proposed a new method of soil property mapping, So LIM-IDW, which incorporates spatial distance information into the SoLIM method by means of inverse distance weighting(IDW). The proposed method is based on the assumption that the soil property value at a location of interest will be more similar to that of a known sample both when the environmental conditions are more similar and when the distance between the location of interest and the sample location is shorter. Our evaluation experiments on A-horizon soil organic matter mapping in two study areas with independent evaluation samples showed that the proposed SoLIM-IDW method can obtain lower prediction errors than the original SoLIM method, multiple linear regression, geographically weighted regression, and regression-kriging with the same modeling points. Future work mainly includes the determination of optimal power parameter values and the appropriate setting of the parameter under different application contexts.

Do model choice and sample ratios separately or simultaneously influence soil organic matter prediction?

This study was performed to examine the separate and simultaneous influence of predictive models’choice alongside sample ratios selection in soil organic matter(SOM).The research was carried out in northern Morocco,characterized by relatively cold weather and diverse geological conditions.The dataset herein used accounted for 1591 soil samples,which were randomly split into the following ratios:10%(∼150 sample ratio),20%(∼250 sample ratio),35%(∼450 sample ratio),50%(∼600 sample ratio)and 95%(∼1200 sample ratio).Models herein involved were ordinary kriging(OK),regression kriging(RK),multiple linear regression(MLR),random forest(RF),quantile regression forest(QRF),Gaussian process regression(GPR)and an ensemble model.The findings in the study showed that the accuracy of SOM prediction is sensitive to both predictive models and sample ratios.OK combined with 95%sample ratio performed equally to RF in conjunction with all the sample ratios,as the latter did not show much sensitivity to sample ratios.ANOVA results revealed that RF with a∼10%sample ratio could also be optimum for predicting SOM in the study area.In conclusion,the findings herein reported could be instrumental for producing cost-effective detailed and accurate spatial estimation of SOM in other sites.Furthermore,they could serve as a baseline study for future research in the region or elsewhere.Therefore,we recommend conducting series of simulation of all possible combinations between various predictive models and sample ratios as a preliminary step in soil organic matter prediction.

Real-time observation of frequency Bloch oscillations with fibre loop modulation

Bloch oscillations(BOs)were initially predicted for electrons in a solid lattice to which a static electric field is applied.The observation of BOs in solids remains challenging due to the collision scattering and barrier tunnelling of electrons.Nevertheless,analogies of electron BOs for photons,acoustic phonons and cold atoms have been experimentally demonstrated in various lattice systems.Recently,BOs in the frequency dimension have been proposed and studied by using an optical micro-resonator,which provides a unique approach to controlling the light frequency.However,the finite resonator lifetime and intrinsic loss hinder the effect from being observed practically.Here,we experimentally demonstrate BOs in a synthetic frequency lattice by employing a fibre-loop circuit with detuned phase modulation.We show that a detuning between the modulation period and the fibre-loop roundtrip time acts as an effective vector potential and hence a constant effective force that can yield BOs in the modulation-induced frequency lattices.With a dispersive Fourier transformation,the pulse spectrum can be mapped into the time dimension,and its transient evolution can be precisely measured.This study offers a promising approach to realising BOs in synthetic dimensions and may find applications in frequency manipulations in optical fibre communication systems.