高分辨率遥感影像在城市绿地信息提取中的应用研究

高分辨率卫星遥感图像数据量大、空间分辨率高、结构信息复杂、地物同物异谱现象更为突出等特征给专题信息提取技术带来了新的挑战。基于植被的光谱特征,利用监督分类、植被指数分类和目视解译等方法对QuickBird高分辨率卫星遥感影像的绿地信息进行提取,并对分类精度作了比对分析。研究结果表明,监督分类方法不能得到令人满意的结果,运用植被指数分类方法则有明显改善,其中归一化植被指数(NDVI)精度最高,因此NDVI能有效地对植被进行分类与识别。     

QuickBird影像融合最佳波段选择及不同融合方法质量评价研究

分析了QuickBird多光谱遥感影像各个波段的光谱特征,并进行了定量评价。根据信息量的大小和波段相关性得到最佳波段组合,在最佳组合波段下利用遥感影像处理软件ERDAS9.2选择或利用建模模块建立不同的影像融合模型对QuikBird多光谱数据与全色遥感影像进行融合,按照定性及定量指标对融合前后的遥感影像进行色彩、分辨率及信息量评价,得到QuikBird影像数据最佳融合方法。     

Evaluation of non-point source pollution reduction by applying Best Management Practices using a SWAT model and QuickBird high resolution satellite imagery

This study evaluated the reduction e ect of non-point source pollution by applying best management practices (BMPs) to a 1.21 km2 small agricultural watershed using a SWAT (Soil andWater Assessment Tool) model. Two meter QuickBird land use data were prepared for the watershed. The SWAT was calibrated and validated using daily streamflow and monthly water quality (total phosphorus (TP), total nitrogen (TN), and suspended solids (SS)) records from 1999 to 2000 and from 2001 to 2002. The average Nash and Sutcli e model e ciency was 0.63 for the streamflow and the coe cients of determination were 0.88, 0.72, and 0.68 for SS, TN, and TP, respectively. Four BMP scenarios viz. the application of vegetation filter strip and riparian bu er system, the regulation of Universal Soil Loss Equation P factor, and the fertilizing control amount for crops were applied and analyzed.     

基于GIS与QuickBird影像的小流域土壤侵蚀定量评价

基于GIS技术和QuickBird遥感影像,采用修正的通用土壤流失方程RUSLE作为评价模型,计算了清水沟小流域土壤侵蚀量,并结合土壤侵蚀强度分级标准,生成流域土壤侵蚀强度等级图;利用GIS的叠置分析功能,定量分析了土壤侵蚀与坡度和土地利用之间的关系,并针对不同水保措施预测了水土保持治理效果.结果表明清水沟小流域土壤侵蚀模数为75.02 t·hm-2·a-1,属强度侵蚀区,年水土流失量2.6×104 t;流域64.5%的泥沙来自于占流域面积仅28%的极强度和剧烈侵蚀区域;经分析,流域土壤侵蚀模数与坡度呈显著正相关,不同土地利用类型的土壤侵蚀模数大小排序依次为难利用地＞建设用地＞坡耕地＞园地＞草地＞林地;退耕还林是降低土壤侵蚀强度与减少水土流失量的主要途径.     

Mapping giant salvinia with satellite imagery and image analysis

QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands), normal color (blue, green and red bands), and four-band composite (blue, green, red, and near-infrared bands) images were studied. Unsupervised image analysis was used to classify the imagery. Accuracy assessments performed on the classification maps of the three composite images had producer’s and user’s accuracies for giant salvinia ranging from 87.8 to 93.5%. Color-infrared, normal color, and four-band satellite imagery were excellent for distinguishing giant salvinia in a complex field habitat.     

甘肃省小柳沟铜钨矿区矿山环境遥感调查与监测

采用遥感和GIS技术,利用两个时相的QuickBird-2和SPOF-5影像对甘肃省小柳沟铜钨矿区2003—2008年矿产资源开发现状与矿山环境进行了遥感调查、监测研究与野外验证,结果表明:小柳沟矿区矿产资源开发总数量和总面积呈现大幅上升趋势,开采面积和矿产开发占地分别从21 587.91 m2、133 517.67 m2增加了151 535.82 m2和537 437.26 m2,其中矿石堆、工矿用地、尾矿库面积分别增加了8.3倍、7.5倍、6.2倍;矿区新构造运动和泥石流活动较强,矿业开发产生的大量废弃物对矿山环境构成了较大的威胁,在暴雨、构造活动等外界因素的诱发下,极易发生新的泥石流、滑坡等灾害。