Simple and highly accurate formulas for the computation of Transverse Mercator coordinates from longitude and isometric latitude

A conformal approximation to the Transverse Mercator (TM) map projection, global in longitude λ and isometric latitude q, is constructed. New formulas for the point scale factor and grid convergence are also shown. Assuming that the true values of the TM coordinates are given by conveniently truncated Gauss–Krüger series expansions, we use the maximum norm of the absolute error to measure globally the accuracy of the approximation. For a Universal Transverse Mercator (UTM) zone the accuracy equals 0.21  mm, whereas for the region of the ellipsoid bounded by the meridians  ±20° the accuracy is equal to 0.3  mm. Our approach is based on a four-term perturbation series approximation to the radius r(q) of the parallel q, with a maximum absolute deviation of 0.43  mm. The small parameter of the power series expansion is the square of the eccentricity of the ellipsoid. This closed approximation to r(q) is obtained by solving a regularly perturbed Cauchy problem with the Poincaré method of the small parameter. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Transformation from geocentric to geodetic coordinates using Newton's iteration

Summary A new procedure for the transformation from geocentric to geodetic coordinates is introduced and analyzed. This new procedure which contains only one trigonometric function uses the Newton's iteration to solve the root of a non-linear equation. Compared with the well-known Bowring's iterative algorithm which uses a number of trigonometric functions, the new procedure is more efficient in computation. Numeric examples are used to test the two algorithms and the results show that the new procedure converges just as well as Bowring's algorithm but requires less time for completion.     

利用RTK进行数字化测图的经验总结

利用RTK进行数字化测图具有速度快、精度高、费用省等特点,RTK测量结果经过简单处理即可导入到CASS测图软件中,从而快速地生产出规范的地形图来。根据利用RTK技术在约100多km^2区域1：2000数字化测图的生产实践,对利用RTK进行数字化测图的作业流程和工作经验进行了归纳总结,对所遇到的问题进行了分析,并提出了相应的解决方案。     

Disaggregating and mapping crop statistics using hypertemporal remote sensing

Governments compile their agricultural statistics in tabular form by administrative area, which gives no clue to the exact locations where specific crops are actually grown. Such data are poorly suited for early warning and assessment of crop production. 10-Daily satellite image time series of Andalucia, Spain, acquired since 1998 by the SPOT Vegetation Instrument in combination with reported crop area statistics were used to produce the required crop maps. Firstly, the 10-daily (1998–2006) 1-km resolution SPOT-Vegetation NDVI-images were used to stratify the study area in 45 map units through an iterative unsupervised classification process. Each unit represents an NDVI-profile showing changes in vegetation greenness over time which is assumed to relate to the types of land cover and land use present. Secondly, the areas of NDVI-units and the reported cropped areas by municipality were used to disaggregate the crop statistics. Adjusted R-squares were 98.8% for rainfed wheat, 97.5% for rainfed sunflower, and 76.5% for barley. Relating statistical data on areas cropped by municipality with the NDVI-based unit map showed that the selected crops were significantly related to specific NDVI-based map units. Other NDVI-profiles did not relate to the studied crops and represented other types of land use or land cover. The results were validated by using primary field data. These data were collected by the Spanish government from 2001 to 2005 through grid sampling within agricultural areas; each grid (block) contains three 700 m × 700 m segments. The validation showed 68%, 31% and 23% variability explained (adjusted R-squares) between the three produced maps and the thousands of segment data. Mainly variability within the delineated NDVI-units caused relatively low values; the units are internally heterogeneous. Variability between units is properly captured. The maps must accordingly be considered “small scale maps”. These maps can be used to monitor crop performance of specific cropped areas because of using hypertemporal images. Early warning thus becomes more location and crop specific because of using hypertemporal remote sensing.     

Multitemporal settlement and population mapping from Landsat using Google Earth Engine

As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more sustainable practices. The Google Earth Engine (GEE) leverages cloud computing services to provide analysis capabilities on over 40 years of Landsat data. As a remote sensing platform, its ability to analyze global data rapidly lends itself to being an invaluable tool for studying the growth of urban areas. Here we present (i) An approach for the automated extraction of urban areas from Landsat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation of the extracted urban extents using changes in the statistical performance of a high resolution population mapping method. Temporally distinct urban extractions were classified from the GEE catalog of Landsat 5 and 7 data over the Indonesian island of Java by using a Normalized Difference Spectral Vector (NDSV) method. Statistical evaluation of all of the tests was performed, and the value of population mapping methods in validating these urban extents was also examined. Results showed that the automated classification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urban extents also improved the quality of the population mapping outputs.     

Updating Landsat-based forest cover maps with MODIS images using multiscale spectral-spatial-temporal superresolution mapping

With the high deforestation rates of global forest covers during the past decades, there is an ever-increasing need to monitor forest covers at both fine spatial and temporal resolutions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat series images have been used commonly for satellite-derived forest cover mapping. However, the spatial resolution of MODIS images and the temporal resolution of Landsat images are too coarse to observe forest cover at both fine spatial and temporal resolutions. In this paper, a novel multiscale spectral-spatial-temporal superresolution mapping (MSSTSRM) approach is proposed to update Landsat-based forest maps by integrating current MODIS images with the previous forest maps generated from Landsat image. Both the 240 m MODIS bands and 480 m MODIS bands were used as inputs of the spectral energy function of the MSSTSRM model. The principle of maximal spatial dependence was used as the spatial energy function to make the updated forest map spatially smooth. The temporal energy function was based on a multiscale spatial-temporal dependence model, and considers the land cover changes between the previous and current time. The novel MSSTSRM model was able to update Landsat-based forest maps more accurately, in terms of both visual and quantitative evaluation, than traditional pixel-based classification and the latest sub-pixel based super-resolution mapping methods The results demonstrate the great efficiency and potential of MSSTSRM for updating fine temporal resolution Landsat-based forest maps using MODIS images.     

Built-up and vegetation extraction and density mapping using WorldView-II

This study demonstrates the use of high resolution WorldView-II satellite data in extraction of built-up land and vegetation using normalized index techniques. The PCA 1 and NIR 2 bands-based built-up index was proposed for extracting built-up land, which exhibit high accuracy. The normalized difference vegetation index based on Red Edge and NIR 2 bands of WorldView-II produced high accuracy inthe estimation of vegetation compared to the use of Red and NIR bands. The grid technique used in estimating built-up and vegetation density from precisely classified images provided better and accurate assessment of built-up and vegetation density in heterogeneous landscape of urban areas. This shows areas of very high to high built-up density are located in the central, western and southern parts, which are primarily devoid of vegetation. This study indicates possibilities of utilizing high resolution satellite data in urban landscape characterization using a grid-based technique.     

Transformation of coordinates between two horizontal geodetic datums

The following topics are discussed in this paper: the geocentric coordinate system and its different realizations used in geodetic practice; the definition of a horizontal geodetic datum (reference ellipsoid) and its positioning and orientation with respect to the geocentric coordinate system; positions on a horizontal datum and errors inherent in the process of positioning; and distortions of geodetic networks referred to a horizontal datum. The problem of determining transformation parameters between a horizontal datum and the geocentric coordinate system from known positions is then analysed. It is often found necessary to transform positions from one horizontal datum to another. These transformations are normally accomplished through the geocentric coordinate system and they include the transformation parameters of the two datums as well as the representation of the respective network distortions. Problems encountered in putting these transformations together are pointed out.     

Detection and mapping of maize streak virus using RapidEye satellite imagery

The aim of this study was to detect and map MSV using RapidEye multispectral sensor in Ofcolaco farm. To achieve this objective, the acquired RapidEye sensor was classified using the robust Random Forest algorithm. Furthermore, the variable importance technique was used to determine the influence of each spectral band and indices on the mapping accuracy. For better performance of image data, the value of the commonly used vegetation indices in improving the classification accuracy was tested. The results revealed that the use of RapidEye spectral bands in detection and mapping of MSV yielded good classification results with an overall accuracy of 82.75%. The inclusion of vegetation indices computed from RapidEye sensor improved the classification accuracies by 3.4%. The most important RapidEye spectral bands in classifying MSV were near infrared, blue and red-edge. On the other hand, the most important vegetation indices were the Soil adjusted vegetation index, Enhanced vegetation index, Red index and Normalized Vegetation Index. The current study recommends future studies to assess the importance of multi-temporal remote sensing applications in detecting and monitoring the spread of MSV.     

Automatic mapping and innovative on-demand mapping services at IGN France

Mapmaking has become widespread through the Internet, resulting in a wide range of cartographic quality. To achieve better quality, mapmaking needs tools and online services for intuitive and efficient on-demand mapping. A project team at IGN, the French National Mapping Agency, is working on producing a digital cartographic model (DCM) from various existing databases and maps on which such tools and services are based. This DCM ranges from detailed topographic maps to small general road maps. GeoServer Web Map Service capabilities were used extensively to produce quality maps with various legends. Special care was taken to make a default legend suitable for customer data overlays, both on-screen and on paper. Web-based interface prototypes were built to guide users in choosing colors and creating their own original map legends. Users can also rely on a growing catalog of harmonious color palettes and map samples as sources of inspiration.     

基于C#的简码法数字化测图技术在测量中的应用

随着计算机技术与测绘科学技术的发展,传统的模拟测图方法已被高度自动化的数字化测图技术所替代。通过大量实践探索,提出一种在测量中实用、经济、高效的测图方法一一简码法,并通过C#语言编程将野外测点简码转化成CASS成图系统默认的编程实现野外数据的转换,并实现内业自动成图。文中利用该方法对昆明理工大学校园进行了数字化测图验证。结果表明：该方法相对其他测图方法外业数据采集速度更快,内业工作量及测量成本大大减少,且该方法能方便地与GIS系统进行数据交换以及更好地服务于测绘行业,提高工作效率。     

The solution of the Korn–Lichtenstein equations of conformal mapping: the direct generation of ellipsoidal Gauß–Krüger conformal coordinates or the Transverse Mercator Projection

The differential equations which generate a general conformal mapping of a two-dimensional Riemann manifold found by Korn and Lichtenstein are reviewed. The Korn–Lichtenstein equations subject to the integrability conditions of type vectorial Laplace–Beltrami equations are solved for the geometry of an ellipsoid of revolution (International Reference Ellipsoid), specifically in the function space of bivariate polynomials in terms of surface normal ellipsoidal longitude and ellipsoidal latitude. The related coefficient constraints are collected in two corollaries. We present the constraints to the general solution of the Korn–Lichtenstein equations which directly generates Gau?–Krüger conformal coordinates as well as the Universal Transverse Mercator Projection (UTM) avoiding any intermediate isometric coordinate representation. Namely, the equidistant mapping of a meridian of reference generates the constraints in question. Finally, the detailed computation of the solution is given in terms of bivariate polynomials up to degree five with coefficients listed in closed form. Received: 3 June 1997 / Accepted: 17 November 1997     

TerraSAR-X卫星影像中大比例尺测图应用研究

为了研究TerraSAR-X卫星的中大比例尺测图可行性,文章利用成都都江堰市3m、1m分辨率的TerraSAR-X影像、控制点及可见光卫星影像,对TerraSAR-X影像在多云多雨地区的中、大比例尺测图展开了研究和分析。实验表明利用TerraSAR-X影像能够符合中大比例尺基础地图测图或修测的精度要求,可用于困难地区1∶50 000~1∶10 000比例尺的基础测图生产和更新。     

Technical progress of China's national remote sensing mapping:from mapping western China to national dynamic mapping

Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1∶50,000 topographic data of China's land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing map-ping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of colla-boration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic survey-ing and mapping.     

利用GML模式映射屏蔽地理空间数据源的异构性

本文分析了地理空间数据源的异构性以及GML模式的异构性;提出以GML模式对地理空间要素进行建模,构建适合空间信息共享的GML基本地物规范模式;通过应用模式的结构去屏蔽不同数据源结构的异构胜,通过对应物属性去屏蔽编码语义的异构性,使空间信息的共享与互操作有统一的语义基础.     

关于新型测绘的探索

探索新型测绘的产生背景与科学内涵等问题,对新时期测绘地理信息事业转型升级与跨越发展具有重要意义。该文首先从经济社会发展需求、测绘发展新阶段、测绘地理信息转型升级、测绘地理信息跨越发展4个方面阐述了新型测绘产生的背景;其次,从新型测绘关系角度给出了新型测绘的内涵与架构,从范围、内容、技术手段、体制机制方面描述了新型测绘的特征;再次,从新型测绘目标出发,描述了新型基础测绘的内涵、要求与主要任务,地理国情监测的总体目标与主要任务,公共服务与应急测绘的新需求与主要任务;最后围绕测绘地理空间数据获取、处理、管理、分析、服务与应用主线,探讨了新型测绘需要着重研究的新理论、新方法、新技术装备,旨在为新型测绘的研究与发展奠定基础。     

Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data

The aim of this paper is to assess the accuracy of an object-oriented classification of polarimetric Synthetic Aperture Radar (PolSAR) data to map and monitor crops using 19 RADARSAT-2 fine beam polarimetric (FQ) images of an agricultural area in North-eastern Ontario, Canada. Polarimetric images and field data were acquired during the 2011 and 2012 growing seasons. The classification and field data collection focused on the main crop types grown in the region, which include: wheat, oat, soybean, canola and forage. The polarimetric parameters were extracted with PolSAR analysis using both the Cloude–Pottier and Freeman–Durden decompositions. The object-oriented classification, with a single date of PolSAR data, was able to classify all five crop types with an accuracy of 95% and Kappa of 0.93; a 6% improvement in comparison with linear-polarization only classification. However, the time of acquisition is crucial. The larger biomass crops of canola and soybean were most accurately mapped, whereas the identification of oat and wheat were more variable. The multi-temporal data using the Cloude–Pottier decomposition parameters provided the best classification accuracy compared to the linear polarizations and the Freeman–Durden decomposition parameters. In general, the object-oriented classifications were able to accurately map crop types by reducing the noise inherent in the SAR data. Furthermore, using the crop classification maps we were able to monitor crop growth stage based on a trend analysis of the radar response. Based on field data from canola crops, there was a strong relationship between the phenological growth stage based on the BBCH scale, and the HV backscatter and entropy.