数字环境下地图综合结果自动评价模型的研究与应用

在对数字环境下地图综合的新含义和新任务进行分析的基础上 ,讨论了地图自动综合的评价标准和综合指标 ,提出了一种大比例尺地图综合结果自动评价模型 ,并利用该模型开发了一个评价模块内置到深圳市规划国土局开发研制的地图综合软件 Auto Map中。此模块可对地图各种要素进行地图综合结果自动评价分析。最后利用深圳市 32幅要综合的 1∶ 10 0 0 0的地图对本文提出的模型和开发的模块进行了全面的实验研究。     

Increasing the detail of European land use/cover data by combining heterogeneous data sets

ABSTRACT

Data on land use and land cover (LULC) are a vital input for policy-relevant research, such as modelling of the human population, socioeconomic activities, transportation, environment, and their interactions. In Europe, CORINE Land Cover has been the only data set covering the entire continent consistently, but with rather limited spatial detail. Other data sets have provided much better detail, but either have covered only a fraction of Europe (e.g. Urban Atlas) or have been thematically restricted (e.g. Copernicus High Resolution Layers). In this study, we processed and combined diverse LULC data to create a harmonised, ready-to-use map covering 41 countries. By doing so, we increased the spatial detail (from 25 to one hectare) and the thematic detail (by seven additional LULC classes) compared to the CORINE Land Cover. Importantly, we decomposed the class ‘Industrial and commercial units’ into ‘Production facilities’, ‘Commercial/service facilities’ and ‘Public facilities’ using machine learning to exploit a large database of points of interest. The overall accuracy of this thematic breakdown was 74%, despite the confusion between the production and commercial land uses, often attributable to noisy training data or mixed land uses. Lessons learnt from this exercise are discussed, and further research direction is proposed.     

Multi-scale remote sensing to support insurance policies in agriculture: from mid-term to instantaneous deductions

ABSTRACT

Climate change is today one of the biggest issues for farmers. The increasing number of natural disasters and change of seasonal trends is making insurance companies more interested in new technologies that can somehow support them in quantifying and mapping risks. Remotely sensed data, with special focus on free ones, can certainly provide the most of information they need, making possible to better calibrate insurance fees in space and time. In this work, a prototype of service based on free remotely sensed data is proposed with the aim of supporting insurance companies’ strategies. The service is thought to calibrate annual insurance rates, longing for their reduction at such level that new customers could be attracted. The study moves from the entire Piemonte region (NW Italy), to specifically focus onto the Cuneo province (Southern Piemonte), which is mainly devoted to agriculture. MODIS MOD13Q1-v6 and Sentinel-2 L2A image time series were jointly used. NDVI maps from MODIS data were useful to describe the midterm phenological trends of main crops at regional level in the period 2000–2018; differently, Sentinel-2 data permitted to map local crop differences at field level in 2016 and 2017 years. With reference to MODIS data, the average phenological behavior of main crop classes in the area, obtained from the CORINE Land Cover map Level 3, was considered using a time series decomposition approach. Trend analyses showed that the most of the crop classes alternated three phases (about 7 years) suggesting that, presently, this is probably the time horizon to be considered to tune mid-term algorithms for risk estimates in the agricultural context. Crop classes trends were consequently split into three phases and each of them modeled by a first-order polynomial function used to update correspondent insurance risk rate. Sentinel-2 data were used to map phenological anomalies at field level for the 2016 and 2017 growing seasons; shifts from class average behavior were considered to locally and temporarily tune insurance premium around its average trend as described at the previous step. Synthesizing, one can say that this approach, integrating MODIS and Sentnel-2 data, makes possible to locally and temporarily calibrate premiums of indexed insurance policies by describing the average trends of crop performance (NDVI) at regional level by MODIS data and refining it at field and specific crop level by Sentinel-2 data.     

土地调查专题图件的制作

本文基于第二次全国土地调查背景,结合土地调查的实际工作,分析和讨论了土地调查图件成果的内容以及土地利用现状图、基本农田分布图和耕地坡度分级图制作的主要流程和关键技术,提出了土地调查专题图件编制过程中应该注意的问题及其解决办法。     

土地利用现状数据缩编方法探讨

在国家第二次土地调查数据通过核查后,要求各省在此基础上开展多比例尺的数据缩编工作以利于成果的各类应用。本文就如何开展土地利用现状数据缩编工作进行了探讨,重点介绍了数据缩编工作的技术路线,对各类空间要素的缩编处理进行详细阐述。通过对典型区进行缩编实践,最终得到了满足国家技术指标要求、符合地方实际的数据。     

多尺度地图空间居民地语义相似度计算方法

地图综合的本质是一种空间相似变换,制图者在相似原则的指导下实施概括,读图者从包含相似性的地图中形成心象地图、重构现实世界。因此,多尺度地图空间中的相似关系研究非常重要。然而,由于相似的可计算性差,且其计算的目的在于揭示更深层次的信息,地图综合中相似关系尤其是语义相似关系的研究相对较少。针对这一问题,本文以语义功能区约束下的大比例尺街区式居民地合并（1∶1750至1∶4000）为例,基于匹配距离模型计算建筑物合并中的语义相似度,得到语义相似度在关键比例尺节点的值,并对结果进行分析、评价。试验表明,语义功能区约束下的建筑物合并符合读图者的地图认知需求,本文所述方法有助于地图更好地发挥信息传输载体的作用。     

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.     

基于EPS的1∶2000地形图缩编方法

1∶500与1∶2 000地形图是城市基础地形图,由1∶500地形图缩编成1∶2 000地形图是1∶2 000地形图制作的重要手段之一。在EPS平台,对1∶500地形图进行缩编的方法分为2类:对制图综合指标明确的要素采用全自动缩编模块处理;对于关系复杂、综合智能化较高的要素采用人机交互摸式处理。该制图综合方法的自动化程度高,已在生产项目中得到实际验证。     

基于EPS的1∶2000地形图缩编方法

1∶500与1∶2 000地形图是城市基础地形图,由1∶500地形图缩编成1∶2 000地形图是1∶2 000地形图制作的重要手段之一。在EPS平台,对1∶500地形图进行缩编的方法分为2类:对制图综合指标明确的要素采用全自动缩编模块处理;对于关系复杂、综合智能化较高的要素采用人机交互摸式处理。该制图综合方法的自动化程度高,已在生产项目中得到实际验证。     

Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.     

Comparative assessment of CORINE2000 and GLC2000: Spatial analysis of land cover data for Europe

Given the current lack of interoperability between global and regional land cover products, efforts are underway to link the new European global land cover map (GLOBCOVER) with the existing global land cover 2000 map (GLC2000) and European CORINE mapping initiative. Since both datasets apply different mapping standards, key for a successful implementation is a thorough understanding of the heterogeneities among both datasets. Thus, this paper provides an assessment of compatibilities and differences between the CORINE2000 and GLC2000 datasets. The comparative assessment considers inconsistencies between the thematic legends (using the UN land cover classification system-LCCS), class specific accuracies, and the spatial resolution and heterogeneity of the datasets. The results are summarized with implications for the development of the new GLOBCOVER datasets.     

IndoorTubes A Novel Design for Indoor Maps

Efforts within cartography on indoor maps have previously not received a lot of attention. Work that has been carried out on indoor maps often focus on map design very similar to an architectural style (Klippel et al. 2006; Ciavarella and Paternò 2004). In some cases the design has been of a more novel character where approaches with augmented and virtual realities have been carried out (Radoczky 2007; Müller et al. 2006). Common to these approaches is the depiction of one floor per map. As well, the primary user task is often solely personal navigation. In this article I present an innovative approach to indoor maps. The design is directly inspired by underground tube maps first developed by Harry Beck (Garland 1994) and today a common design for public transport maps. The main advantages of the map design are its simplicity and the possibility of including all floors in one map view. This allows the map user to easier comprehend the structure of the building without using several maps, as commonly needed with today's indoor map designs. I present several different map styles each intended to satisfy different user groups and tasks depending on the user's familiarity with the environment. In addition the article motivate for new application areas suitable for indoor maps, especially large hospitals. I hypothesize that the design proposed in this article leans very well to displaying real-time dynamic geospatial information, such as patients, staff, equipment and room availability within hospitals. Due to the early phase of the work presented here I outline the needed further work and possibilities of technological platforms as well as evaluations necessary in order for the design to gain acceptance and success.     

城市影像地图制图综合初探

影像地图制图综合是城市影像地图设计与编制的重要理论和方法。基于《广州市数字影像地图集》的编制对城市影像制图综合理论与方法进行了初步探讨,提出了不同于传统制图综合的遥感影像制图综合的内涵、影响因素与技术方法。     

泛地图学理论研究框架

信息与通信技术的快速发展带动人类进入地理空间、人文社会空间和信息空间相融合的三元空间。地图制图的目的、人员、对象和环境等均发生巨大变化,地图的类型、空间对象、表达维度、地图角色等呈现出显著泛化特征,现有地图学理论无法引领和指导当代的地图实践。地图学理论亟待"突围"。从地图学研究的角度出发,重新梳理泛地图的对象空间理论、表达维度模型,以及表达机制与方法,构建适应新环境背景,满足地图新视角、新思维、新制图需求的泛地图学理论框架,以适应地图学在新时期发展的需要。     

A method to generalize stream flowlines in small-scale maps by a variable flow-based pruning threshold

The aim of this paper is to explore and describe a method of automated generalization designed to produce a map which strikes a balance between cartographic and hydrologic representations. Following a discussion of scholarly literature on generalization, we describe a novel method for automated generalization of hydrographic stream data, using the National Hydrography Data Set (NHDPlus) as an example.

Traditional hydrography shows a fairly uniform density of stream flowlines over space. While this is pleasing to the eye, traditional methods tend to under-represent rivers in humid areas and over-represent them in arid areas. We address this problem through a method in automated generalization to produce a high-quality presentation of hydrographic data, suitable for display as a wall map or in an atlas. Streams are pruned based on a variable flow threshold, derived from the local mean annual precipitation by a regression equation.

After running the model using different parameters, we produce a more satisfactory portrayal of stream networks in the United States that communicates the flow of water through rivers and reflects the regional climate. Specific advantages in generalizing with variable flow threshold include (1) the method allows for fine gradations in output scale; (2) the output maps tend to minimize density variations in the raw data; (3) the subjective criteria are easily derived; and (4) the method can be performed rapidly on large data sets, as long as the stream data has been enriched with reliable flow rates.     

The assessment of potential land use in the proposed irrigation command using Remote Sensing and GIS

Standard false colour composites (Std. FCC) on 1:50,000 scale was visually interpreted in conjunction with soil survey to prepare physiographic-soil map. Thirteen mapping units were delineated indicating soil association at family-level. Soil and land resource was evaluated for their land capability and irrigation suitability for its sustained use under irrigation. Land capability and land irrigability maps were generated as attribute map. These maps were integrated to suggest potential land use map. Current land use/land cover map prepared by visual analysis was spatially analysed in relation to potential land use to study potential changes in land use / land cover using GIS. The study reveals that 14.66% area has no limitation and can be brought to intensive agriculture by double cropping.     

Generalization Services on the Web—Classification and an Initial Prototype Implementation

Much progress has been made in the field of web-based cartography through standards developed by the Open Geospatial Consortium (OGC). While automated access and presentation of cartographic data have been defined, the services for automated generalization are yet to be standardized. This paper aims to show advantages of applying the service concept to generalization and suggests several classification schemas of generalization services at different levels of granularity. A detailed explanation of a real implemented Generalization Service is provided. We show how software developers can make their generalization functionality available as a service and how these services can be accessed dynamically. For the implementation, the open source Java Unified Mapping Platform (JUMP) was extended to work as a framework for generalization. Generalization services could be used in different application scenarios, for instance as a middleware component extending a web map service with adaptive zooming or as stand-alone services supporting the production of topographic maps by national mapping agencies. They may also allow the development of a common research platform, where researchers would have access to a common generalization framework.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.     

Editorial

This article presents research that implements a fully automated workflow to generalize a 1:50k map from 1:10k data. This is the first time that a complete topographic map has been generalized without any human interaction. More noteworthy is that the resulting map is good enough to replace the existing map. Specifications for the automated process were established as part of this research.

Replication of the existing map was not the aim, because feasibility of automated generalization is better when compliance with traditional generalizations rules is loosened and alternate approaches are acceptable. Indeed, users valued the currency and relevancy of geographical information more than complying with all existing cartographic guidelines. The development of the workflow thus started with the creation of a test map with automated generalization operations. The reason for the test map was to show what is technologically possible and to refine the results based on iterative users’ evaluation. The generalization operations (200 in total) containing the relevant algorithms and parameter values were developed and implemented in one model. Particular effort was made to enrich the source data in order to improve the results. The model is context aware which means it is able to apply different algorithms or adjust parameter values in accordance with a specific area. The result of the research is a fully automated generalization workflow that produces a countrywide map at scale 1:50k from 1:10k data in 50 hours.

A fully automated workflow may be the only way to produce flexible and on-demand products; consequently, the results were implemented as a new production line in 2013. Issues for further research have been identified.     

Primitives as building blocks for constructing land cover maps

Land cover maps play an integral role in environmental management. However, countries and institutes encounter many challenges with producing timely, efficient, and temporally harmonized updates to their land cover maps. To address these issues we present a modular Regional Land Cover Monitoring System (RLCMS) architecture that is easily customized to create land cover products using primitive map layers. Primitive map layers are a suite of biophysical and end member maps, with land cover primitives representing the raw information needed to make decisions in a dichotomous key for land cover classification. We present best practices to create and assemble primitives from optical satellite using computing technologies, decision tree logic and Monte Carlo simulations to integrate their uncertainties. The concept is presented in the context of a regional land cover map based on a shared regional typology with 18 land cover classes agreed on by stakeholders from Cambodia, Laos PDR, Myanmar, Thailand, and Vietnam. We created annual map and uncertainty layers for the period 2000–2017. We found an overall accuracy of 94% when taking uncertainties into account. RLCMS produces consistent time series products using free long term historical Landsat and MODIS data. The customizable architecture can include a variety of sensors and machine learning algorithms to create primitives and the best suited smoothing can be applied on a primitive level. The system is transferable to all regions around the globe because of its use of publicly available global data (Landsat and MODIS) and easily adaptable architecture that allows for the incorporation of a customizable assembly logic to map different land cover typologies based on the user's landscape monitoring objectives