Spatial scaling between leaf area index maps of different resolutions

We developed algorithms for spatial scaling of leaf area index (LAI) using sub-pixel information. The study area is located near Liping County, Guizhou Province, in China. Methods for LAI spatial scaling were investigated on LAI images with 960 m resolution derived in two ways. LAI from distributed calculation (LAID) was derived using Landsat ETM+ data (30 m), and LAI from lumped calculation (LAIL) was obtained from the coarse (960 m) resolution data derived through resampling the ETM+ data. We found that lumped calculations can be considerably biased compared to the distributed (ETM+) case, suggesting that global and regional LAI maps can be biased if surface heterogeneity within the mapping resolution is ignored. Based on these results, we developed algorithms for removing the biases in lumped LAI maps using sub-pixel land cover-type information, and applied these to correct one coarse resolution LAI product which greatly improved its accuracy.     

Using GIS to Generate Spatially Balanced Random Survey Designs for Natural Resource Applications

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.     

我国旱涝空间型的马尔科夫概型分析

旱涝灾害在我国是影响最大、也最为频繁的气候灾害。本文利用马尔科夫概型分析的原理和方法，在验证了我国旱涝空间型序列具有马尔科夫性质的基础上，计算出各状态的转移概率，进而分析了旱涝空间型序列的静态和动态结构，并揭示出旱涝空间型各状态演化的优势倾向。     

Temporal limits to simulating the future spread pattern of invasive species: Buddleja davidii in Europe and New Zealand

The spread of invasive species is a major ecological and economic problem. Dynamic spread modelling is a potentially valuable tool to assist regional and central government authorities to monitor and control invasive species. To date a lack of suitable data has meant that most broad scale dispersal models have not been validated with independent datasets, and so their predictive ability and reliability has remained unscrutinised. A dynamic, stochastic dispersal model of the widely invasive plant Buddleja davidii was calibrated on European spread data and then used to project the temporal progression of B. davidii's distribution in New Zealand, starting from several different historical distributions. To assess the model's performance, we constructed an occupancy map based on the average number of simulation realisations that have a population present. The application of Receiver Operating Characteristic (ROC) curves to occupancy maps is introduced, but with specificity substituted by the proportion of available area used in a realisation. A derivative measure, the partial area under these curves when assessed through time (pAUC), is introduced and used to assess overall performance of the spread model. The model was able to attain a high level of model sensitivity, encompassing all of the known locations within the occupancy envelope. However, attempting to simulate the spread of this invasive species beyond a decade had very low model specificity. This is due to several factors, including the exponential process of spread (the further a population spreads the more sites exist from which it can spread stochastically), and the Markovian chain property of the stochastic system whereby differences between realisations compound through time. These features are seen in many reports of spread models, without being explicitly acknowledged. Our measure of pAUC through time allows a model's temporal performance and its specificity to be simultaneously assessed. While the rapid deterioration in model performance limits the utility of this type of modelling for forecasting long-term broad-scale strategic management of biological invasions, it does not necessarily limit its attractiveness for informing smaller scale and shorter term invasion management activities such as surveillance, containment and local eradication.     

Residence and place image

Data are presented for a particular population on its perception of English and Welsh local authority areas in terms of desirability for residence. The method employed permits a distinction between positive and negative judgements as well as a measure of the differing degree to which areas figure in the mind at all. It is established that the areas are seen in terms of a sharply differentiated hierarchy of preference and that there is considerable variation in the extent to which areas are “visible”. In aggregate negative judgements predominate and the most frequently expressed attitude is strong dislike. Places in the south‐west are popular as are some places in the north. London Boroughs are unpopular although in varying degrees. The most favoured place is Cornwall and the least favoured is Wolverhampton. It is argued that perceptions studied in the “direct” way used here are important to complement those employing an “oblique” method in which criteria of choice are assumed or established by social survey and then used to create a profile of preference against which places can be measured and ranked.     

Evaluating Nonpoint Pollution Policy Using a Tightly Coupled Spatial Decision Support System

Policy makers often must rely on the cumulative impact of independent actions taken by local landowners to achieve environmental goals. The connection between policy, regulation, and local action, however, is often not well understood and, thus, the impact of proposed policies may be difficult to predict. In this study we evaluate the effectiveness of alternative policy scenarios for agricultural set aside programs (e.g., the conservation reserve program administered by the United States Department of Agriculture) in reducing nonpoint pollution. Two alternative policy scenarios are developed and analyzed; one based on the erodibility index (detachment), the other sediment yield (transport). An estimate of the cumulative impact of associated land use change on nonpoint pollution is made using the AGNPS distributed parameter watershed model. This work is completed within the Cypress Creek watershed in southern Illinois. An analysis of the resulting data suggests that the most efficacious regulatory strategy for achieving nonpoint water pollution goals depends, in part, on place-specific land use patterns. This conclusion provides a solid argument for place-based regulatory strategies.     

Spatial Pattern of Ecosystem Function and Ecosystem Conservation

The spatial pattern of ecosystem function can affect ecosystem conservation. Ecosystem functions are often heterogeneous spatially due to physical and biological factors. We can influence ecosystem functions by changing the spatial patterns of the physical and biological elements of an ecosystem and regulating their combinations. The variation–position effect highlights a phenomenon resulting from the spatial pattern of ecosystem function. The effect shows that the identical variation of a factor may produce different effects on the overall situation when this variation occurs in a different spatial position. In a watershed of the Yangtze River, water retention is a primary ecosystem function. The variation–position effect for water retention capacity occurs in the watershed because of the spatial heterogeneity in vegetation, soil, and slope. The change of vegetation that occurs in a complex can affect the overall situation of water retention, and the effect can be different due to the change occurring in the position holding different vegetation-soil-slope complex. To improve the ecosystem in the watershed and to meet the social needs for the ecosystem function of water retention, a strategy called ecosystem function and spatial pattern-based forest extension was proposed to conserve forests. The implementation of the strategy enables the watershed to attain the maximum effective increase in water retention capacity.     

Geographic Analysis of Forest Health Indicators Using Spatial Scan Statistics

Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.     

Evaluating the effects of spatial monitoring policy on groundwater quality portrayal

What size sample is sufficient for spatially sampling ambient groundwater quality? Water quality data are only as spatially accurate as the geographic sampling strategies used to collect them. This research used sequential sampling and regression analysis to evaluate groundwater quality spatial sampling policy changes proposed by California's Department of Water Resources. Iterative or sequential sampling of a hypothetical groundwater basin's water quality produced data sets from sample sizes ranging from 2.8% to 95% coverage of available point sample sites. Contour maps based on these sample data sets were compared to an original (control), mapped hypothetical data set, to determine at which point map information content and pattern portrayal are not improved by increasing sample sizes. Comparing series of contour maps of ground water quality concentration is a common means of evaluating the geographic extent of groundwater quality change. Comparisons included visual inspection of contout maps and statistical tests on digital versions of these map files, including correlation and regression products. This research demonstrated that, down to about 15% sample site coverage, there is no difference between contour maps produced from the different sampling strategies and the contout map of the original data set.     

OPEN CHANNEL INTERPOLATION OF CROSS SECTIONAL PROPERTIES1

ABSTRACT: This paper confirms the use of interpolated data to refine water surface profiles. Sources of error within these computations are due to truncation error, inaccuracies in geometric data, and improper modeling. Confirmation includes the development of an equation that models the effect of data measurement error on the computed water surface profile. A review of interpolation procedures includes a proposed method based upon geometric properties.