Updating the Phase 1 habitat map of Wales, UK, using satellite sensor data

The Phase 1 Survey is the most comprehensive and widely used national level map of semi-natural habitats in Wales. However, the survey was based largely on field survey and was conducted over several decades, before being completed in 1997. Given that resources for a repeat survey were limited, this study has used an object-orientated rule-based classification implemented within eCognition of multi-temporal satellite sensor data acquired between 2003 and 2006 to map semi-natural habitats and agricultural land across Wales, thereby allowing a progressive update of the Phase 1 Survey. The classification of objects to Phase 1 habitat classes was undertaken in two steps; firstly the landscape of Wales was divided into objects using orthorectified SPOT-5 High Resolution Geometric (HRG) reflectance data (10 m spatial resolution) and Land Parcel Information System (LPIS) boundaries. A rule-base was then developed to progressively discriminate and map the distribution of 105 sub-habitats across Wales based on time-series of SPOT HRG, Terra-1 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Indian Remote Sensing Satellite (IRS) LISS-3 data, derived datasets (e.g., vegetation indices, fractional images) and ancillary information (e.g., topography). The rules coupled knowledge of ecology and the information content of these remote sensing data using a combination of thresholds, Boolean operations and fuzzy membership functions. A second rule-base was then developed to translate the more detailed sub-habitat classification to Phase 1 habitat classes. Indicative accuracies of the revised Phase 1 mapping, based on comparisons with the later Phase 2 survey (for selected habitats), were >80% overall and typically between 70% and 90% for many classes. Through this exercise, Wales has become the first country in Europe to produce a national map of habitats (as opposed to land cover) through object-orientated classification of satellite sensor data. Furthermore, the approach can be adapted to allow continual monitoring of the extent and condition of habitats and agricultural land.     

警用GIS综合服务平台的设计与实现

针对现有公安部门GIS系统缺乏统一的、标准的空间信息和业务应用体系的状况,提出并设计了警用GIS综合服务系统,着重突出了地理信息与公安部门业务数据的集成共享和互操作,根据各个公安部门的业务需求,提供标准的接口,使系统具有可持续维护性,最后进行了功能层面的设计和实现。     

基于ArcEngine的基础地理信息系统的设计与实现

介绍了利用ArcEngine技术开发基础GIS软件的特点,重点讨论了在GIS软件中查询功能、缓冲区功能和注记随地图缩放功能的实现.     

基于GIS和景观生态学的土地整理景观研究

运用GIS技术和景观生态学理论方法,以安徽省淮南市潘集区市级投资重点土地整理项目为例,选取3类景观指标,对项目区内土地整理前后的土地利用现状和景观格局变化情况进行研究。结果表明： 景观类型中水田斑块占绝对优势,斑块分维数、形状指数呈下降趋势,表明斑块形状趋于规则和简单; 斑块数量和斑块密度降低,平均斑块面积和最大斑块面积增加,最大斑块指数增大,景观破碎度降低; 平均分维数和平均形状指数增大,表明景观形状较整理前变得规则,但总体形态变得复杂; 多样性指数和均匀度指数降低,表明在增加了景观分布均匀程度的同时降低了景观的多样性,景观类型有所减少。     

基于最小二乘法道路平面曲线拟合

结合最小二乘法的基本原理,利用其进行道路平面曲线拟合,实例表明,与三次样条函数设计计算结果接近,同样能满足路线设计要求,且简化了计算过程,在平面设计工作中具有很强的实用性。     

Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation

Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment.     

基于CJ-57编码的长江电子航道图研究

本文以长江数字航道与智能航运建设示范工程(南京至浏河口河段)为依托,介绍了国际标准电子海图的发展情况,着重阐述了基于S-57编码的长江内河电子航道图(iENCs)的关键技术,以保证长江电子航道图的生产、应用遵循相关国际标准,同时也尽量体现长江内河流域的航道特征。     

密度聚类算法在连续分布点云去噪中的应用

在原始测量获取的点云数据中,除了目标数据外,还有大量的噪声数据。噪声往往无规律地分布在目标物体周围,难以用统一数学模型区分。基于密度的聚类算法将簇定义为密度相连的点的最大集合,能发现任意形状、大小的类簇,将该算法应用在点云去噪中,能将密度分布连续点进行聚类,从中提取出目标点云。     

Evaluating a thermal image sharpening model over a mixed agricultural landscape in India

Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between the normalised difference vegetation index (NDVI) at fine spatial resolution and land surface temperature at coarse spatial resolution. The current study utilised the TsHARP model over a mixed agricultural landscape in the northern part of India. Five variants of the model were analysed, including the original model, for their efficiency. Those five variants were the global model (original); the resolution-adjusted global model; the piecewise regression model; the stratified model; and the local model. The models were first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) thermal data (90 m) aggregated to the following spatial resolutions: 180 m, 270 m, 450 m, 630 m, 810 m and 990 m. Although sharpening was undertaken for spatial resolutions from 990 m to 90 m, root mean square error (RMSE) of <2 K could, on average, be achieved only for 990–270 m in the ASTER data. The RMSE of the sharpened images at 270 m, using ASTER data, from the global, resolution-adjusted global, piecewise regression, stratification and local models were 1.91, 1.89, 1.96, 1.91, 1.70 K, respectively. The global model, resolution-adjusted global model and local model yielded higher accuracy, and were applied to sharpen MODIS thermal data (1 km) to the target spatial resolutions. Aggregated ASTER thermal data were considered as a reference at the respective target spatial resolutions to assess the prediction results from MODIS data. The RMSE of the predicted sharpened image from MODIS using the global, resolution-adjusted global and local models at 250 m were 3.08, 2.92 and 1.98 K, respectively. The local model consistently led to more accurate sharpened predictions by comparison to other variants.     

坐标转换中大地高对平面坐标和高程的影响

验证大地高的不确定性对高程的影响和对平面坐标的影响,为具体工程实际应用提供参考依据.通过改变选定的重合点上的大地高,求得两套转换参数,并比较这两套转换参数求得的高斯平面坐标.通过不同数据验证,得出结论.