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本文运用生态经济学原理,以黑龙江省东部低山丘陵区的光恩乡建设果林工程的经验为实例,分析寒地山区果林工程建设的生态、经济、社会效益。结果表明,果林工程是山区水土流失快速治理,自然资源合理开发利用,摆脱林业资源危机和经济危机,加快群众致富奔小康的有效途径,具有广阔的推广应用前景。 相似文献
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Native antioxidants (AO) are involved in the transformation of organic matter (OM) in different stages of diagenesis. In the early stages, the geochemical significance of AO can be estimated by using AO consumption index (I). The positive I values suggest that the OM fossilization proceeded under reducing conditions which favoured the formation of oil-source rocks, while the negative I values indicate oxidizing conditions which are characterized by the formation of rocks having a low oil-generation potential. In the late stages of diagenesis, the AO content is indicative of the degree of catagenic (thermal) or biodegradation (oxidative) transformation of oils. The AO contents of Paleogenic, Mesozoic and Paleozoic oils have been found to differ approximately by one order of magnitude. A major portion of AO is concentrated in oil resins and asphaltenes. The ratio of AO to resins and asphaltenes can be used as criterion of catagenic transformation of OM. 相似文献
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在旅游业发展影响下,丽江古城传统纳西古乐的主体地位迅速地被现代民谣音乐所取代。音乐是地方文化的重要组成部分,地方音乐的变化折射出地方文化的整体变迁。本文利用观察法、文本分析法对丽江古城的地方音乐形式、表达内容及展演场所进行调查,采用访谈法对音乐表演者、经营者与游客进行了深入的采访。研究发现:在旅游影响下,原本作为本地居民精神伴侣、融入在地方社会生活中的传统古乐转变为服务于游客的各类商业演艺活动,在场所和游客认同方面表现出“不得其所”的特征;而以现代民谣音乐为代表的流行音乐成为丽江古城的主流音乐形式,在丽江古城中“安适其位”。传统古乐建构了丽江古城的独特感,激发了游客的异乡感,现代民谣音乐更加渲染了丽江古城的“小资情调”,两种音乐均在游客的情感建构中起到了重要作用。研究旨在丰富旅游地文化变迁的研究视角,反思旅游与地方传统文化的关系,亦是对音乐与地方人地关系研究成果的有益拓展与补充。 相似文献
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山西省古村落的空间分布与演化研究 总被引:4,自引:2,他引:2
以山西省303个国家级和省级历史名村和传统村落为研究对象,采用历史时间断面方法、历史文献分析方法与GIS空间分析方法,对其空间分布与演化进行分析,结果表明:山西省古村落的形成与区域开发进程密切相关,宋代以前形成的主要分布在晋南,宋元时期形成的主要分布在晋中,明清时期形成的仍以晋中为主但晋北比重明显上升,整个历史时期总体上有由南向北推进的时序。山西古村落具有“聚盆、近水、沿边、偏中南”的空间分布特征,63.70%分布于盆地地区,67.66%分布于距河流10 km的地域,50.50%分布于省界四边的县域,晋中、晋南又分别集中了41.58%和43.89%。山西古村落主要有农耕、商贸、军事、工矿4种类型,农耕型和商贸型的分布由晋南向晋北递减,军事型的分布由晋北向晋南递减,工矿型集中分布于晋南。303个古村落中,46.53%在历史时期发生过转型,转型主要发生在明清时期,转型方式主要是农耕型转商贸型、军事型、工矿型以及军事型转商贸型、农耕型。总之,山西古村落的时空演化揭示了其由晋南向晋北、由平原向山区、由中原向塞外的区域开发过程。 相似文献
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Mangrove forests grow in intertidal zones in tropical and subtropical regions and have suffered a dramatic decline globally over the past few decades. Remote sensing data, collected at various spatial resolutions, provide an effective way to map the spatial distribution of mangrove forests over time. However, the spectral signatures of mangrove forests are significantly affected by tide levels. Therefore, mangrove forests may not be accurately mapped with remote sensing data collected during a single-tidal event, especially if not acquired at low tide. This research reports how a decision-tree −based procedure was developed to map mangrove forests using multi-tidal Landsat 5 Thematic Mapper (TM) data and a Digital Elevation Model (DEM). Three indices, including the Normalized Difference Moisture Index (NDMI), the Normalized Difference Vegetation Index (NDVI) and NDVIL·NDMIH (the multiplication of NDVIL by NDMIH, L: low tide level, H: high tide level) were used in this algorithm to differentiate mangrove forests from other land-cover and land-use types in Fangchenggang City, China. Additionally, the recent Landsat 8 OLI (Operational Land Imager) data were selected to validate the results and compare if the methodology is reliable. The results demonstrate that short-term multi-tidal remotely-sensed data better represent the unique nearshore coastal wetland habitats of mangrove forests than single-tidal data. Furthermore, multi-tidal remotely-sensed data has led to improved accuracies using two classification approaches: i.e. decision trees and the maximum likelihood classification (MLC). Since mangrove forests are typically found at low elevations, the inclusion of elevation data in the two classification procedures was tested. Given the decision-tree method does not assume strict data distribution parameters, it was able to optimize the application of multi-tidal and elevation data, resulting in higher classification accuracies of mangrove forests. When using multi-source data of differing types and distributions to map mangrove forests, a decision-tree method appears to be superior to traditional statistical classifiers. 相似文献
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In order to evacuate residents in time, flood warning systems must have rapid data processing algorithms to translate detailed numerical data into simple warnings and navigation aids. Although it is common to display warning messages by directly drawing red circles on a map embedded in a Web page to indicate the regions about to be inundated, such an approach has some drawbacks. We propose an alternative way by summarizing the warning messages based on landmarks, so that the messages can be short and convey even more information. We have designed two approaches to output such messages. They are the nearest landmark approach and the threshold approach, which differ in the way of determining which landmarks will be influenced by a certain flooded region. These two methods are implemented and we compare their performance through real and synthetic datasets. Experimental results show that the threshold approach usually takes less execution time than the nearest landmark approach. Its severity ranking of landmarks is also better suited to human behaviour. 相似文献