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卫星遥感技术在城市规划中的应用 总被引:22,自引:3,他引:22
对卫星遥感技术在城市规划中的应用进行了分析,包括城市空间布局信息分析(如城市建成区范围、城镇体系、城市内部用地结构、建筑密度与建筑容积率、城市环境污染等)、城市变化监测(城市扩展、土地利用/土地覆盖变化等)及规划实施情况检查(监测未经批准的建设工程及检查规划批准项目的落实情况),对应用的内容、方案及效果进行了总结和探讨。分析表明,遥感技术能为城市规划提供众多基础数据,具有广阔的应用前景,但不能完全代替地面调查。 相似文献
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本文简要地介绍了我国遥感技术的应用现状,回顾了遥感技术二十余年来在河北省有关领域的应用情况,客观地概括和总结了遥感技术在河北省国民经济可持续发展中发挥的重要作用和所取得的科研成果,并对今后河北省的遥感技术的发展和应用进行了展望。从河北省的实际情况出发,提出了进一步拓宽遥感技术应用领域,构建对地观测体系,有效监测资源环境动态变化,为河北省国民经济建设和可持续发展提供技术服务的可行性,为科技强省提供了高新科技基础保障。 相似文献
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河北省从2001年首次在土地资源调查监测中引入卫星遥感技术,开展了石家庄市土地利用卫星遥感动态监测试点研究。在试点经验的基础上,2005年部署开展了河北省土地利用遥感动态监测,对重点城市和县城开展了土地利用变化监测,构建全省土地利用遥感本底数据库。从2005年开始我省用三年时间,在全省组织实施了土地利用更新调查工作,其中遥感技术得到了更加广泛和深入的应用。本文着重分析遥感在土地调查中的作用、技术方法和流程,以及存在的主要问题,并结合未来遥感技术的发展和国家土地遥感工作的部署,对我省今后遥感技术在土地调查中应用前景作出展望。 相似文献
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遥感技术在华北平原地下水资源潜力调查评估中的试点应用 总被引:1,自引:0,他引:1
在地下水资源日趋缺乏的太行山前河北平原,采用遥感技术开展地下水资源调查评价.在充分利用卫星遥感(ETM+)图像数据反映地下水资源相关信息灵敏的基础上,综合其他常规资料,准确的圈定出山前冲洪积扇的范围,划分出它们的形成期次和扇体结构.明晰了不同河流扇体之间和同一河流不同期次扇体之间的空间交叠关系,恢复了主要河流的水流系统.详细解译出其他如古河道、地下水浅埋区、地下水溢出区、决口扇、消亡湖泊及其古三角洲等水文地质要素.在此基础上,推测出具有开采潜力的地下水富水区6处.在对其中的两处进一步开展详细的水文地质勘察后,被有关部门确认为极具开采潜力,可做为大型城市供水水源地. 相似文献
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陕西省遥感技术的应用起步早、发展快、力量雄厚。近年来,以省遥感中心为核心,逐步形成了推进追感技术广泛应用的产业集团,编制完成了“陕西省国土资源遥感系列图”等国家重点项目,为扔国国土资源调查作出了贡献。并提出应立足陕西,面向国内外,参与竟争,发展遥感技术产业。 相似文献
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自2001年我省首次应用遥感技术对石家庄市土地利用变化状况进行遥感动态监测以来,河北省国土资源厅连续几年在此方面作了大量的工作,并取得了显著的成效。目前,应用遥感技术对土地利用情况进行动态监测,已经成为我省土地资源管理中实行业务化和常规化运行的重要手段。本文就遥感技术在土地资源管理中的应用、土地利用动态遥感监测的技术路线和方法、遥感技术在土地资源管理中的应用前景以及今后需要研究和解决的主要问题做一简要介绍。 相似文献
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卫星遥感技术应用在高压输电选线中, 具有常规方法无法比拟的优势。在西北-华北500 KV高压直流输电线路工程的宁-蒙-陕段的选线研究中, 通过对多时相遥感数据处理, 获取了研究区内的地质、地貌等相关信息, 并分析了沿线沙地的动态演化及分布规律。研究结果表明, 区域沙丘属于半固定沙丘, 移动速度缓慢, 全区的沙化地总体表现为负增长。尤其是基于地形图等高线要素获取数字高程模型(DEM ) , 对研究区进行三维虚拟地理景观可视化模拟, 并利用相应的遥感图像进行叠加复合, 获取真实三维地表景观, 提高可视化效果。在此基础上通过综合分析区内地形、地貌、工程地质、岩性构造、地理条件及居民地分布等相关因素, 提出了两套选线方案作对比分析, 为高压输电线选线方案的最终确立提供了科学依据。 相似文献
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遥感技术在生态环境治理工程中应用的初步分析 总被引:2,自引:0,他引:2
以甘肃省中部地区生态环境治理工程重点区域为研究对象,以1990年陆地卫星TM影像遥感解译结果为生态环境本底数据,以2000年同一季节TM影像资料解译结果为现状数据,结合数字地形模型和实地调查结果,对该地区的生态环境进行动态监测。监测结果表明:虽然在研究区内采取了退耕还林、小流域综合治理等改善生态环境的种种措施,环境依然趋向恶化。分析了1990年到2000年10年间生态环境变化的原因,并提出相应的对策建议,为农业结构调整、生态环境建设等提供科学依据。 相似文献
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介绍利用GIS,RS和计算机技术,通过对TM卫星影像进行解译处理,结合地面调查数据,在ERDAS IMA GINE和ARC/INFO系统支持下,实现对水稻进行估产,建立适合对农作物估产的模型。 相似文献
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Maps of burned area have been obtained from an automatic algorithm applied to a multitemporal series of Landsat TM/ETM+ images in two Mediterranean sites. The proposed algorithm is based on two phases: the first one intends to detect the more severely burned areas and minimize commission errors. The second phase improves burned patches delimitation using a hybrid contextual algorithm based on logistic regression analysis, and tries to minimize omission errors. The algorithm was calibrated using six study sites and it was validated for the whole territory of Portugal (89,000 km2) and for Southern California (70,000 km2). In the validation exercise, 65 TM/ETM+ scenes for Portugal and 35 for California were used, all from the 2003 fire season. A good agreement with the official burned area perimeters was shown, with kappa values close to 0.85 and low omission and commission errors (< 16.5%). The proposed algorithm could be operationally used for historical mapping of burned areas from Landsat images, as well as from future medium resolution sensors, providing they acquire images in two bands of the Short Wave Infrared (1.5-2.2 μm). 相似文献
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随着遥感技术的发展,获取遥感数据的手段越来越丰富,各种不同的传感器所获取的影像数据与日俱增,在同一地区形成了多时相、多分辨率的影像序列金字塔。如何综合各种类型的遥感影像信息,提高遥感数据的利用效益已成为遥感应用的瓶颈问题。多源遥感数据融合技术是解决这一问题的有效手段,即将同一地区不同类型的影像数据进行空间配,然后采用一定的算法将各种影像数据中所含的信息优势或互补性有机的结合起来,产生新影像的过程。以Landsat和SPOT数据为例进行了这方面的探讨。为了充分利用TM丰富的光谱信息和SPOT较高的空间分辨率,研究中引入了4种影像融合算法:加权融合、K-L变换、K-T变换、基于信息特征的融合。通过信息量和分类精度的比较,表明基于信息特 的融合效果较好。 相似文献
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During the last few decades, many regions have experienced major land use transformations, often driven by human activities. Assessing and evaluating these changes requires consistent data over time at appropriate scales as provided by remote sensing imagery. Given the availability of small and large-scale observation systems that provide the required long-term records, it is important to understand the specific characteristics associated with both observation scales. The aim of this study was to evaluate the potentials and limits of remote sensing time series for change analysis of drylands. We focussed on the assessment and monitoring of land change processes using two scales of remote sensing data. Special interest was given to the influence of the spatial and temporal resolution of different sensors on the derivation of enhanced vegetation related variables, such as trends in time and the shift of phenological cycles. Time series of Landsat TM/ETM+ and NOAA AVHRR covering the overlapping time period from 1990 to 2000 were compared for a study area in the Mediterranean. The test site is located in Central Macedonia (Greece) and represents a typical heterogeneous Mediterranean landscape. It is undergoing extensification and intensification processes such as long-term, gradual processes driven by changing rangeland management and the extension of irrigated arable land. Time series analysis of NOAA AVHRRR and Landsat TM/ETM+ data showed that both sensors are able to detect this kind of land cover change in complementary ways. Thereby, the high temporal resolution of NOAA AVHRR data can partially compensate for the coarse spatial resolution because it allows enhanced time series methods like frequency analysis that provide complementary information. In contrast, the analysis of Landsat data was able to reveal changes at a fine spatial scale, which are associated with shifts in land management practice. 相似文献
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Based on very high resolution satellite images, object-based classification methods can be used to produce large scale maps for forest management. These new products require a method to derive quantitative information about the accuracy and precision of delineated boundaries. This assessment would complement any measure of thematic accuracy derived from the confusion matrix. This study aims to assess the positional quality of the boundaries between different landscape units produced by automated segmentation of IKONOS and SPOT-5 satellite images over temperate forests. A robust method was developed to assess the accuracy and the precision of the forest boundaries, respectively measured by the bias and the standard deviation. The two main sources of positional error, namely residual parallax and automatic segmentation, were independently assessed. Positional errors caused by the residual parallax were quantified using a 3D model. Forest stand boundaries generated by automatic segmentation were compared to corresponding visual delineations. The results showed that residual parallax was the major source of positive bias (area overestimation) along forest/non-forest boundaries and depended on the interactions between forest stand patterns and sensor viewing angles. Due mainly to tree shade, the automatic segmentation also produced a positive bias on forest areas, which remained under 1 m for both IKONOS-2 and SPOT-5 images. Standard deviation did not increase linearly with pixel size and was influenced by the nature of the boundary. Production of 1:20,000 scale forest maps from very high resolution satellite data clearly requires acquisition of near nadir imagery or knowledge of landscape object height for true orthorectification. In these cases, IKONOS-2 segmentation outputs were found to correspond with 1:20,000 scale map specification, and SPOT-5 imagery with 1:30,000 scale. 相似文献