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.

A novel method to develop quantitative structure-property relationship (QSPR) models of organic contaminants was proposed based on genetic algorithm (GA) and support vector machine (SVM). GA was used to perform the variable selection and SVM was used to construct QSPR models. In this study, GA-SVM was applied to develop the QSPR model for aqueous solubility (S_w, mol·L^-1) of polycyclic aromatic hydrocarbons (PAHs). The R² (0.98) of the model developed by GA-SVM indicated a good predictive precision for lg S_w values of PAHs. According to leave-one-out (LOO) cross validation, the results of GA-SVM were compared with those of genetic algorithm-radial based function neural network (GA-RBFNN) and genetic algorithm-partial least-squares (GA-PLS) regression. The comparisons showed that the cross validation correlation coefficient ((QLOO2) = 0.92) and root mean square error of LOO cross validation (RMSE_LOO = 0.49) of GA-SVM were the highest and lowest, respectively, which illustrated that GA-SVM was more suitable to develop QSPR model for the lg S_w values of PAHs than GA-RBFNN and GA-PLS.

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: Carex muliensis marsh, Stipa and Kobresia meadow, Carex-dominated forb meadow and Sibiraea angustata scrub. Principal-components analysis (PCA) was used to determine the relationships between modern pollen and vegetation and environmental variables. The results show that the pollen assemblages of surface moss samples generally reflect the features of the modern vegetation, basically similar in the vegetation types and the dominant genera; however, they don’t show a very clear distinction between different communities. Our results also demonstrate that pollen representation of different families or genus varied. Some tree taxa, such as Pinus and Betula, and herb types, such as Artemisia are over-represented, while Asteraceae, Ranunculaceae and Cyperaceae are moderately represented, and Poaceae and Rosaceae are usually under-represented in our study region. PCA results indicate that the distribution of vegetation in the Zoige Basin is mainly controlled by precipitation and altitude.

This paper reviews the modern process studies for four types of proxies (tree-ring, biologic indicators, physical proxies and geochemical indexes) in arid north-western China for the purpose of better understanding their environmental indication for reconstructing paleoenvironment and paleoclimate. These proxies are affected by many variables in some cases, such as temperature, precipitation, pH, topography etc., and their indicative meanings may become complex sometimes. For this reason, multiple proxies might be used to complement each other if conditions permit. Moreover, potential differences of each proxy should be taken into consideration when they were used. This paper indicates the application of each modern process proxy and their advantages and disadvantages, so as to give some references to fossil data interpretation and environment reconstruction in arid north-western China.

Using unsupervised classification, visual interpretation, slope mask with the aid of ArcGIS and ERDAS, we analyzed the peatland area change in the Zoige Basin, eastern Tibetan Plateau, during last two decades on the basis of 12 Landsat-TM images. The results showed that the peatland area decreased seriously from 4143.39 to 3407.29 km² between early 1990s and 2000 and increased slightly to 3588.71 km² in 2009. Though peatland area change is positively correlated with the climate trend, the correlation is not very significant. Instead, in considering the population increase, stock development and government policy, we suggest that human activity is likely the more important factor that caus the peatland area variations.

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.

Preservation of the amount and quality of groundwater resources is an important issue around the world. Changes in groundwater levels need to be monitored in efforts to preserve groundwater. This study investigates suitable methods to characterize changes in the groundwater level and determine the factors involved. The area of Kumamoto, a city in central Kyushu, south-west Japan, was selected to demonstrate the usefulness of the methods because this area is one of the richest in Japan in terms of groundwater resources and takes all its water from groundwater. Data of the groundwater level recorded at 69 wells from 1979 to 2007 were used in geostatistical and correlogram analyses. First, strong correlation between the topography and groundwater level was identified. Incorporating this correlation into spatial modeling of the groundwater level, co-kriging was demonstrated to be more accurate than ordinary kriging. The co-kriging results clarified the hydraulic characteristics of the Kumamoto area; the patterns of shallow and deep groundwater levels were agreeable generally, and the general trends of their annual average levels were similar regardless of precipitation. Another important feature was that the correlograms for the precipitation amount and groundwater level had a constant shape and changed smoothly with a change in lag time regardless of the precipitation only in the area of Togawa lava. These characteristics are probably due to the connections between shallow and deep aquifers and the high permeability of Togawa lava.

High concentrations of total suspended solids (TSS) in coastal and bay areas strongly affect water quality and aquatic ecosystems. Frequent monitoring of spatio-temporal changes of TSS distribution in such areas is indispensable for understanding sediment fluxes and water cycles, and to preserve ecosystem health. This study aimed to identify appropriate and sufficient tools for assessing changes in TSS distribution in Tien Yen Bay in Northern Vietnam, a typical closed bay, which was selected as the study area because of its rich biodiversity. Initially, a physical based model using the reflectance at the sea surface was developed for estimating TSS concentrations from satellite image data, and a model with an exponential function was identified as suitable for the estimation. This model was fitted appropriately to provide a relationship between reflectance from the MODIS/Terra band 1 (visible red) after the atmospheric correction and the in situ TSS concentrations at 40 points. Ordinary kriging was then shown to be effective in improving the spatial resolution of the MODIS/Terra image-based estimation of the TSS concentration at a 250 m interval, because it could detect TSS variation in detail, in particular in the local estuaries. TSS distributions derived from 12 MODIS/Terra images from November 2009 to October 2010 clarified seasonal changes in TSS during one year. TSS concentrations were high during summer and lower during fall and winter. Such trends were conformable with the hydrodynamics in Tien Yen Bay. Consequently, the proposed method was more effective for TSS estimation than traditional methods using satellite image data only.

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 (LLII) was established in this paper to evaluate the urban livability, while the linear weighted sum was applied as the assessment model. After analyzing the situations of the four cities during 2000–2009, it was indicated that the LLIIs of Beijing, New York City, Greater London, and Tokyo-to were respectively 38.76, 52.93, 50.95, and 40.65 in 2000. By comparison, the LLIIs in 2009 were 38.96, 59.23, 69.24 and 52.15, respectively. Further analysis showed that a big gap exists between the environmental quality of Beijing and those of three global cities and the performance of social development for Beijing declined in the last decade. To accelerate the transformation of Beijing to a global city, much more attention should be paid to improve the environmental quality, especially the atmospheric quality and water quality.