基于关系数据库的邻接域处理

本文就跨图幅的地物(邻接域)的管理问题作了一些有益的探讨，为了达到有效管理这个目的，本文采用Oracle公司提供的空间数据插件Spatial将空间数据和属性数据存入Oracle数据库中，这样不仅可以通过标准SQL语句可下裁任意区域的数据，而且数据库还会自动维护数据的完整性。因此，用空间数据库的管理方式使邻接域问题就不存在了。     

Geostatistical approaches to refinement of digital elevation data

Data refinement refers to the processes by which a dataset’s resolution, in particular, the spatial one, is refined, and is thus synonymous to spatial downscaling. Spatial resolution indicates measurement scale and can be seen as an index for regular data support. As a type of change of scale, data refinement is useful for many scenarios where spatial scales of existing data, desired analyses, or specific applications need to be made commensurate and refined. As spatial data are related to certain data support, they can be conceived of as support-specific realizations of random fields, suggesting that multivariate geostatistics should be explored for refining datasets from their coarser-resolution versions to the finer-resolution ones. In this paper, geostatistical methods for downscaling are described, and were implemented using GTOPO30 data and sampled Shuttle Radar Topography Mission data at a site in northwest China, with the latter’s majority grid cells used as surrogate reference data. It was found that proper structural modeling is important for achieving increased accuracy in data refinement; here, structural modeling can be done through proper decomposition of elevation fields into trends and residuals and thereafter. It was confirmed that effects of semantic differences on data refinement can be reduced through properly estimating and incorporating biases in local means.     

面向高光谱图像分类的半监督空谱判别分析

为充分利用高光谱图像蕴藏的空间信息提升分类精度,提出了面向高光谱图像分类的半监督空谱判别分析(S3 DA)算法。考虑高光谱图像数据集的空间一致性,首先利用少量标记样本定义类内散度矩阵,保存数据集同类像元的光谱近邻结构;再利用无标记样本定义空间近邻像元散度矩阵,揭示像元间的空间近邻结构和地物的空间分布结构信息。S3 DA既保持数据集在光谱域的可分性,又保存了无标记样本蕴藏的空间域近邻结构,增强了同类像元和空间近邻像元在投影子空间的聚集性,从而提升分类性能。在PaviaU和Indian Pines数据集的试验表明,总体分类精度分别达到81.50%和71.77%。与传统的光谱方法比较,该算法能有效提升高光谱图像数据集的地物分类精度。     

美国空间规划体系的构建及启示

本文在分析美国空间规划及体系形成的基础上,从规划的法规体系、行政体系和运行体系三个方面阐述各级规划的法规、机构及规划类型,总结美国空间规划体系的特点,得出对我国空间规划体系构建的启示.     

Multi‐scale approach to mining significant spatial co‐location patterns

Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features, which are frequently located in close geographic proximity to each other. Existing methods for identifying spatial co‐location patterns usually require users to specify two thresholds, i.e. the prevalence threshold for measuring the prevalence of candidate co‐location patterns and distance threshold to search the spatial co‐location patterns. However, these two thresholds are difficult to determine in practice, and improper thresholds may lead to the misidentification of useful patterns and the incorrect reporting of meaningless patterns. The multi‐scale approach proposed in this study overcomes this limitation. Initially, the prevalence of candidate co‐location patterns is measured statistically by using a significance test, and a non‐parametric model is developed to construct the null distribution of features with the consideration of spatial auto‐correlation. Next, the spatial co‐location patterns are explored at multi‐scales instead of single scale (or distance threshold) discovery. The validity of the co‐location patterns is evaluated based on the concept of lifetime. Experiments on both synthetic and ecological datasets show that spatial co‐location patterns are discovered correctly and completely by using the proposed method; on the other hand, the subjectivity in discovery of spatial co‐location patterns is reduced significantly.     

高光谱影像数据预处理技术评价

高光谱影像数据预处理是构建高效的影像数据库以及实现地理目标成分信息反演与地理目标识别的基础。本文从反射率演算、光谱微分技术以及高光谱影像数据的降维处理等三个方面对高光谱影像数据预处理进行了研究。实现了基于高光谱影像的反射率反演算法，针对高光谱遥感数据影像分辨率比较低的现状，提出了直方图均衡化、色调平衡、对比度调整等影像处理算法，并给出了实验结果。     

BP神经网络模型在澜沧江流域径流量模拟中的应用

河川径流等水文时间序列属于复杂的非线性系统,使用回归分析等传统的分析方法,难以获取和描述其内在关联和变化规律。利用现有的相关站点的径流量历史数据和输沙量、降水量数据,在进行规格化处理和主成分分析的基础上,利用三层BP人工神经网络模型,对澜沧江流域上游昌都站径流量与各关联因子之间复杂的非线性映射关系进行模拟,采用拟牛顿算法对模型进行训练,模拟结果达到期望精度要求,并利用1982年~1985年实测数据进行模型验证。结果证明利用BP神经网络模型对澜沧江流域站点的月径流量序列进行模拟、预测和数据补缺处理具有可行性。     

基于MODIS数据的雪面温度遥感反演

On the basis of simplification of the Planck function in a low temperature range, this paper revises the practical split-window algorithm and presents a method for retrieving snow surface temperature （Ts） based on MODIS data in the middle-latitude region. The application of this method in Qinghai Lake region reveals that it is feasible for the retrieval of Ts. Results of correlation analysis indicate that there was strong negative relationship between Ts and altitude. By analyzing three typical areas in which land cover was relatively homogenous, this paper discusses the relationship between Ts and normalized difference snow index （NDSI） and then presents a new concept named ＂NDSI-Ts space＂.     

Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.     

近邻点指数法测度澜沧江流域居民地空间分布类型

居民地分布情况间接地映射着区域的经济发展与城市布局,为研究居民点的分布特征,采用聚落地理学的邻点指数方法测度。以澜沧江流域为例,对流域不同类型居民地以及流域所涉及不同地区的居民地的分布特征进行分析研究。