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作物胁迫无人机遥感监测研究评述 总被引:1,自引:0,他引:1
作物胁迫是全球农业发展的一个重要制约因素,实现快速、大范围、实时的作物胁迫监测对于农业生产具有重要意义。传统的作物胁迫监测方式,如田间调查、理化检测和卫星遥感监测总是受到各种田间条件或大气条件的制约。随着无人机和各种轻量化传感器的快速发展,其凭借高频、迅捷等优势为各种作物胁迫监测提供了一套全新的解决方案。本文在介绍了目前主流的多种无人机和传感器的基础上,首先对目前无人机遥感用于作物监测的主要胁迫类型进行了梳理,然后重点阐述了基于光谱成像和热红外传感器进行作物胁迫无人机遥感监测的应用和技术方法,最后提出了作物胁迫无人机遥感监测尚需解决的关键问题,并展望了未来无人机遥感用于作物胁迫监测的前景。 相似文献
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针对高精度GNSS定向应用场景,通过实验对比对低成本单频u-blox接收机的数据质量和解算精度。结果表明,u-blox接收机GPS、BDS观测值的信噪比略低于测量型接收机;伪距精度分别为0.91 m、0.56 m,相位精度分别为1.35 cm、1.20 cm。在静态观测环境下,u-blox的定向精度可以达到航向0.2°/m和俯仰0.4°/m;动态环境下解算结果稍差,但也可以达到航向0.3°/m和俯仰0.6°/m,略低于高成本测量型接收机单频数据的实时动态定向精度。 相似文献
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Catia Real Ehrlich 《地球空间信息科学学报》2019,22(2):73-88
ABSTRACTThe localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented. 相似文献
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为解决三杯风速传感器在计量检定条件下与观测场景中环境差异所导致的测量数据误差,致力于研究空气流速计量标准在量值传递过程中的真实性、准确性和一致性,为新一代三杯风速传感器作为计量器具的新产品型式评价提供思路和参考指标,依据杯式测风仪测量方法与自动气象站风速风向传感器检定规程,并在实验中加入了主体由角度编码器构成的自动化转盘系统,设计了三杯风速传感器在非水平风场内测量性能水平实验。通过调整三杯风速传感器在风洞试验段内的倾斜角度,模拟其在自然界非水平风场中的测量状态,同步采集风洞的标准指示风速、三杯风速传感器的实测风速以及其相应的倾斜角度,计算示值误差,利用方差分析、趋势分析、相关性分析和线性回归分析等统计方法,对不同倾斜角度下三杯风速传感器示值误差进行研究,得出了三杯风速传感器在风洞试验段内的示值误差与实测风速和倾斜角度之间的相关关系,提出了三杯风速传感器在非水平风场下的测量性能指标。研究了三杯风速传感器在非水平风场中实测风速与标准风速和倾斜角度的回归关系,提出了三杯风速传感器在计量环境下非水平风场中数据的量值传递修正算法。 相似文献
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Calibrating the GOCE accelerations with star sensor data and a global gravity field model 总被引:1,自引:0,他引:1
A reliable and accurate gradiometer calibration is essential for the scientific return of the gravity field and steady-state
ocean circulation explorer (GOCE) mission. This paper describes a new method for external calibration of the GOCE gradiometer
accelerations. A global gravity field model in combination with star sensor quaternions is used to compute reference differential
accelerations, which may be used to estimate various combinations of gradiometer scale factors, internal gradiometer misalignments
and misalignments between star sensor and gradiometer. In many aspects, the new method is complementary to the GOCE in-flight
calibration. In contrast to the in-flight calibration, which requires a satellite-shaking phase, the new method uses data
from the nominal measurement phases. The results of a simulation study show that gradiometer scale factors can be estimated
on a weekly basis with accuracies better than 2 × 10−3 for the ultrasensitive and 10−2 for the less sensitive axes, which is compatible with the requirements of the gravity gradient error. Based on a 58-day data
set, scale factors are found that can reduce the errors of the in-flight-calibrated measurements. The elements of the complete
inverse calibration matrix, representing both the internal gradiometer misalignments and scale factors, can be estimated with
accuracies in general better than 10−3. 相似文献
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