The success of precision agriculture (PA) depends strongly upon an efficient and accurate method for in-field soil property determination. This information is critical for farmers to calculate the proper amount of inputs for best crop performance and least environmental effect. Grid sampling, as a traditional way to explore in-field soil variation, is no longer considered appropriate since it is labor intensive, time consuming and lacks spatial exhaustiveness. Remote sensing (RS) provides a new tool for PA information gathering and has advantages of low cost, rapidity, and relatively high spatial resolution. Great progress has been made in utilizing RS for in-field soil property determination. In this article, recent publications on the subject of RS of soil properties in PA are reviewed. It was found that a large array of agriculturally-important soil properties (including textures, organic and inorganic carbon content, macro- and micro-nutrients, moisture content, cation exchange capacity, electrical conductivity, pH, and iron) were quantified with RS successfully to the various extents. The applications varied from laboratory-analysis of soil samples with a bench-top spectrometer to field-scale soil mapping with satellite hyper-spectral imagery. The visible and near-infrared regions are most commonly used to infer soil properties, with the ultraviolet, mid-infrared, and thermal-infrared regions have been used occasionally. In terms of data analysis, MLR, PCR, and PLSR are three techniques most widely used. Limitations and possibilities of using RS for agricultural soil property characterization were also identified in this article.
In precision agriculture regression has been used widely to quantify the relationship between soil attributes and other environmental variables. However, spatial correlation existing in soil samples usually violates a basic assumption of regression: sample independence. In this study, a regression-kriging method was attempted in relating soil properties to the remote sensing image of a cotton field near Vance, Mississippi, USA. The regression-kriging model was developed and tested by using 273 soil samples collected from the field. The result showed that by properly incorporating the spatial correlation information of regression residuals, the regression-kriging model generally achieved higher prediction accuracy than the stepwise multiple linear regression model. Most strikingly, a 50% increase in prediction accuracy was shown in soil sodium concentration. Potential usages of regression-kriging in future precision agriculture applications include real-time soil sensor development and digital soil mapping.
We use a data set of 23 surface pollen samples from moss polsters in the Zoige Basin to explore the relationship between modern pollen assemblages and contemporary vegetation patterns. The surface pollen samples spanned four types of plant communities:
In this paper, a simple analysis is conducted for the purpose of addressing a simple but fundamental question, i.e., does the world have the capability in sciences, economics and governance to deal with the global climate change today and what should we do? By pointing out that although understanding of multidimensionality and nonlinearity of global changes from both natural and social sciences has been advanced significantly, it is extremely difficult, if not impossible, to find a single solution for global climate change because of the multi-dimensionality of social components and the nonlinearity of natural elements inherent in the global climate systems.
Ecological compensation is an important means to maintain the sustainability and stability of ecosystem services. The property rights analysis of ecosystem services is indispensable when we implement ecological compensation. In this paper, ecosystem services are evaluated via spatial transferring and property rights analysis. Take the Millennium Ecosystem Assessment (MA) as an example, we attempt to classify the spatial structure of 31 categories of ecosystem services into four dimensions, i.e., local, regional, national and global ones, and divide the property rights structure into three types, i.e., private property rights, common property rights and state-owned property rights. Through the case study of forestry, farming industry, drainage area, development of mineral resources, nature reserves, functional areas, agricultural land expropriation, and international cooperation on ecological compensation, the feasible ecological compensation mechanism is illustrated under the spatial structure and property rights structure of the concerned ecosystem services. For private property rights, the ecological compensation mode mainly depends on the market mechanism. If the initial common property rights are “hidden,” the implementation of ecological compensation mainly relies on the quota market transactions and the state investment under the state-owned property rights, and the fairness of property rights is thereby guaranteed through central administration.
This article summarizes the change of land use in 1986–2008 through data analysis on land use/land cover in Xishuangbanna Region, Yunnan Province, China. The major driving forces of land use change are identified by the gray incidence analysis method. The results shows that the area ratio of forestland in Xishuangbanna Region decreased from 57.62% to 42.87% in the studied period, The ratio of plantation and shrub land increased from 4.77%, 15.10% to 13.92%, 23.87%, respectively, The ratio of crop land increased from 4.77% in 1986 to 5.85% in 1999, and then dropped to 4.99% in 2008. The driving force analysis shows that population density, the average annual temperature, grain output and economic density are among the major driving forces causing land use/land cover change (LUCC) in Xishuangbanna Region.
The rapid growth of agro-ecosystem has been the focus of “New Rural Construction” in China due to intensive energy consumption and environmental pollution in rural areas. As a kind of renewable energy, biogas is helpful for new energy development and plays an important role in the sustainable development of agro-ecosystem in China. To evaluate the effects of biogas on agro-ecosystem from a systematic angle, we discussed the status quo of household biogas and identified its main factors that may have impacts on agro-ecosystem. An indicator framework covering environmental, social and economic aspects was established to quantify the impacts exerted by biogas project on agro-ecosystem. A case study of Gongcheng was then conducted to evaluate the combined impact of biogas project using the proposed indicator framework. Results showed that there was a notable positive effect brought by the application of biogas, and the integrated benefit has been significantly improved by 60.36%, implying that biogas as a substitute energy source can promote the sustainable level of rural areas.
A so-called global city that plays an important role in regional and global economic, political and cultural development should perform well in terms of its livability. The livability level of Beijing was compared with those of three acknowledged global cities, i.e., New York City, Greater London, and Tokyo-to to clarify whether Beijing has great potential to grow into a global city. From the aspects of social development, living standard and environmental quality, the livable level integrated index (