荒漠化分类分级理论的初步探讨

简要回顾了二十多年来联合国荒漠化代表性分类分级理论的发展,评价了1977年、1984年、1992年和1997年提出的最有代表性分类分级理论,归纳出目前三种分类分级理论的评价思想:以指标体系为基础的绝对退化评价,生产力与经营水平相结合的相对退化评价和以生态系统中植被土壤地形差异退化为依据的多样性评价。在对比分析的基础上,针对各体系存在的问题,指出通过荒漠化退化生态基准的恢复和确定可提高分类分级理论的科学性与权威性,并提出确定时间尺度和空间类型的初步建议。     

The classification and assessment of freeze-thaw erosion in Tibet

Freeze-thaw erosion is the third largest soil erosion type after water erosion and wind erosion. Restricted by many factors, few researches on freeze-thaw erosion have so far been done at home and abroad, especially those on the assessment method of freeze-thaw erosion. Based on the comprehensive analysis of impact factors of free-thaw erosion, this paper chooses six indexes, including the annual temperature range, annual precipitation, slope, aspect, vegetation and soil, to build the model for relative classification of freeze-thaw erosion using weighted and additive methods, and realizes the relative classification of the freeze-thaw erosion in Tibet with the support of GIS software. Then a synthetic assessment of freeze-thaw erosion in Tibet has been carried out according to the relative classification result. The result shows that the distribution of freeze-thaw eroded area is very extensive in Tibet, accounting for 55.3% of the total local land area; the spatial differentiation of freeze-thaw erosion with different intensities is obvious; and the difference in distribution among different regions is also obvious.     

西藏冻融侵蚀的分级和评价

Freeze-thaw erosion is the third largest soil erosion type after water erosion and wind erosion. Restricted by many factors, few researches on freeze-thaw erosion have so far been done at home and abroad, especially those on the assessment method of freeze-thaw erosion. Based on the comprehensive analysis of impact factors of free-thaw erosion, this paper chooses six indexes, including the annual temperature range, annual precipitation, slope, aspect, vegetation and soil, to build the model for relative classification of freeze-thaw erosion using weighted and additive methods, and realizes the relative classification of the freeze-thaw erosion in Tibet with the support of GIS software. Then a synthetic assessment of freeze-thaw erosion in Tibet has been carried out according to the relative classification result. The result shows that the distribution of freeze-thaw eroded area is very extensive in Tibet, accounting for 55.3% of the total local land area; the spatial differentiation of freeze-thaw erosion with different intensities is obvious; and the difference in distribution among different regions is also obvious.     

COSI-Corr技术在风沙地貌研究中的初步应用及精度检验

沙丘移动与形态监测是风沙地貌研究的重要内容,传统的测量方法对大范围的风沙地貌进行动态监测存在很大的困难。光学影像配准与关联（Co-registration of Optically Sensed Images and Correlation,COSI-Corr）技术的出现为区域风沙地貌的动态演化与监测研究提供了良好契机。讨论了COSI-Corr技术在沙丘移动和形态监测中的优势和存在的主要问题,通过无人机野外地面实测结果检验了COSI-Corr的测量精度。结果表明：沙丘背风坡底缘COSI-Corr测量精度最高,月测量误差0.01～0.53 m,达到影像分辨率的1/30像元;在沙丘背风坡底缘,COSI-Corr测量精度与沙丘底面积呈线性关系,底面积越大,COSI-Corr测量误差越大;个别沙丘脊线部位出现极大异常点,与沙丘脊线部位的光噪影响有关。COSI-Corr技术在风沙地貌监测中尚属起步阶段,一些具体的问题还需要我们在实践中不断的去检验和改进,但它确实极大提高了野外风沙地貌动态监测的效率,为研究大尺度范围内风沙地貌的时空动态演化过程提供了可能,在未来的风沙地貌研究中将具有广阔的应用前景。     

Spatial variability in classification accuracy of agricultural crops in the Dutch national land-cover database

Variability in per cell classification accuracy is predominantly modelled with land-cover class as the explanatory variable, i.e. with users' accuracies from the error matrix. Logistic regression models were developed to include other explanatory variables: heterogeneity in the 3×3 window around a cell, the size of the patch and the complexity of the landscape in which a cell is located. It was found that per cell, the probability of correct classification was significantly (α=0.05) higher for cells with a less heterogeneous neighbourhood, for cells part of larger patches and for cells in regions with a less heterogeneous landscape. To validate the models, a leave-one-out procedure was applied in which the absolute difference between the actual and the model-estimated number of cells correctly classified was summarized over 55 regions in the Netherlands. The sum of differences reduced from 60.9 to 48.1 after adding the variables ‘patch size’ and ‘landscape dominance’ to the land-cover class model. Spatial variability thus modelled therefore led to a substantial improvement in the estimation of the per cell classification accuracy.     

基于地理信息元组的分类预测理论及应用——以中亚矿集区预测为例

地理信息科学的迅速发展为矿集区预测提供了新的理论依据,使地理信息理论、相应的技术方法组合及应用的整体研究成为可能。在大量理论和实验研究的基础上提出了基于地理信息元组的分类预测理论体系,该理论体系由六个概念、一个空间信息本质、两个空间信息特性以及六个空间信息相关方法和约定的构成。并在该理论体系基础上结合空间数据分析方法和探索式空间数据分析方法,建立了基于地理信息元组的分类预测模型。应用该模型在中亚区域实现了Au矿集区预测目标。为中亚成矿域中其它区域(如新疆)的矿集区预测研究奠定了理论与方法论基础。     

Use of the weighted Kappa coefficient in classification error assessment of thematic maps

Abstract

The weighted Kappa coefficient is applied to the comparison of thematic maps. Weighted Kappa is a useful measure of accuracy when the map classes are ordered, or when the relative seriousness of the different possible errors may vary. The calculation and interpretation of weighted Kappa are demonstrated by two examples from forest surveys. First, the accuracy of thematic site quality maps classified according to an ordinal scale is assessed. Error matrices are derived from map overlays, and two different sets of agreement weights are used for the calculation. Weighted Kappa ranges from 0.34 to 0.55, but it does not differ significantly between two separate areas. Secondly, weighted Kappa is calculated for a tree species cover classified according to a nominal scale. Weights reflecting the economic loss for the forest owner due to erroneous data are used for the computation. The value of weighted Kappa is 0.56.     

Exploring a combination of objective and subjective assessment in landscape classification: Side case from Turkey

Landscape is a product of interactions between human and nature that bring multiple characteristics to discrete geographic settings. Landscape character assessment (LCA) is a process of describing, mapping and evaluating distinct characters in the landscape. The aim of this study is to integrate objective and subjective assessment in landscape classification in the case of Side district in Antalya, Turkey. The methodology of the study is based on a holistic approach to combine map-based biophysical information and on-site visual landscape characteristics into the LCA process. Principal component and cluster analysis were used to understand relationships and spatial patterns between 29 landscape character areas and types which were previously defined by previous work. The main source of data was landscape characters, and 35 character attributes was processed as variables. Cluster analysis showed that landscape character areas and types in Side were gathered into two main cluster groups and five sub clusters. The majority of landscape character areas tended to constitute separate subclusters, while character types appeared to form large groups of clusters in which recognisable land-use patterns were the main activity. According to the cluster dendrogram, it was possible to interpret spatial linkages between the clusters of character areas and types and to delineate geographic classification of the main landscapes in Side. Scaling relations for LCA in a pattern-process-product framework provided an explicit understanding of the data layers in landscape classification and where the clustering can function. Biophysical characteristics comprised the pattern of the landscape, while visual characteristics demonstrated the condition of the landscape as a product. The process depends upon transformation between the objective and the subjective as a link between pattern and product. Further steps would be to conduct semistructured surveys to assess local perceptions and preferences about landscape characters for landscape quality objectives.     

Urban mapping,accuracy, & image classification: A comparison of multiple approaches in Tsukuba City,Japan

The rapid growth of urban space and its environmental challenges require precise mapping techniques to represent complex earth surface features more accurately. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and GIS post-processing) using Advanced Land Observing Satellite images to predict urban land use and land cover of Tsukuba city in Japan. Intensive fieldwork was conducted to collect ground truth data. A random stratified sampling method was chosen to generate geographic reference data for each map to assess the accuracy. The accuracies of the maps were measured, producing error matrices and Kappa indices. The GIS post-processing approach proposed in this research improved the mapping results, showing the highest overall accuracy of 89.33% as compared to other approaches. The fuzzy supervised approach yielded a better accuracy (87.67%) than the supervised and unsupervised approaches. The fuzzy supervised approach effectively dealt with the heterogeneous surface features in residential areas. This paper presents the strengths of the mapping approaches and the potentials of the sensor for mapping urban areas, which may help urban planners monitor and interpret complex urban characteristics.     

土地利用变化遥感监测精度评价系统——以随机抽样为基础的方法

中国正在采用遥感技术对 5 0万以上市区非农人口城市的建设用地扩展情况进行分期监测 ,监测结果的精度评价是该项工作的一个重要方面。本文提出以分层随机抽样的方法来获取对遥感监测的精度分析 ,内容包括监测精度评价的指标系统、分层随机抽样样本容量的确定和在各层的分配、抽样评价的工作步骤以及抽样调查的统计分析和结果表达 ,并以北京和重庆 2 0 0 1年的遥感监测数据和实地调查数据为基础进行了精度评价的实际演练。     

自然灾害风险评估与分级方法论探研——以山西省地震灾害风险为例

自然灾害发生的可能损失一直是灾害风险评估上的难题.本研究以自然灾害风险评估经典模型为基础,提出了新的自然灾害风险评估与风险等级划分方法,利用历史灾情和孕灾环境解决风险评价中致灾因子破坏力与灾害发生的可能,并以山西省地震灾害风险为例进行了定量化评估研究.主要改进在于:确定灾害损失率和环境参数以建立地震灾害可能损失计算模型...     

基于QUEST决策树的遥感影像土地利用分类——以云南省丽江市为例

土地利用分类精度直接决定土地利用／土地覆被变化相关研究的准确性,而基于决策树的遥感影像分类是近年来提高土地利用分类精度的重要方法。QUEST决策树在影像解译和空间表达方面,运算速度和分类精度均优于普通CART等决策树方法。本文以云南丽江地区为例,应用QUEST决策树分类方法,对该地区的LandsatTM5影像图进行分类,同时将地形因素、植被指数作为地学辅助数据的因子添加到分类波段中,进行不同特征融合,来处理目标类别间的非线性关系,该方法在处理图像理解知识方面具有更大的灵活性;同时与普通决策树分类法的遥感影像分类的结果相比较,Kappa系数值从原来的0．789提高到0．849。在地形复杂的山地地区,针对TM影像数据,选择基于QUEST决策树分类能够有效提高土地利用分类结果精度。     

Variation in land cover classification due to individual interpreter assessment: a case study of farmland mapping in Norway

Visual interpretations of remote sensing images are required when producing land cover/use maps for management purposes. Human assessment is viewed as an advantage during the interpretation process. However, large mapping projects require several interpreters, and the possibility of inter-operator variability during classification work may affect map usage. In this study, five skilled interpreters from the Norwegian Forest and Landscape Institute independently updated the national Norwegian land resource dataset (AR5) in the same two study areas using the same orthophotos. Cross-tabulations were obtained, and class agreement, overall agreement, kappa agreement and fuzzy Kappa (K_fuzzy) were calculated. Most disagreements occurred in fragmented and complex landscapes, particularly with closely related classes. What can be regarded as an acceptable level of agreement depends on the intended map use and should be based on sensitivity tests exploring the effects of interpreter variation on specific applications of the map product. Finally, the threshold is a political decision based on thorough consideration of the economic and non-economic consequences of the variation tolerated in the maps produced.     

基于粗集的知识发现与地理模拟——以深圳市土地利用变化为例

为了更有效地模拟地理现象的复杂演变过程,提出了用粗集理论来确定元胞自动机 (CA)不确定性转换规则的新方法。CA可以通过局部规则来有效地模拟许多地理现象的演变过程。但目前缺乏很好定义CA转换规则的方法。往往采用启发式的方法来定义CA的转换规则,这些转换规则是静态的,而且其参数值多是确定的。在反映诸如城市扩张、疾病扩散等不确定性复杂现象时,具有一定的局限性。利用粗集从GIS和遥感数据中发现知识,自动寻找CA的不确定性转换规则,基于粗集的CA在缩短建模时间的同时,能提取非确定性的转换规则,更好地反映复杂系统的特点。采用所提出的方法模拟了深圳市的城市发展过程,取得了比传统MCE方法更好的模拟效果。     

基于粗糙模型的模糊地理对象空间拓扑关系研究

在粗糙集的基本概念上,基于上、下近似集定义了二维离散空间中的粗糙区域和粗糙模型,用粗糙模型描述二维离散空间中的模糊地理对象,并给出了粗糙区域的3种类型:确定—确定类型、确定—模糊类型、模糊—模糊类型。在离散空间的空间连接计算理论RCC-D-5的基础上,定义了模糊地理对象拓扑关系之间的拓扑约束关系,并依据概念临近推演和拓扑约束关系,研究得出二维离散空间中简单模糊地理对象之间的73种全拓扑关系,并基于4×4相交包含矩阵进行了描述,使得复杂的拓扑关系在计算机中描述和表达成为可能。     

Map-image registration accuracy using least-squares polynomials

Abstract

Results of a simulation study of map-image rectification accuracy are reported. Sample size, spatial distribution pattern and measurement errors in a set of ground control points, and the computational algorithm employed to derive the estimate of the parameters of a least-squares bivariate map-image transformation function, are varied in order to assess the sensitivity of the procedure. Standard errors and confidence limits are derived for each of 72 cases, and it is shown that the effects of all four factors are significant. Standard errors fall rapidly as sample size increases, and rise as the control point pattern becomes more linear. Measurement error is shown to have a significant effect on both accuracy and precision. The Gram-Schmidt orthogonal polynomial algorithm performs consistently better than the Gauss-Jordan matrix inversion procedure in all circumstances.     

基于粗糙集的不确定区域RCC拓扑关系研究

基于粗糙集定义了粗糙区域和粗糙区域的上、下近似区域,提出两种基于上、下近似区域表示粗糙区域拓扑关系的方法。一种方法用上、下近似区域的连接关系表达粗糙区域拓扑关系,得出两个粗糙区域之间的6种拓扑关系,并进一步利用上、下近似区域的RCC5关系表达粗糙区域之间的拓扑关系,得出两个粗糙区域之间的51种拓扑关系,然后分析两种表达之间的联系。另一种方法扩展RCC5模型,首先定义三值逻辑的部分关系≤和补运算~,然后用三值逻辑三元组(X≤Y,X≤~Y,Y≤X)描述两个粗糙区域X和Y的拓扑关系,并给出可能的8种拓扑关系。