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11.
Knowledge of seasonal variation of net ecosystem CO2 exchange (NEE) and its biotic and abiotic controllers will further our understanding of carbon cycling process, mechanism and large-scale modelling. Eddy covariance technique was used to measure NEE, biotic and abiotic factors for nearly 3 years in the hinterland alpine steppe--Korbresia meadow grassland on the Tibetan Plateau, the present highest fluxnet station in the world. The main objectives are to investigate dynamics of NEE and its components and to determine the major controlling factors. Maximum carbon assimilation took place in August and maximum carbon loss occurred in November. In June, rainfall amount due to monsoon climate played a great role in grass greening and consequently influenced interannual variation of ecosystem carbon gain. From July through September, monthly NEE presented net carbon assimilation. In other months, ecosystem exhibited carbon loss. In growing season, daytime NEE was mainly controlled by photosynthetically active radiation (PAR). In addition, leaf area index (LAI) interacted with PAR and together modulated NEE rates. Ecosystem respiration was controlled mainly by soil temperature and simultaneously by soil moisture. Q10 was negatively correlated with soil temperature but positively correlated with soil moisture. Large daily range of air temperature is not necessary to enhance carbon gain. Standard respiration rate at referenced 10℃(R10) was positively correlated with soil moisture, soil temperature, LAI and aboveground biomass. Rainfall patterns in growing season markedly influenced soil moisture and therefore soil moisture controlled seasonal change of ecosystem respiration. Pulse rainfall in the beginning and at the end of growing season induced great ecosystem respiration and consequently a great amount of carbon was lost. Short growing season and relative low temperature restrained alpine grass vegetation development. The results suggested that LAI be usually in a low level and carbon uptake be relatively low. Rainfall patterns in the growing season and pulse rainfall in the beginning and at end of growing season control ecosystem respiration and consequently influence carbon balance of ecosystem.  相似文献   
12.
基于植被-土壤二向反射模型的土壤含水量遥感   总被引:1,自引:0,他引:1  
以北京地区为例,利用像元信息分解法,定量提取出区域植被盖度,由植被盖度得到区域叶面积指数,在只考虑一次散射的情况下,利用植被-土壤二向反射模型,提取出下层湿润土壤反射率。通过引入粗糙度因子建立起粗糙地表下土壤反射率与叶面积指数的函数关系,进而得出土壤含水量。  相似文献   
13.
首先,利用辐射传输方程对微波极化指数(MPI,Microwave Polarization Index)进行推导,以AMSR-E像元经纬度为控制条件,采集与之对应的MODIS植被指数( LAI/NDVI),并将其平均值作为AMSR-E对应像元的值; 然后,对AMSR-E微波极化指数与LAI/NDVI进行相关分析。结果表明,MPI与LAI/NDVI之间存在着指数关系,而且频率越低,相关性越好。  相似文献   
14.
Optimizing nitrogen (N) fertilization in crop production by in-season measurements of crop N status may improve fertilizer N use efficiency. Hyperspectral measurements may be used to assess crop N status by estimating leaf chlorophyll content. This study evaluated the ability of the PROSAIL canopy-level reflectance model to predict leaf chlorophyll content. Trials were conducted with two potato cultivars under different N fertility rates (0–300 kg N ha−1). Canopy reflectance, leaf area index (LAI) and leaf chlorophyll and N contents were measured. The PROSAIL model was able to predict leaf chlorophyll content with reasonable accuracy later in the growing season. The low estimation accuracy earlier in the growing season could be due to model sensitivity to non-homogenous canopy architecture and soil background interference before full canopy closure. Canopy chlorophyll content (leaf chlorophyll content × LAI) was predicted less accurately than leaf chlrophyll content due to the low estimation accuracy of LAI for values higher than 4.5.  相似文献   
15.
基于PROSPECT+SAIL模型的遥感叶面积指数反演   总被引:4,自引:1,他引:4  
以PROSPECT+SAIL模型为基础,从物理机理角度反演植被叶面积指数(LAI)。首先,通过FLAASH模型进行大气校正,使得图像像元值表达植被冠层反射率; 然后,根据LOPEX 93数据库和JHU光谱数据库选择植物生化参数和光谱数据,以PROSPECT模型模拟出的植物叶片反射率和透射率作为SAIL模型的输入参数,得到植被冠层反射率,将结果与遥感影像的植被冠层反射率对应,回归出植被LAI; 最后,以地面实测数据对遥感反演数据进行验证,并分析了误差的可能来源。  相似文献   
16.
基于高光谱数据的叶面积指数监测是快速获取冬小麦叶面积指数的重要方法。为了探究回归方法和高光谱数据变换对冬小麦叶面积指数反演精度的影响,采用逐步回归和偏最小二乘回归方法,分别建立基于冬小麦拔节期冠层高光谱数据、一阶导数光谱数据、二阶导数光谱数据和对数光谱数据的叶面积指数多元线性回归模型。结果显示,导数和对数变换能够提高冬小麦LAI反演精度,以蓝紫光、绿光、红光和近红外波段建立的一阶导数光谱数据逐步回归模型最优,建立回归模型的决定系数R2为0.974,交叉验证的RMSE为0.131,可为冬小麦LAI估算的方法选择和数据处理提供依据和参考。  相似文献   
17.
Accurate representation of leaf area index (LAI) from high resolution satellite observations is obligatory for various modelling exercises and predicting the precise farm productivity. Present study compared the two retrieval approach based on canopy radiative transfer (CRT) method and empirical method using four vegetation indices (VI) (e.g. NDVI, NDWI, RVI and GNDVI) to estimate the wheat LAI. Reflectance observations available at very high (56 m) spatial resolution from Advanced Wide-Field Sensor (AWiFS) sensor onboard Indian Remote Sensing (IRS) P6, Resourcesat-1 satellite was used in this study. This study was performed over two different wheat growing regions, situated in different agro-climatic settings/environments: Trans-Gangetic Plain Region (TGPR) and Central Plateau and Hill Region (CPHR). Forward simulation of canopy reflectances in four AWiFS bands viz. green (0.52–0.59 μm), red (0.62–0.68 μm), NIR (0.77–0.86 μm) and SWIR (1.55–1.70 μm) were carried out to generate the look up table (LUT) using CRT model PROSAIL from all combinations of canopy intrinsic variables. An inversion technique based on minimization of cost function was used to retrieve LAI from LUT and observed AWiFS surface reflectances. Two consecutive wheat growing seasons (November 2005–March 2006 and November 2006–March 2007) datasets were used in this study. The empirical models were developed from first season data and second growing season data used for validation. Among all the models, LAI-NDVI empirical model showed the least RMSE (root mean square error) of 0.54 and 0.51 in both agro-climatic regions respectively. The comparison of PROSAIL retrieved LAI with in situ measurements of 2006–2007 over the two agro-climatic regions produced substantially less RMSE of 0.34 and 0.41 having more R2 of 0.91 and 0.95 for TGPR and CPHR respectively in comparison to empirical models. Moreover, CRT retrieved LAI had less value of errors in all the LAI classes contrary to empirical estimates. The PROSAIL based retrieval has potential for operational implementation to determine the regional crop LAI and can be extendible to other regions after rigorous validation exercise.  相似文献   
18.
Short-term earthquake prediction: Current status of seismo-electromagnetics   总被引:3,自引:0,他引:3  
Loss of human lives as a result of earthquakes is caused overwhelmingly by the collapse of buildings within less than a few minutes of main shocks. The most urgent countermeasure consists of two key elements. One is strengthening of weak structures and the other is short-term earthquake prediction. Short-term prediction needs precursors. Although some promising precursors are reported, the prevailing views in Japan and elsewhere are overly pessimistic. The pessimism largely roots in the fact that short-term precursors are generally non-seismic and tools developed for seismology are not designed to detect them. Nonetheless, nationally funded large-scale earthquake prediction programs always emphasize the need to reinforce seismometer networks. They do not take into account the views of those in the science community who point to the importance of non-seismic precursors. While there are well-founded causes to be skeptical, the situation needs to be improved. One reason for skepticism is that the observations of precursors have not yet been perfect enough and another is that some important fundamental aspects of non-seismic precursors are still unresolved. We review some of these problems.  相似文献   
19.
利用遥感数据,以异于传统的点分析的方法,分析水热条件对植被的影响。以青藏高原为研究区域,利用2003年的遥感数据 进行分析,结果表明,在时间轴上,叶面积指数和温度、土壤水分、降雨存在着良好的相关性; 在空间分布上,叶面积指数和三 者的相关性在大部分区域是呈良好的正相关,在部分区域呈现了弱相关和负相关,且分析探讨了出现这种现象的原因。  相似文献   
20.
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