Qualitative landslide susceptibility assessment by multicriteria analysis: A case study from San Antonio del Sur, Guantánamo, Cuba

Geomorphological information can be combined with decision-support tools to assess landslide hazard and risk. A heuristic model was applied to a rural municipality in eastern Cuba. The study is based on a terrain mapping units (TMU) map, generated at 1:50,000 scale by interpretation of aerial photos, satellite images and field data. Information describing 603 terrain units was collected in a database. Landslide areas were mapped in detail to classify the different failure types and parts. Three major landslide regions are recognized in the study area: coastal hills with rockfalls, shallow debris flows and old rotational rockslides denudational slopes in limestone, with very large deep-seated rockslides related to tectonic activity and the Sierra de Caujerí scarp, with large rockslides. The Caujerí scarp presents the highest hazard, with recent landslides and various signs of active processes. The different landforms and the causative factors for landslides were analyzed and used to develop the heuristic model. The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones. From these variables a hierarchical heuristic model was applied in which three levels of weights were designed for classes, variables, and criteria. The model combines all weights into a single hazard value for each pixel of the landslide hazard map. The hazard map was then divided by two scales, one with three classes for disaster managers and one with 10 detailed hazard classes for technical staff. The range of weight values and the number of existing landslides is registered for each class. The resulting increasing landslide density with higher hazard classes indicates that the output map is reliable. The landslide hazard map was used in combination with existing information on buildings and infrastructure to prepare a qualitative risk map. The complete lack of historical landslide information and geotechnical data precludes the development of quantitative deterministic or probabilistic models.     

Comparison of land cover maps using fuzzy agreement

A generic problem associated with different land cover maps that cover the same geographical area is the use of different legend categories. There may be disagreement in many areas when comparing different land cover products even though the legend shows the same or very similar land cover class. To capture the uncertainty associated with both differences in the legend and the difficulty in classification when comparing two land cover maps, expert knowledge and a fuzzy logic framework are used to map the fuzzy agreement. The methodology is illustrated by comparing the Global Land Cover 2000 data set and the MODIS global land cover product. Overall accuracy measures are calculated, and the spatial fuzzy agreement between the two land cover products is provided. This approach can be used to improve the overall confidence in a land cover product, since areas of severe disagreement can be highlighted, and areas can be identified that require further attention and possible re-mapping.     

Thematic land-cover map assimilation and synthesis: the case of locating potential bioenergy feedstock in eastern Ontario,Canada

Insufficient spatial coverage of existing land-cover data is a common limitation to timely and effective spatial analysis. Achieving spatial completeness of land-cover data is the most challenging for large study areas which straddle ecological or administrative boundaries, and where individuals and agencies lack access to, and the means to process, raw data from which to derive spatially complete land-cover maps. In many cases, various sources of secondary data are available, so that land-cover map assimilation and synthesis can resolve this research problem. The following paper develops a reliable and repeatable framework for assimilating and synthesizing pre-classified data sets. Assimilation is achieved through data reformatting and map legend reconciliation in the context of a specific application. Individual maps are assessed for accuracy at various geographic scales and levels of thematic precision, with an emphasis on the ‘area of overlap’, in order to extract information that guides the synthesis process. The quality of the synthesized land-cover data set is evaluated using advanced accuracy assessment methods, including a measure describing the ‘magnitude of disagreement’. This method is applied to derive a seamless thematic map of the land cover of eastern Ontario from two disparate map series. The importance of assessing data quality throughout the process using multiple reference data sets is highlighted, and limitations of the method are discussed.     

COMPARING TRADITIONAL METHODS FOR SELECTING CLASS INTERVALS ON CHOROPLETH MAPS*

The most common goal when classing data for choropleth maps is to create homogeneous classes which contain similar data values. None of the four traditional data classing methods examined here (quartile, equal interval, standard deviation, and natural breaks) consistently generalized the experimental data sets into homogeneous classes. These methods were most accurate for data sets with specific distributional characteristics, but none classed all of any type of distribution accurately. Only the optimization method produced reliable and accurate results for all of the experimental data.     

Demographic Transition: Threat to Developing Nations

Abstract

As computers become commonplace in the nation's schools, interactive maps are finding their way into the geography classroom. Students can use electronic atlases to access information as well as use authoring software to produce their own interactive maps. Does this change in media correspond to better geography education for our children? This article addresses whether using interactive maps for gathering and presenting information can have a positive influence on learning geography content. A two-week experiment was conducted in five 7th grade classrooms. Students in four of the classes researched and produced map products using both traditional and computer-assisted techniques. The fifth class was a control group. A pretest and two post-tests were given to quantitatively assess student learning after each project. Also, students were given a qualitative questionnaire to determine their attitude towards the different techniques. Quantitative results of the study indicate that there was no significant difference in student post-test performance after using each of the techniques, but qualitative results suggest that students prefer using the computer techniques over the traditional methods for gathering and presenting information.     

FRYBERGER输沙势计算方法及其估算值偏差分析——以塔克拉玛干沙漠为例

以塔克拉玛干沙漠地区2007年5个观测站及策勒站2007-2013年逐时观测数据为例,详细介绍了FRYBERGER输沙势计算方法和步骤,并对输沙势含义和易混淆的问题进行了解释说明。基于输沙势公式定义输沙势基准值,通过比较FRYBERGER输沙势估算值与基准值之间的差异,分析了不同观测点之间年均输沙势及其各风级输沙势分量的估算偏差。结果表明：（1）风速观测值的平均时距愈短,风速脉动性作用愈显著,导致输沙势计算值偏大。（2）输沙势的贡献率主要集中于I、II风级,其分布形态不同于起沙风频数分布。（3）FRYBERGER方法估算各测站年均输沙势时,采用FRYBERGER风速中间值产生的估算偏差最小。（4）输沙势估算偏差具有区域和年际性变化（策勒站为例）。（5）各风级风速代表值对输沙势分量的估算偏差产生影响,其最佳组合随观测点和年份而变化;采用最佳组合可有效减小输沙势估算偏差。     

Head/Tail Breaks: A New Classification Scheme for Data with a Heavy-Tailed Distribution

This article introduces a new classification scheme—head/tail breaks—to find groupings or hierarchy for data with a heavy-tailed distribution. The heavy-tailed distributions are heavily right skewed, with a minority of large values in the head and a majority of small values in the tail, commonly characterized by a power law, a lognormal, or an exponential function. For example, a country's population is often distributed in such a heavy-tailed manner, with a minority of people (e.g., 20 percent) in the countryside and the vast majority (e.g., 80 percent) in urban areas. This new classification scheme partitions all of the data values around the mean into two parts and continues the process iteratively for the values (above the mean) in the head until the head part values are no longer heavy-tailed distributed. Thus, the number of classes and the class intervals are both naturally determined. I therefore claim that the new classification scheme is more natural than the natural breaks in finding the groupings or hierarchy for data with a heavy-tailed distribution. I demonstrate the advantages of the head/tail breaks method over Jenks's natural breaks in capturing the underlying hierarchy of the data.     

地图质量可拓综合评价模型

可拓学是解决矛盾问题的新兴交叉学科,理论支柱是物元理论和可拓集合。它以物元为基本元,通过物元变换来建立物元模型,化矛盾问题为相容问题。基于可拓论探讨了地图质量的可拓综合评价新模型,即通过构造各评定等级的经典域和全体等级的节域物元矩阵,计算待评物元与各评定等级之间的关联度,判定对各评定等级的符合程度而作出综合评定。文中给出了具体评价流程,并应用于实际地图的质量综合评价,结果同其它方法进行了对比,取得了较好的结果。     

基于多样本潜在类别的旅游者生态文明行为分析——以苏州市为例

基于多样本潜在类别模型,划分旅游者生态文明行为的潜在类别,比较不同性别、学历、年龄和收入旅游者潜在类别的异同。研究发现：① 根据生态文明行为差异,可以将旅游者划分为成熟型、起步型和淡漠型3种类型,分别占旅游者总数的28.7%、33.2%和38.2%,成熟型旅游者最少。② 性别间、学历间、收入间存在较高的形貌同构性（潜在类别数目都为3）和内涵同构性（各潜在类别命名一致）,表明性别、学历、收入对旅游者生态文明行为的影响较小;高学历对成熟型、起步型旅游者的生态文明行为有少量促进作用。③ 年龄间尽管分类形貌相似（潜在类别数目都为3）,但是分类内涵存在异质性,高、中、低年龄者的潜在类别命名和占比不尽相同;中年龄者生态文明行为表现优于低年龄者,表明年龄增长对主流旅游者的生态文明行为有积极影响;高年龄者生态文明行为呈现两极分化状态。④ 生态文明行为六要素方面,游览生态文明化最易实现,其次是出行生态文明化,而餐饮、住宿、购物、娱乐生态文明化实现难度较大。最后,从旅游者、旅游企业和国家三个层面探讨旅游者生态文明行为提升路径。     

Direct induction of compact rule-based classifiers for resource mapping

Abstract

Rule-based classifiers are used regularly with geographical information systems to map categorical attributes on the basis of a set of numeric or unordered categorical attributes. Although a variety of methods exist for inducing rule-based classifiers from training data, these tend to produce large numbers of rules when the data has noise. This paper describes a method for inducing compact rule-sets whose classification accuracy can, at least in some domains, compare favourably with that achieved by larger less succinct rule-sets produced by alternative methods. One rule is induced for each output class. The condition list for this rule represents a box in n-dimensional attribute space, formed by intersecting conditions which exclude other classes. Despite this simplicity, the classifier performed well in the test application prediction of soil classes in the Port Hills, New Zealand, on the basis of regolith type and topographic attributes obtained from a digital terrain model.     

一种面向对象分类的特征分析方法

特征分析是面向对象分类成功的先决条件,通常采用试错方式进行。由于时间和成果要求等条件限制,通常不可能测试所有的特征,致使所选取特征常常并不是最佳特征,从而导致分类效果不理想。该文采用SaT特征分析方法,从大量特征集中准确提取特有特征,而且能获取相关联的阈值;通过其计算分离度值,可以实时地比较特征分类质量。实例验证表明,该方法能大大提高面向对象分类方法的精度和速度。     

地图综合中语义质量的度量方法研究

从地图综合前、后语义变化的角度,建立了一种地图综合中语义质量的度量方法。从语义变化的4个方面分别提出了相应的语义质量元素,即语义准确性、一致性、完整性和内容相似性;从目标层次、目标类层次和地图层次分别建立了以上4个语义质量元素的度量指标。在此基础上,给出1个地图语义质量综合指标,即通过对提出的4个语义质量元素分别赋予1个权重得到。最后,通过实例分析了语义质量元素在GIS环境下的实现方法。     

雾霾影响下不同阶层市民日常消费活动与制约

由于不同阶层居民资源获取和选择能力的差异,导致雾霾这种外部环境制约有差异地内化为个人的感知和心理制约,出现不同阶层在恶劣天气环境下的日常生活时空行为差异。通过对南京市老城南地区居民日常消费活动的调查访谈与情景阐释,发现雾霾影响下居民的消费活动随着消费类型以及消费者阶层的差异呈现不同的时空间变化特征。另外,由于不同阶层冲破制约的能力存在差别,致使应对雾霾的消费行为与活动出现差异。低阶层面对恶劣天气影响的能动性非常局限,往往做出被动妥协行为,而中、高阶层则积极主动应对雾霾危害。研究进一步强调,负面环境制约,如消极的天气影响,有可能放大现有的社会经济差异,使不同阶层之间的日常生活空间隔离加剧。     

Expert-driven semi-automated geomorphological mapping for a mountainous area using a laser DTM

In this paper a semi-automated method is presented to recognize and spatially delineate geomorphological units in mountainous forested ecosystems, using statistical information extracted from a 1-m resolution laser digital elevation dataset. The method was applied to a mountainous area in Austria. First, slope angle and elevation characteristics were determined for each key geomorphological unit occurring in the study area. Second, a map of slope classes, derived from the laser DTM was used in an expert-driven multilevel object-oriented approach. The resulting classes represent units corresponding to landforms and processes commonly recognized in mountain areas: Fluvial terrace, Alluvial Fan, Slope with mass movement, Talus slope, Rock cliff, Glacial landform, Shallow incised channel and Deep incised channel. The classification result was compared with a validation dataset of geomorphological units derived from an analogue geomorphological map. For the above mentioned classes the percentages of correctly classified grid cells are 69%, 79%, 50%, 64%, 32%, 61%, 23% and 70%, respectively. The lower values of 32% and 23% are mainly related to inaccurate mapping of rock cliffs and shallow incised channels in the analogue geomorphological map. The accuracy increased to 76% and 54% respectively if a buffer is applied to these specific units. It is concluded that high-resolution topographical data derived from laser DTMs are useful for the extraction of geomorphological units in mountain areas.     

Increasing the spatial resolution of agricultural land cover maps using a Hopfield neural network

Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale.     

Toward mapping land-use patterns from volunteered geographic information

A large number of applications have been launched to gather geo-located information from the public. This article introduces an approach toward generating land-use patterns from volunteered geographic information (VGI) without applying remote-sensing techniques and/or engaging official data. Hence, collaboratively collected OpenStreetMap (OSM) data sets are employed to map land-use patterns in Vienna, Austria. Initially the spatial pattern of the landscape was delineated and thereafter the most relevant land type was assigned to each land parcel through a hierarchical GIS-based decision tree approach. To evaluate the proposed approach, the results are compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) data. The results are compared in two ways: first, the texture of the resulting land-use patterns is analyzed using texture-variability analysis. Second, the attributes assigned to each land segment are evaluated. The achieved land-use map shows kappa indices of 91, 79, and 76% agreement for location in comparison with the GMESUA data set at three levels of classification. Furthermore, the attributes of the two data sets match at 81, 67, and 65%. The results demonstrate that this approach opens a promising avenue to integrate freely available VGI to map land-use patterns for environmental planning purposes.     

A double continuous approach to visualization and analysis of categorical maps

A method to visualize multiple membership maps, called ‘Colour mixture’ (CM) is described and compared with alternative techniques: defuzzification and Pixel mixture. Six landform parameters were used to derive the landform classes using supervised fuzzy k-means classification. The continuous categorical map is derived by GIS calculations with colours, where colour values are considered to represent the taxonomic space spanned by the attribute variables. Coordinates of the nine class centres (landform facets) were first transformed from multivariate to two-dimensional attribute space using factor analysis, and then projected on the Hue Saturation Intensity (HSI) colourwheel. The taxonomic value was coded with the Hue and confusion with Saturation. To improve visual impression, saturation was replaced with whiteness. Classes that were closer in attribute space were merged into similar generic colours. The CM technique limits the derived mixed-colour map to seven generic hues independently of the total number of classes, which provides a basis for automated generalization. The confusion index derived from the mixed-colour map was used to derive primary boundaries and to locate areas of higher taxonomic confusion.     

Mapping forest biomass in India through aerial photographs and nondestructive field sampling

A method for mapping of forest biomass using black-and-white aerial photographs and nondestructive field sampling is described through a case study of Ladhiya subcatchment in Kumaun Himalaya, India. Forest types were mapped using aerial photographs and field checks. Each forest type was divided into five crown cover classes. Mean crown cover for each class was determined in the field. Density and basal cover were measured on reference sites. Stand biomass was estimated by using biomass estimation equations, mean girth and mean density on the reference sites. Regression equations were developed between crown cover and basal cover, and between crown cover and stand biomass. Mean basal cover and mean stand biomass for each photo-interpreted crown cover class were estimated through these equations. Forest biomass values were substituted for crown cover classes on the interpreted map.     

Risk Assessment of Vegetation Degradation Using Geographic Information System: A Case Study of Qareh Aghaj Basin,Iran

The entire land of Southern Iran faces problems arising out of various types of land degradation of which vegetation degradation forms one of the major types. The Qareh Aghaj basin (1 265 000 ha), which covers the upper reaches of Mond River, has been chosen for a test risk assessment of this type. The different kinds of data for indicators of vegetation degradation were gathered from the records and published reports of the governmental offices of Iran. A new model has been developed for assessing the risk of vegetation degradation. Taking into consideration nine indicators of vegetation degradation the model identifies areas with “Potential Risk” (risky zones) and areas of “Actual Risk” as well as projects the probability of the worse degradation in future. The preparation of risk maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures. By fixing the thresholds of severity classes of the nine indicators a hazard map for each indicator was first prepared in GIS. The risk classes were defined on the basis of risk scores arrived at by assigning the appropriate attributes to the indicators and the risk map was prepared by overlaying nine hazard maps in the GIS. Areas under actual risk have been found to be widespread (78%) in the basin and when the risk map classified into subclasses of potential risk with different probability levels the model projects a statistical picture of the risk of vegetation degradation.     

DEM误差对滑坡危险性评价模型的影响

基于数字高程模型(DEM)计算得到的坡度、坡向等地形属性是滑坡危险性评价模型的重要输入数据, DEM误差会导致地形属性计算结果不确定性, 进而影响滑坡危险性评价模型的结果。本文选择基于专家知识的滑坡危险性评价模型和逻辑斯第回归模型, 采用蒙特卡洛模拟方法, 研究DEM误差所导致的滑坡危险性评价模型结果不确定性。研究区位于长江中上游的重庆开县, 采用5 m分辨率的DEM, 以序贯高斯模拟方法模拟了不同大小(误差标准差为1 m、7.5 m、15 m)和空间自相关性(变程为0 m、30 m、60 m、120 m)的12 类DEM误差场参与滑坡危险性评价。每次模拟包括100 个实现, 通过对每次模拟分别计算滑坡危险性评价结果的标准差图层和分类一致性百分比图层, 用以评价结果不确定性。评价结果表明, 在不同的DEM精度下, 两个滑坡危险性评价模型所得结果的总体不确定性随空间自相关程度的变化趋势并不相同。当DEM空间自相关性程度不同时, 基于专家知识的滑坡危险性评价模型的评价结果总体不确定随着DEM误差增加而呈现不同的变化趋势, 而逻辑斯第回归模型的评价结果总体不确定性随着DEM误差大小增加而单调增加。从评价结果总体不确定性角度而言, 总体上逻辑斯第回归模型比基于专家知识的滑坡危险性评价模型更加依赖于DEM数据质量。