Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.     

A land-use mix allocation model considering adjacency,intensity, and proximity

ABSTRACT

Land-Use Mix (LUM) refers to the strategy of integrating complementary functions within a building or area. While LUM has become a dominant approach in urban planning, its actual benefits and vision for spatial planning remain unclear. To clarify this issue, this study discerns the spatial features of land-use patterns depending on the compatibilities among land-use categories. Accordingly, this study introduces three LUM measures – adjacency, intensity, and proximity – to identify differences in the spatial distribution of land-use categories. Based on these measures, a land-use allocation model is developed to specify spatial patterns satisfying the given compatibilities. This model is tested by applying the concept of the neighborhood unit on a case study of normative land-use patterns subject to specified compatibilities. The results describe spatial features of four compatibility sets, including a set exhibiting a compatibility conflict between the same land-use pair and LUM measures when, for example, a given land-use pair is compatible in terms of intensity but incompatible in terms of proximity. Understanding the spatial features of a normative land-use pattern that satisfies various possible compatibilities will facilitate the incorporation of the LUM approach into local planning guidance and zoning ordinances.     

Spatial measurements of stream baseflow,a relevant method for aquifer characterization and permeability evaluation. Application to a hard‐rock aquifer,the Oman ophiolite

The structure, functioning and hydrodynamic properties of aquifers can be determined from an analysis of the spatial variability of baseflow in the streams with which they are associated. Such analyses are based on simple low‐cost measurements. Through interpreting the hydrological profiles (Q = f(A)) it is possible to locate the aquifer(s) linked to the stream network and to determine the type of interrelated flow, i.e. whether the stream drains or feeds the aquifer. Using an analytical solution developed for situations with a positive linear relationship, i.e. where the baseflow increases linearly with increasing catchment size, it is also possible to estimate the permeability of the aquifer(s) concerned at catchment scale. Applied to the hard‐rock aquifers of the Oman ophiolite, this method shows that the ‘gabbro’ aquifer is more permeable than the ‘peridotite’ aquifer. As a consequence the streams drain the peridotites and ‘leak’ into the gabbro. The hydrological profiles within the peridotite are linear and positive, and indicate homogeneity in the hydrodynamic properties of these formations at the kilometre scale. The permeability of the peridotite is estimated at 5 · 10^?7 to 5 · 10^?8 m/s. Copyright © 2004 John Wiley & Sons, Ltd.     

Pollen-based reconstructions of Holocene vegetation and climatic change of Tibetan Plateau

A synthesis of Holocene pollen records from the Tibetan Plateau shows the history of vegetation and climatic changes during the Holocene. Palynological evidences from 24 cores/sections have been compiled and show that the vegetation shifted from subalpine/alpine conifer forest to subalpine/alpine evergreen sclerophyllous forest in the southeastern part of the plateau; from alpine steppe to alpine desert in the central, western and northern part; and from alpine meadow to alpine steppe in the eastern and southern plateau regions during the Holocene. These records show that increases in precipitation began about 9 ka from the southeast, and a wide ranging level of increased humidity developed over the entire of the plateau around 8-7 ka, followed by aridity from 6 ka and a continuous drying over the plateau after 4-3 ka. The changes in Holocene climates of the plateau can be interpreted qualitatively as a response to orbital forcing and its secondary effects on the Indian Monsoon which expanded northwards     

空间数据仓库的认知过程

从理论上探讨了空间数据仓库的认知过程．主要是十一个层次的世界模型通过十个算子转换的过程，对十一个层次世界及十个算子概念进行了较详细地讨论，并用代数系统对其进行了定义。     

The FAST/SKA site selection in Guizhou province

Many karst depressions with diameters of 300 m to 500 m, suitable for constructing Arecibo-style radio telescopes, were identified in the south of Guizhou Province by Remote Sensing (RS) and Geographic Information System (GIS) technologies together with field investigations. Fundamental topography and landform databases were established for 391candidate depressions, and using GIS the3-dimensional images of depressions, at a scale of 1:10000, were then simulated to fit a spherical antenna. This revised version was published online in July 2006 with corrections to the Cover Date.     

FARMLAND AND URBAN AREA DYNAMICS MONITORING INCHINA USING REMOTE SENSING AND SPATIALSTATISTICS METHODOLOGY

1 INTRODUCTIONGlobal change research involves much geo-objectsand geo-process, such as climate and environmentalchange, substance and energy cycling, land-use/land-cover change (LUCC), interactivity between human and nature, etc.. So it need cooperation frommany research communities including international research programs groups such as IGBP (InternationalGeosphere-Biosphere Programme IPCC (Intergovemmental Panel on Climate Change), IHDP (InternationalHuman Dimension Program o…     

A stepwise method for determining the number of component distributions in a mixture

This paper considers the problem of estimatingm, the number of components in a finite mixture of distributions from a parametric family. A step-up procedure using the bootstrap method is proposed. Some properties of the procedure are illustrated with simulation studies. An example of the method, applied to orientation of beach clasts, is given.