复种指数遥感监测方法

复种指数是反映水土光与自然资源利用程度的指标 ,其实质是沿时间序列 ,反映某一种植制度对耕地的利用程度。联系复种指数与时间序列NDVI曲线的纽带是农作物年内的循环规律。时间序列的NDVI值蕴涵着植被的生长和枯萎的年循环节律 ,经时间序列谐函数分析法 (HarmonicAnalysisofTimeSeries ,HANTS)重构的NDVI曲线 ,可以准确地反映农作物的出苗、拔节、抽穗、收获等物理过程。因此 ,根据时间序列的NDVI曲线的周期性 ,可以反向捕捉到耕地农作物动态的信息 ,进而得到耕地的复种指数。本文依据上述原理 ,提出复种指数遥感监测的方法 ,然后用 1999年至 2 0 0 2年 4年的VGT(SPOT4卫星vegetation数据 )旬合成NDVI时间序列数据集提取了复种指数 ,并利用地面样区观测结果和统计数据进行检验 ,取得很高的精度。     

泰国水稻种植面积月变化的遥感监测

介绍了光学和微波遥感影像相结合进行泰国水稻种植面积监测方法。泰国雨季雨量充足 ,气温适合 ,同一时间耕地上水稻的物候多样 ,每月水稻种植面积都发生变化。利用旱季的TM影像 ,获得耕地信息。同时利用TM影像覆盖的雷达区域进行非耕地去除 ,进行非监督分类 ,提取反映水稻种植不同生长期的雷达影像后向反射系数特征 ,建立各种类型的分类模型 ,采用监督分类的方法对全景雷达数据进行水稻种植情况调查 ,并分别予以识别和统计 ,反映研究区水稻月种植情况。分类结果通过类别检验和面积量算检验进行精度评价和分析。     

铺就GIS全球化之路--解读g.net

介绍了g.net的体系结构,阐明了其特征和关键技术,以ArcGIS为例说明了它的具体实现,为实现地理信息和服务的全球化提供了可能.     

等高线拓扑关系的构建以及应用

提出了等高线拓扑关系的描述框架 ,其规范化描述形式具有更强的适用性 ,使用三角网作为工具设计了建立拓扑关系的算法。以提出的拓扑关系描述为基础 ,具体实现了等高线高程自动赋值 ,处理过程可以同时考虑开曲线 (包括断线 )和闭曲线 ,提高了可靠性和自动化程度 ,并进一步将断线连接为完整目标 ,减少了人机交互的编辑工作     

谈县级地震部门依法管理建设工程抗震设防要求

以山西省祁县依法管理工程抗震设防要求为例，论述了强制性审核、确定一般工业、民用建设工程抗震设防要求的重要性及其深远意义。结合工作实际．总结了部分依法行政、规范管理和落实抗震设防要求的经验。     

竖向地震动强度包络函数的空间变化规律

利用SMART 1台阵三次地震记录拟合了各个测点在地震中的竖向地震动强度包络曲线及Amin 和Ang的强度包络函数中各模型参数值,分析了各模型参数的空间变化规律,建立了各模型参数随二维空间坐标及土层厚度变化的随机模型,为多点地震动合成中竖向强度包络函数的计算提供了理论依据。     

震群精定位问题讨论

本文利用一组高精度数字记录台站在新西兰北岛附近观测得到的一个地震群资料,选用合适的地壳结构,合理控制造成误差的因素,应用偏振技术提高地震波震相判定的分辨率,最后反演计算获得震源的定位解.虽然这个震群仅发生在15 km长的小条形区域内,由于较高的定位精度,能较清晰地反映出火山地区地震活动的特点,尤其是深度分布图像表现了一种非任意性.     

Primary component analysis method and reduction of seismicity parameters

Introduction Data mining (SHAO and YU, 2003) is a new kind of technique developed with database and artificial intelligence in recent years, which processes the data in the database to abstract the im- plied and pre-unknown, but potentially useful information and knowledge from large amounts of incomplete, noisy, blurring and stochastic data. For data mining, data purging is an important link beforehand that includes eliminating noise, making up lost domain, and deleting ineffective data, as…     

Cause of winter gravity wave spectrum saturation

Gravity waves play a significant role in establishing the large-scale circulation and structure of the middle atmosphere. Through gravity wave saturation proc-esses, such motions are believed to cause turbulence, resulting in divergence of momentum flux and the diffusion of heat and constituents in the meso-sphere[1,2]. The mechanisms that contribute signifi-cantly to the gravity wave saturation are thought to be the dynamical and convective instabilities[3]. However, it is difficult to distin…     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".