Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods

The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.

Optimised Spatial Sampling Scheme for Soil Electriclal Conductivity Based on Variance Quad-Tree (VQT) Method

The acquisition of precise soil data representative of the entire survey area, is a critical issue for many treatments such as irrigation or fertilization in precision agriculture. The aim of this study was to investigate the spatial variability of soil bulk electrical conductivity （ECb） in a coastal saline field and design an optimized spatial sampling scheme of ECb based on a sampling design algorithm, the variance quad-tree （VQT） method. Soil ECb data were collected from the field at 20 m interval in a regular grid scheme. The smooth contour map of the whole field was obtained by ordinary kriging interpolation, VQT algorithm was then used to split the smooth contour map into strata of different number desired, the sampling locations can be selected within each stratum in subsequent sampling. The result indicated that the probability of choosing representative sampling sites was increased significantly by using VQT method with the sampling number being greatly reduced compared to grid sampling design while retaining the same prediction accuracy. The advantage of the VQT method is that this scheme samples sparsely in fields where the spatial variability is relatively uniform and more intensive where the variability is large. Thus the sampling efficiency can be improved, hence facilitate an assessment methodology that can be applied in a rapid, practical and cost-effective manner.

Changes of forest land use and ecosystem service values along Lao-Chinese border:A case study of Luang Namtha Province,Lao PDR

Forest cover and land use change directly impact biological diversity worldwide, contribute to climate change and affect the ability of biological systems to support human needs by altering ecosystem services. Given the forest land use characteristics and ecosystem types in Luang Namtha Province, Lao PDR, the forest cover and land cover category of Luang Namtha Province were divided into six classes, i.e., current forest （CF）, potential forest （PF）, other wooded areas （OW）, permanent agricultural land （PA）, other non-forest areas （NF） and water （W）. In first instance, earlier geographic information data （GIS data） of forest cover and land use during 1992 and 2002 was obtained from the Ministry of Agriculture and Forestry （MAF）, Lao PDR. Two steps of forest land use change assessment were conducted by the MAF, i.e., plot sampling on satellite image maps （SIMs） to detect the changes of forest cover and land use during 1992 and 2002 for the entire Luang Namtha Province and field verification in order to identify causes of the changes. Secondly, dynamic information of the forest land cover changes during this ten-year period was calculated by means of map algebra in ArcGIS 9.2. Thirdly, based on the theory of ecosystem service functions and the service function values of different global ecosystems, the value of the six forest cover and land use categories in the province was obtained. Finally, ecological environmental effects, produced by the regional land cover changes over the study period, were calculated.

“社会—空间”关系视角下的国际居住空间分异研究

日益加剧的居住空间分异是中国城市面临的重要现实问题。以“社会—空间”关系为理论视角,梳理国际居住空间分异研究进展,总结居住空间分异的形成机制,以期为分析及应对中国居住空间分异问题提供参考。研究发现,20世纪初期以来,居住空间分异研究的主流理论——传统芝加哥学派将空间视为社会的产物,认为具有不同社会经济特征的群体在地理空间中的差异化分布是居住空间分异的核心特征,空间分化作为社会分化的空间表征而出现。20世纪80年代出现的邻里效应理论和20世纪90年代提出的领土污名化理论则分别关注空间分化塑造的社会隔离效应和主观隔离效应,认为社会分化也是居住空间分异的核心特征,强调空间具有塑造社会的能动性。已有研究证明,居住空间分异的形成机制存在“社会—空间”互嵌关系。为实现以人为本、公平共享的中国新型城镇化,未来中国居住空间分异研究应更多地关注空间分化的社会效应分析,探索基于社会和空间互嵌关系的居住空间分异理论解释和应对策略。

喀斯特地区城镇化质量与土地利用系统健康协同演化关系研究

在城镇化过程中,城镇化质量与土地利用系统健康存在着相互联系、相互影响的耦合关系,只有当两者协调发展,才能进一步促进城镇化的协调发展。以喀斯特地区贵阳市为研究对象,在构建了城镇化质量和土地利用系统健康的评价指标体系后,分别计算了两者的综合指数,并采用耦合度模型与耦合协调模型以及剪刀差方法对两者的协调关系进行分析。研究表明:(1)城镇化质量和土地利用系统健康的综合指数大体上呈逐年上升的趋势,其中土地利用系统健康先后经历了从亚健康到初级健康再到中级健康的状态;(2)城镇化质量与土地利用系统健康的耦合度在研究期内一直处于拮抗水平,耦合协调水平先后经历了从濒临失调到勉强协调再到初级协调的状态;(3)城镇化质量与土地利用系统健康演化速率的剪刀差较为稳定,波动趋势比较平缓,贵阳市城镇化质量与土地利用系统健康这两个系统发展演化速率的差异基本维持在稳定水平。在未来应当采用促进城镇化质量与土地利用系统健康双向提升的优化路径以提高两个系统之间的耦合关系。