利用多源数据估算黑河流域总初级生产力

总初级生产力(GPP)决定了进入陆地生态系统的初始物质与能量,但由MODIS GPP产品获取的GPP在地表覆盖复杂的黑河流域却不足以准确的反映生态系统物质与能量的分布。因此,利用MODIS影像数据、ASTER GDEM数据、30 m分辨率土地利用覆被数据和中国区域地面气象要素驱动数据,驱动VPM模型模拟黑河流域2015年5～10月的总初级生产力,并据此揭示黑河流域GPP在生长季的时空格局,时间分辨率为8 d,空间分辨率为500 m。研究结果表明:VPM模型估算结果的精度高于MODIS GPP产品,判定系数增长了45.5%,总均方根误差降低了57.0%;黑河流域生长季累积GPP总体呈现出中游最高、上游其次、下游最低的显著空间分布梯度格局;全境与局部有植被覆盖区域的日GPP均呈先增加后减少倒U型变化规律,且前者在7月下旬达到最高值;植被覆盖率极低的地表区域生长季内的日GPP在基本稳定中上下波动,稳定值处于1 gC·m^-2·d^-1附近。     

Using inquiry to enhance the learning and appreciation of geography

Abstract

To meet national geography standards, instructional materials using issues-based inquiry are needed. This paper reports on national classroom trials of drafts of Geographic Inquiry into Global Issues (GIGI), a set of inquiry modules for secondary geography. The analysis focuses on three modules about environmental issues, tried by 480 students in 18 schools. Students made significant gains in learning the modules' cognitive and skills objectives, but they showed no change in interest toward studying geography or these environmental issues. Student comments about the modules underscored the necessity of connecting classroom materials about global issues more closely to local experiences. These findings support current models in environmental education. Reflecting this analysis, the published modules now include activities emphasizing inquiry into local issues, to complement the study of global environmental problems. The improved GIGI materials can better meet the goals of both geography and environmental education.     

Terrain data compression using wavelet-tiled pyramids for online 3D terrain visualization

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applications based on multiresolution tiled pyramids. A comparative performance evaluation with the currently existing techniques shows that the proposed scheme obtains a better compression ratio of the terrain data, reducing the storage space and transmission bandwidth required, and achieving a better visual quality of the virtual terrain reconstructed after data decompression.     

Elementary forms for land surface segmentation: The theoretical basis of terrain analysis and geomorphological mapping

Land surface morphology is fundamental to geomorphological mapping and many GIS applications. Review and comparison of various approaches to segmentation of the land surface reveals common features, and permits development of a broad theoretical basis for segmentation and for characterization of segments and their boundaries. Within the context of defining landform units that maximise internal homogeneity and external differences, this paper introduces the concept of elementary forms (segments, units) defined by constant values of fundamental morphometric properties and limited by discontinuities of the properties. The basic system of form-defining properties represents altitude and its derivatives, constant values of which provide elementary forms with various types of homogeneity. Every geometric type of elementary form can be characterized by a defining function, which is a specific case of the general polynomial fitted function. Various types of boundary discontinuity and their connections and transformations into other types of morphological unit boundaries are analysed.The wealth of types of elementary forms and their boundaries is potentially unbounded and thus is sufficient to cover the real variety of landforms. Elementary forms in the basic set proposed here have clear potential for genetic and dynamic interpretation. A brief worked example documents the possibility of analytical computation of various models of ideal elementary forms for particular segments of landform. Ideal elementary forms can be considered as attractors, to which the affinity of surface segments can be measured by multivariate statistical methods. The use of the concept of elementary forms in landscape segmentation is promising and it could be adapted for elementary segmentation of various other spatial fields.     

Using auxiliary information to adjust fuzzy membership functions for improved mapping of soil qualities

Agronomic soil management and decision-making frequently requires the joint classification of soil variables. Fuzzy set theory is often used to accomplish this task. This paper addresses the issues of objectively defining fuzzy membership functions (FMF) and reducing classification uncertainty with hedge operators. As an example, soil in North-east Thailand was classified according to its inherent potential to support the recovery of a rice crop after a drought spell. The utility of auxiliary information not directly included in the classification was explored. A tree cover density index was employed for an objective definition of the FMF to classify soil organic matter content and plant-available potassium. Mapping units were allocated to classes having low, medium or high availability of these plant nutrients. It was shown that crisp, Boolean style classifications severely misclassify land in all but one class. Adjusted FMF decreased the uncertainty contained in thematic class maps. Single FMF values for soil organic matter and plant-available K were then jointly modelled and the soil classified as having low, medium and high potential for rice plants to recover from drought impacts. The very and more or less hedge operators were applied to increase or decrease the joint FMF values using farmer' knowledge about soil fertility. Overall classification uncertainty using FMF was decreased by 14% if the standard FMF was adjusted and the generated membership values were hedged. It was shown that adjusting FMF influenced the uncertainty components vagueness and ambiguity differently; the former increased slightly but the latter was drastically reduced.     

A parallel computing approach to viewshed analysis of large terrain data using graphics processing units

Viewshed analysis, often supported by geographic information system, is widely used in many application domains. However, as terrain data continue to become increasingly large and available at high resolutions, data-intensive viewshed analysis poses significant computational challenges. General-purpose computation on graphics processing units (GPUs) provides a promising means to address such challenges. This article describes a parallel computing approach to data-intensive viewshed analysis of large terrain data using GPUs. Our approach exploits the high-bandwidth memory of GPUs and the parallelism of massive spatial data to enable memory-intensive and computation-intensive tasks while central processing units are used to achieve efficient input/output (I/O) management. Furthermore, a two-level spatial domain decomposition strategy has been developed to mitigate a performance bottleneck caused by data transfer in the memory hierarchy of GPU-based architecture. Computational experiments were designed to evaluate computational performance of the approach. The experiments demonstrate significant performance improvement over a well-known sequential computing method, and an enhanced ability of analyzing sizable datasets that the sequential computing method cannot handle.     

GIS-based modelling of topography-induced solar radiation variability in complex terrain for data sparse region

Solar radiation not only sustains the lives on the Earth, but also creates spatial and temporal variations of hydrological ingredients, such as vegetation, soil moisture, and snow. Precise quantification of spatial solar radiation incident on the Earth's surface which accounts for the topographic modulation, especially in complex terrain, underpins the study of many catchment hydro-meteorological and hydro-ecological processes. Topography is a key parameter that affects the spatial solar radiation pattern across different scales. This article addresses the issue of modelling spatial variability of actual solar radiation caused by topography from the hydrological perspective. Models with different algorithms and different complexities, from the simple empirical equations to process-based physical approach, have been developed to parameterize and calculate the potential radiation (under clear-sky condition) and the actual radiation (under overcast cloudy condition). Based on a review of the general steps of solar radiation modelling and the corresponding models for each step, two models with easily or globally available data for spatial solar radiation modelling in complex terrain, namely, the physically parameterized, remote-sensing-oriented Heliosat-2 model and the sunshine duration-based Angström–Prescott regression model are selected and implemented in a GIS framework. The capability of both models for simulation of cloudy-sky radiation on horizontal surfaces has been verified against observed station data showing an R ² greater than 0.9. The validity of the models for modelling inclined surface is tested by comparing against each other, which has shown a satisfactory agreement and demonstrated that the simple Angström–Prescott method performed reasonably well compared with the more elaborate Heliosat-2 method. Scale sensitivity of the models and the shading effect are examined with different digital elevation model (DEM) resolutions from 30 to 500 m and reveal the existence of a threshold grid size to resolve the topography-induced spatial solar radiation variability. Spatial mapping of potential solar radiation and actual solar radiation has been demonstrated in a small catchment in Southern Germany, with a spatial difference up to 30% in winter and 5% in summer. This may lead to a significant difference for the energy-limited hydrological processes, such as snowmelt, and evapotranspiration.     

SIMPLE An inductive modelling and mapping tool for spatially-oriented data

Abstract

An inductive learning capability has been interfaced to a computerized geographical modelling package. The capabilities of the integrated system, called SIMPLE, are described. The use of the system to model and map the distribution of kangaroo populations is briefly described.     

Using rainfall-runoff modeling to interpret lake level data

Using water balance computations, the behavior of different kinds of lakes is discussed. Simple analytical expressions relating water level to hydrological conditions and lake bathymetry are given. The importance of knowing the river basin area when analyzing lake levels is stressed. A conceptual rainfall-runoff model including lake routing is used to simulate runoff and lake levels and to compute quasi-steady state conditions and long-term transient situations. It is suggested that models can be used to construct curves relating lake levels to precipitation and lake evaporation. By comparing with paleo-lake levels, the annual precipitation related to these levels can be found, provided information is available about the seasonal distribution of the precipitation.     

综合地理数据与MODIS物候特征的区域土地覆盖制图(英文)

The study developed a feasible method for large-area land cover mapping with combination of geographical data and phenological characteristics, taking Northeast China (NEC) as the study area. First, with the monthly average of precipitation and temperature datasets, the spatial clustering method was used to divide the NEC into four ecoclimate regions. For each ecoclimate region, geographical variables (annual mean precipitation and temperature, elevation, slope and aspect) were combined with phenological variables derived from the moderate resolution imaging spectroradiometer (MODIS) data (enhanced vegetation index (EVI) and land surface water index (LSWI)), which were taken as input variables of land cover classification. Decision Tree (DT) classifiers were then performed to produce land cover maps for each region. Finally, four resultant land cover maps were mosaicked for the entire NEC (NEC_MODIS), and the land use and land cover data of NEC (NEC_LULC) interpreted from Landsat-TM images was used to evaluate the NEC_MODIS and MODIS land cover product (MODIS_IGBP) in terms of areal and spatial agreement. The results showed that the phenological information derived from EVI and LSWI time series well discriminated land cover classes in NEC, and the overall accuracy was significantly improved by 5.29% with addition of geographical variables. Compared with NEC_LULC for seven aggregation classes, the area errors of NEC_MODIS were much smaller and more stable than that of MODIS_IGBP for most of classes, and the wall-to-wall spatial comparisons at pixel level indicated that NEC_MODIS agreed with NEC_LULC for 71.26% of the NEC, whereas only 62.16% for MODIS_IGBP. The good performance of NEC_MODIS demonstrates that the methodology developed in the study has great potential for timely and detailed land cover mapping in temperate and boreal regions.     

多源遥感数据在土地覆盖变化监测中的应用

基于MODIS、Landsat TM、Quick Bird 数据,对山西芦芽山2000 年、2005 年和2010年植被变化作了定量和定性分析。结果显示：3 年间,部分植被MODIS NDVI年际波动可达5%~10%。1 年之内,多数植被MODIS NDVI 季节性明显,Landsat TM季节差对应的NDVI差可达0.2。在自然地带的过渡区,因难以区分人类活动引起的变化和季节变化,这种季节差使变化检测面临不确定性。利用2002 年和2008 年Quick Bird 数据对森林采伐迹地对比发现,只有局部地区的植被类型开始草丛向灌木林的演替,说明植被恢复缓慢。由此可以认为,自然植被过渡带植被固有的分类模糊性,人类活动反复干扰-恢复后形成植被的破碎性,以及Landsat 数据可能存在的季节不一致性,都会影响土地覆盖分类精度和变化检测可靠性。因此,需要使用多源数据对自然过渡带进行重点分析。     

基于多架构混搭模式的极地海洋数据库建模技术研究

通过对极地海洋数据的特征及应用需求分析,基于"一种架构支持多类应用"的传统数据库模式已无法满足需求,本文提出采用"多种架构支持多类应用"模式的数据库设计理念,通过研究极地海洋数据分类分层管理体系,开展极地海洋原始数据层、基础数据层、综合数据层、成果数据层的存储管理机制、数据库体系架构设计、数据库模型设计等关键技术研究,开发数据库查询检索功能,满足用户对极地海洋数据的多样化查询检索、空间可视化展示、关联分析等需求,实现极地海洋数据的有效存储、高效应用和开放共享。     

Using geographically weighted regression kriging for crop yield mapping in West Africa

Geographical information systems support the application of statistical techniques to map spatially referenced crop data. To do this in the optimal way, errors and uncertainties have to be minimized that are often associated with operations on the data. This paper applies a spatial statistical approach to upscale crop yields from the field level toward the scale of Burkina Faso. Observed yields were related to the Normalized Difference Vegetation Index derived from SPOT-VEGETATION. The objective was to quantify the uncertainties at the subsequent steps. First, we applied a point pattern analysis to examine uncertainties due to the sampling network of field surveys in the country. Second, geographically weighted regression kriging (GWRK) was applied to upscale the yield observations and to quantify the corresponding uncertainty. The proposed method was demonstrated with the mapping of sorghum yields in Burkina Faso and results were compared with those from regression kriging (RK) and kriging with external drift using a local kriging neighborhood (KEDLN). The proposed method was validated with independent yield observations obtained from field surveys. We observed that the lower uncertainty range value increased by 39%, and the upper uncertainty range value decreased by 51%, when comparing GWRK with RK and KEDLN. Moreover, GWRK reduced the prediction error variance as compared to RK (20 vs. 31) and to KEDLN (20 vs. 39). We found that climate and topography had a major impact on the country’s sorghum yields. Further, the financial ability of farmers influenced the crop management and, thus, the sorghum crop yields. We concluded that GWRK effectively utilized information present in the covariate datasets and improved the accuracies of both the regional-scale mapping of sorghum yields and was able to quantify the associated uncertainty.     

Optical and radar remote sensing data for forest cover mapping in Peninsular Malaysia

This study aims to map forest cover in Peninsular Malaysia using satellite images as deforestation is of concern in the recent decades, and is an important environmental issue for the future too. The Carnegie Landsat Analysis System‐Lite (CLASlite) program was used in this study to detect forest cover in Peninsular Malaysia using Landsat satellite data. The results of the study show that CLASlite algorithm misclassified some oil palm, rubber and urban areas as forest vegetation. A reliable forest cover map was produced by first combining Landsat and ALOS PALSAR images to identify oil palm, rubber and urban areas, and then subsequently removing them. The HH and HV polarization data of ALOS PALSAR (threshold method) could detect oil palm plantations with 85.26 per cent of overall accuracy. For urban area detection, Enhance Build up Index (EBBI) using spectral bands from Landsat provided higher overall accuracy of 94 per cent. These methods produced a forest cover reading of 5 914 421 ha with an overall classification accuracy of 94.5 per cent. The forest cover (including rubber areas) detected in this study is 0.38 per cent higher than the percentage of 2010 forest cover detected by the Forestry Department of Peninsular Malaysia. The technique described in this paper presents an alternative and viable approach for updating forest cover maps in Malaysia.     

Using a Bayesian estimator to combine information from a cluster analysis and remote sensing data to estimate high-resolution data for agricultural production in Germany

In Germany, a county-resolution data set that consists of 35 land-use and animal-stock categories has been used extensively to assess the impact of agriculture on the environment. However, because such environmental effects as emission or nutrient surplus depend on the location, even a county resolution might produce misleading results. The aim of this article is to propose a Bayesian approach which combines two sorts of information, with one being treated as defining the prior and the other the data to form a posterior, used to estimate a data set at a municipality resolution. We define the joint prior density function based on (i) remote sensing data, thus accounting for differences in county data and missing data at the municipality level, and (ii) the results of a cluster analysis that was previously applied to the micro-census, whereas the data are defined by official statistics at the county level. This approach results in a fairly accurate data set at the municipality level. The results, using the proposed method, are validated by the national research data centre by comparing the estimates to actual observations. The test statistics presented here demonstrate that the proposed approach adequately estimates the production activities.     

Using geomagnetic secular variation to separate remanent and induced sources of the crustal magnetic field

Magnetic fields originating from magnetized crustal rocks dominate the geomagnetic spectrum at wavelengths of 0.1–100 km. It is not known whether the magnetization is predominantly induced or remanent, and static surveys cannot discriminate between the two. Long‐running magnetic observatories offer a chance, in principle, of separating the two sources because secular variation leads to a change in the main inducing field, which in turn causes a change in the induced part of the short‐wavelength crustal field. We first argue that the induced crustal field, b ^I( t ), is linearly related to the local core field, B ( t ), through a symmetric, trace‐free matrix A : b ^I( t )= A B ( t ). We then subtract a core field model from the observatory annual means and invert the residuals for three components of the remanent field, b ^R( t ), and the five independent elements of A . Applying the method to 20 European observatories, all of which have recorded for more than 50 years, shows that the most difficult task is to distinguish b ^R from the steady part of b ^I. However, for nine observatories a time‐dependent induced field fits the data better than a steady remanent field at the 99 per cent confidence level, suggesting the presence of a significant induced component to the magnetization.     

Using GIS and large-scale digital data to implement hedonic pricing studies

This paper describes how a standard GIS package can be used to convert large-scale vector digital data (point, line and annotation features) into polygons using standardised and replicable methods. Building area, garden and land use polygons are all derived from such data (Ordnance Survey LandLine.Plus). These entities are then combined with further sources of digital data to derive more refined information such as property types. Finally, complex DEMs are developed for use in visibility studies. The variables calculated are subsequently employed in a property valuation study where many are found to be significant determinants of property price. The main exception is variables relating to viewsheds, although it is argued that this does not invalidate the techniques used in their deviation but highlights the difficulties involved in modelling a large number of variables in a property price analysis.     

The application of radar topographic data to mapping of a mega-paleodrainage in the Eastern Sahara

The recently available Shuttle Radar Topography Mission (SRTM) data, with 90 m horizontal resolution, are used to delineate the entire Tushka mega-watershed. It is calculated that the watershed covers an area of 150 000 km² and composed of four subwatersheds. This study indicates that the Tushka basin is a closed hydrological system independent of the Nile hydro-system, the Qena Valley system, and the Chad basin as well. More importantly, the study demonstrates that this basin drains northeasterly toward the westernmost of the recently flooded lakes in the Tushka depression, west of Lake Nasser. The hydrological activities within the basin resulted in the formation of the largest paleo-lake deposit in Egypt at Bir-Tarfawi. The vast sand sheets that cover the Tushka basin accentuate the theory of El-Baz [1982. Genesis of the Great Sand Sea, Western Desert of Egypt. International Association of Sediment, 11th International Conference, Hamilton, Ontario, Canada, p. 68], which relates sand accumulations within basins in today's deserts to previous fluvial activities. The present study illustrates the capability of the SRTM in penetrating desert sand surfaces and mapping the ancient drainage networks, which remarkably correlate with subsurface channels detected in Radarsat-1 images.     

Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this article, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.