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1.
利用2003年1月至2012年4月间109个月的GRACE时变卫星重力数据,反演得到了长江流域的陆地水储量变化,并对三个典型区域的水储量变化做了分析。结果显示GRACE数据能有效揭示长江流域水储量变化的季节性变化及其长期的变化趋势,流域内的水储量变化受气候因素的影响较大。 相似文献
2.
3.
青藏高原及其周边地区水储量变化的独立成分分析 总被引：1，自引：1，他引：0
采用2003年1月至2013年12月共132个月的GRACE卫星数据反演得到的水储量变化信息,利用独立成分分析方法将水储量变化信息分解成多个信号成分,然后与NOAH和WGHM两个水文模型的分析结果进行比较。成分对比结果表明,GRACE反演得到的水储量变化与NOAH和WGHM水文模型在第一个主成分方面符合很好,相关系数分别是0.884和0.877。说明GRACE反演的水储量变化和水文模型在青藏高原及其周边区域具有很强的一致性。从空间模式上看,GRACE反演水储量变化信号的强度比水文模型信号要大,可能与GRACE反演的水储量变化还包括地下水的变化情况等有关。 相似文献
4.
针对京津冀地区水资源灾害频发、水储量监测手段存在局限性的问题,本文利用该地区2015年1月至2017年6月的重力场恢复与气候实验（GRACE）月重力场模型数据反演陆地水储量变化信息,结合区域降水、全球陆地资料同化系统（GLDAS）模型数据,对研究区域内水储量变化时空特征进行相关性分析。结果表明：GRACE监测的陆地水储量变化滞后降水2个月达到强相关性,监测到2016年春旱灾害的发生,扣除季节项影响后,GRACE&GLDAS相关系数为0.88,研究区陆地水储量上升速率为0.118 mm/a。研究结果可为该区域水储量时空调配、旱涝灾害防治提供理论依据。 相似文献
5.
为了实现科尔沁沙地的水资源监测,该文采用2003年7月至2010年12月的GRACE月重力场模型,经过去相关滤波、高斯平滑滤波和GIA改正,利用尺度因子法恢复重力场信号,反演科尔沁沙地的陆地水储量变化,与CPC水文模型反演结果进行对比分析。研究结果表明:由GRACE Release-05Level-2数据反演得到的2003年7月至2010年12月科尔沁沙地陆地水储量下降速率为-13.2±2.6(mm·a^-1);CPC水文模型反演的该地区陆地水储量变化曲线与GRACE反演结果呈现出良好的一致性,具有相似的季节变化;2009年秋至2010年春该地区陆地水储量呈现直线减少,并达到最低点,这一现象与该时段中国北方的干旱事件相一致。 相似文献
6.
《武汉大学学报(信息科学版)》2020,(1)
青藏高原水资源对我国经济社会发展及气候变化影响深远。借助重力反演与气候实验(gravity recovery and climate experiment, GRACE)卫星重力数据,针对其滤波泄漏误差影响,采用Forward-Modeling方法进行定量估算。在顾及冰川均衡调整(glacial isostatic adjustment, GIA)效应情况下,反演青藏高原水储量变化,将结果与全球水评估与预测模型(water-global assessment and prognosis hydrology model, WGHM)进行比较分析。利用短时傅里叶变换提取时序信号的时频谱特征,并结合全球降水气候中心(global precipitation climatology centre, GPCC)降水数据探讨水储量与降水的关系。研究发现:(1)恢复泄漏信号后水储量变化呈现明显的空间差异性,大部分时段青藏高原正北和东南部水储量大幅盈余,正南和西南部水储量快速亏损,其空间特征与WGHM模型结果基本一致。(2)水储量时频谱分布以低频信号为主,其动态变化具有明显的季节性和阶段性变化,周年振幅达到7.5 cm。2003—2004年水储量增加速率为(3.9±4.9)cm/a;2005—2010年亏损速率为(-0.3±0.8)cm/a;2011—2014年上升速率为(0.2±1.6)cm/a。(3)降水是影响陆地水储量变化的主要因素,在降水明显偏少的2006年和2009年,水储量均存在明显负异常;在降水偏多的2010年,水储量显著回升。实验证明,该泄漏误差改正方法和研究结果对于区域水储量变化的定量研究具有重要参考价值。 相似文献
7.
针对GRACE与GRACE-FO卫星存在衔接空白且卫星加速度计已出现受损的情况，SWARM卫星监测可作为一种有效补充的技术手段。本文选择ASU、IGG和COST-G等机构的SWARM时变模型监测松辽流域陆地水储量变化，并与GRACE、GRACE-FO时变模型进行比较。结果表明：(1)各SWARM时变模型的前10阶位系数与GRACE模型精度接近，其中IGG-SWARM模型经1200 km高斯滤波后的信噪比，相较于ASU和COST-G模型分别高62.47%、55.99%;(2)IGG-SWARM时变模型可探测松辽流域大尺度陆地水储量的时空变化特征，识别流域内的显著旱涝事件，与GRACE、GRACE-FO时变模型均反映出松辽流域在2015年7月—2020年12月的陆地水储量整体呈上升趋势，两者在数据重叠时段的相关系数可达0.6以上。因此，SWARM时变模型可适用于监测松辽流域的陆地水储量变化研究。 相似文献
8.
利用GRACE反演长江流域水储量变化 总被引：3，自引：0，他引：3
利用GRACE重力卫星2003年1月～2006年9月共计43个月的时变重力场数据,反演了长江流域水储量的变化.结果显示,基于GRACE数据的反演结果和CPC模型符合得相当好;若考虑低阶项的影响,对GRACE的反演结果有很明显的改进. 相似文献
9.
利用2002—2012年的GLDAS和WGHM模型模拟水文产品,以及重力恢复与气候试验卫星（Gravity Recovery and Climate Experiment,GRACE）观测数据,计算了全球范围内30个主要流域的水储量变化时间序列,从模拟数据与观测数据的年周期振幅、长期趋势项及时空分布一致性等几个方面,对GLDAS和WGHM进行了评估。结果表明,GLDAS的4个子模型都表现出了明显的季节性变化,CLM年周期振幅输出最小,MOSAIC和VIC最大,NOAH居中,且最接近4个子模型的平均值。与GRACE结果相比,约80%流域的GLDAS与WGHM模型年周期振幅输出呈明显低估现象,且GLDAS的低估程度大于WGHM,但靠近北极高纬度地区的流域有相反的情况出现。在长期趋势项方面,三者结果差异较大,尤其是对于面积较小且人类活动影响较大的流域,GLDAS与WGHM模型不能充分反映人类活动的影响,模型输出表现较差,GRACE结果更接近实际情况。此外,还研究了流域水储量长期变化趋势与灌溉率的关系,发现呈现明显下降趋势的流域主要集中在高灌溉率（>10%）地区,而灌溉率是影响流域水储量变化的重要因素之一。 相似文献
10.
利用GRACE时变重力场反演黑河流域水储量变化 总被引：5，自引：0，他引：5
黑河流域水储量变化对该区域的生态环境和经济建设等具有重要影响。本文利用2002年8月至2011年6月GRACE（Gravity Recovery and Climate Experiment）时变重力场模型GRGS-EIGEN-GL04,采用去相关滤波P3M6与300km高斯滤波相结合的滤波方法反演了黑河流域陆地水储量变化,扣除GLDAS（Global Land Data Assimilation System）水文模型计算的土壤水和冰雪变化,给出了黑河流域地下水储量的时空变化,并利用张掖地区23口地下水测井数据对地下水反演结果进行了初步验证。研究结果表明：（1）黑河流域陆地水储量整体上呈现减少趋势,与该流域气候变化和CPC水文模型的计算结果具有较好的一致性,其减少速率为2.3cm/a等效水高;（2）黑河流域地下水储量呈现长期减少趋势,其减少速率为2.5cm/a等效水高,上、中游区域地下水储量减少速率相当,下游区域地下水储量减少速率明显小于中上游区域。 相似文献
11.
Heavy metals contaminated soils and water will become a major environmental issue in the mining areas. This paper intends to use field hyper-spectra to estimate the heavy metals in the soil and water in Wan-sheng mining area in Chongqing. With analyzing the spectra of soil and water, the spectral features deriving from the spectral of the soils and water can be found to build the models between these features and the contents of Al, Cu and Cr in the soil and water by using the Stepwise Multiple Linear Regression (SMLR). The spectral features of Al are: 480 nm, 500 nm, 565 nm, 610 nm, 680 nm, 750 nm, 1000 nm, 1430 nm, 1755 nm, 1887 nm, 1920 nm, 1950 nm, 2210 nm, 2260 nm; The spectral features of Cu are: 480 nm, 500 nm, 610 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1920 nm, 2150 nm, 2260 nm; And the spectral features of Cr are: 480 nm, 500 nm, 610 nm, 715 nm, 750 nm, 860 nm, 1300 nm, 1430 nm, 1755 nm, 1920 nm, 1950 nm. With these features, the best models to estimate the heavy metals in the study area were built according to the maximal R2. The R2 of the models of estimating Al, Cu and Cr in the soil and water are 0.813, 0.638, 0.604 and 0.742, 0.584, 0.513 respectively. And the gradient maps of these three types of heavy metals’ concentrations can be created by using the Inverse distance weighted (IDW).The gradient maps indicate that the heavy metals in the soil have similar patterns, but in the North-west of the streams in the study area, the contents are of great differences. These results show that it is feasible to predict contaminated heavy metals in the soils and streams due to mining activities by using the rapid and cost-effective field spectroscopy. 相似文献
12.
Soil erodibility, which is difficult to estimate and upscaling, was determined in this study using multiple spectral models of soil properties (soil organic matter (SOM), water-stable aggregates (WSA) > 0.25 mm, the geometric mean radius (Dg)). Herein, the soil erodibility indicators were calculated, and soil properties were quantitatively analyzed based on laboratory simulation experiments involving two selected contrasting soils. In addition, continuous wavelet transformation was applied to the reflectance spectra (350–2500 nm) of 65 soil samples from the study area. To build the relationship, the soil properties that control erodibility were identified prior to the spectral analysis. In this study, the SOM, Dg and WSA >0.25 mm were selected to represent the most significant soil properties controlling erodibility and describe the erodibility indicator based on a logarithmic regression model as a function of SOM or WSA > 0.25 mm. Five, six and three wavelet features were observed to calibrate the estimated soil properties model, and the best performance was obtained with a combination feature regression model for SOM (R2 = 0.86, p < 0.01), Dg (R2 = 0.79, p < 0.01) and WSA >0.25 mm (R2 = 0.61, p < 0.01), respectively. One part of the wavelet features captured amplitude variations in the broad shape of the reflectance spectra, and another part captured variations in the shape and depth of the soil dry substances. The wavelet features for the validated dataset used to predict the SOM, WSA >0.25 mm and Dg were not significantly different compared with the calibrated dataset. The synthesized spectral models of soil properties, and the formation of a new equation for soil erodibility transformed from the spectral models of soil properties are presented in this study. These results show that a spectral analytical approach can be applied to complex datasets and provide new insights into emerging dynamic variation with erodibility estimation. 相似文献
13.
This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R2 > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R2 > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot. 相似文献
14.
Xia Yao Yan ZhuYongChao Tian Wei FengWeiXing Cao 《International Journal of Applied Earth Observation and Geoinformation》2010
Hyperspectral sensing can provide an effective means for fast and non-destructive estimation of leaf nitrogen (N) status in crop plants. The objectives of this study were to design a new method to extract hyperspectral spectrum information, to explore sensitive spectral bands, suitable bandwidth and best vegetation indices based on precise analysis of ground-based hyperspectral information, and to develop regression models for estimating leaf N accumulation per unit soil area (LNA, g N m−2) in winter wheat (Triticum aestivum L.). Three field experiments were conducted with different N rates and cultivar types in three consecutive growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance and LNA under the various treatments. Then, normalized difference spectral indices (NDSI) and ratio spectral indices (RSI) based on the original spectrum and the first derivative spectrum were constructed within the range of 350–2500 nm, and their relationships with LNA were quantified. The results showed that both LNA and canopy hyperspectral reflectance in wheat changed with varied N rates, with consistent patterns across different cultivars and seasons. The sensitive spectral bands for LNA existed mainly within visible and near infrared regions. The best spectral indices for estimating LNA in wheat were found to be NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516), and the regression models based on the above four spectral indices were formulated as Y = 26.34x1.887, Y = 5.095x − 6.040, Y = 0.609 e3.008x and Y = 0.388x1.260, respectively, with R2 greater than 0.81. Furthermore, expanding the bandwidth of NDSI (R860, R720) and RSI (R990, R720) from 1 nm to 100 nm at 1 nm interval produced the LNA monitoring models with similar performance within about 33 nm and 23 nm bandwidth, respectively, over which the statistical parameters of the models became less stable. From testing of the derived equations, the model for LNA estimation on NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) gave R2 over 0.79 with more satisfactory performance than previously reported models and physical models in wheat. It can be concluded that the present hyperspectral parameters of NDSI (R860, R720), RSI (R990, R720), NDSI (FD736, FD526) and RSI (FD725, FD516) can be reliably used for estimating LNA in winter wheat. 相似文献
15.
Gianfranco Piras Kieran P. Donaghy Giuseppe Arbia 《Journal of Geographical Systems》2007,9(4):311-344
This paper presents an innovative approach to the study of regional economic dynamics within a nonlinear continuous-time econometric
framework—a generalized specification of the Lotka–Volterra system of equations. This specification, which accounts for interdependent
behavior of three industrial sectors and spillover effects of activities in neighboring regions, is employed in an analysis
of five Italian regions between 1980 and 2003. For these regions, we report estimation results, characterize the varying systems
dynamics, analyze the models’ local and global stability properties, and determine via sensitivity analyses which structural
features appear to exert the greatest influence on these properties.
相似文献
| Kieran P. DonaghyEmail: |
16.
Wenbin Shen Jin Li Jiancheng Li Zhengtao Wang Jinsheng Ning Dingbo Chao 《地球空间信息科学学报》2008,11(4):273-278
Given the second radial derivative Vrr（P） ｜δs of the Earth＇s gravitational potential V（P） on the surface δS corresponding to the satellite altitude, by using the fictitious compress recovery method, a fictitious regular harmonic field rrVrr（P）^＊ and a fictitious second radial gradient field V：（P） in the domain outside an inner sphere Ki can be determined, which coincides with the real field V（P） in the domain outside the Earth. Vrr^＊（P）could be further expressed as a uniformly convergent expansion series in the domain outside the inner sphere, because rrV（P）^＊ could be expressed as a uniformly convergent spherical harmonic expansion series due to its regularity and harmony in that domain. In another aspect, the fictitious field V^＊（P） defined in the domain outside the inner sphere, which coincides with the real field V（P） in the domain outside the Earth, could be also expressed as a spherical harmonic expansion series. Then, the harmonic coefficients contained in the series expressing V^＊（P） can be determined, and consequently the real field V（P） is recovered. Preliminary simulation calculations show that the second radial gradient field Vrr（P） could be recovered based only on the second radial derivative V（P）｜δs given on the satellite boundary. Concerning the final recovery of the potential field V（P） based only on the boundary value Vrr （P）｜δs, the simulation tests are still in process. 相似文献
17.
Tatenda Dalu Timothy Dube P. William Froneman Mwazvita T.B. Sachikonye Bruce W. Clegg Tamuka Nhiwatiwa 《国际地球制图》2015,30(10):1130-1143
Traditional approaches to monitoring aquatic systems are often limited by the need for data collection which often is time-consuming, expensive and non-continuous. The aim of the study was to map the spatio-temporal chlorophyll-a concentration changes in Malilangwe Reservoir, Zimbabwe as an indicator of phytoplankton biomass and trophic state when the reservoir was full (year 2000) and at its lowest capacity (year 2011), using readily available Landsat multispectral images. Medium-spatial resolution (30 m) Landsat multispectral Thematic Mapper TM 5 and ETM+ images for May to December 1999–2000 and 2010–2011 were used to derive chlorophyll-a concentrations. In situ measured chlorophyll-a and total suspended solids (TSS) concentrations for 2011 were employed to validate the Landsat chlorophyll-a and TSS estimates. The study results indicate that Landsat-derived chlorophyll-a and TSS estimates were comparable with field measurements. There was a considerable wet vs. dry season differences in total chlorophyll-a concentration, Secchi disc depth, TSS and turbidity within the reservoir. Using Permutational multivariate analyses of variance (PERMANOVA) analysis, there were significant differences (p < 0.0001) for chlorophyll-a concentration among sites, months and years whereas TSS was significant during the study months (p < 0.05). A strong positive significant correlation among both predicted TSS vs. chlorophyll-a and measured vs. predicted chlorophyll-a and TSS concentrations as well as an inverse relationship between reservoir chlorophyll-a concentrations and water level were found (p < 0.001 in all cases). In conclusion, total chlorophyll-a concentration in Malilangwe Reservoir was successfully derived from Landsat remote sensing data suggesting that the Landsat sensor is suitable for real-time monitoring over relatively short timescales and for small reservoirs. Satellite data can allow for surveying of chlorophyll-a concentration in aquatic ecosystems, thus, providing invaluable data in data scarce (limited on site ground measurements) environments. 相似文献
18.
On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms 总被引：2，自引：1，他引：1
The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model (Y−E
Y
= (X−E
X
) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E
Y
and E
X
. Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation
matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix
X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem
by using the nonlinear Euler–Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative
algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition.
For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert
cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing
the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment
of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift
to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335–342). The differences between the standard least-squares
and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion
matrix of the estimated parameters. 相似文献
19.
In this study, sensible heat (H) calculation using remote sensing data over an alpine grass landscape is conducted from May to September 2010, and the calculation is validated using LAS (large aperture scintillometers) measurements. Data from two remote sensing sensors (FY3A-VIRR and TERRA-MODIS) are analysed. Remote sensing data, combined with the ground meteorological observations (pressure, temperature, wind speed, humidity) are fed into the SEBS (Surface Energy Balance System) model. Then the VIRR-derived sensible heat (VIRR_SEBS_H) and MODIS-derived sensible heat (MODIS_SEBS_H) are compared with the LAS-estimated H, which are obtained at the respective satellite overpass time. Furthermore, the similarities and differences between the VIRR_SEBS_H and MODIS_SEBS_H values are investigated. The results indicate that VIRR data quality is as good as MODIS data for the purpose of H estimation. The root mean square errors (rmse) of the VIRR_SEBS_H and MODIS_SEBS_H values are 45.1098 W/m2 (n = 64) and 58.4654 W/m2 (n = 71), respectively. The monthly means of the MODIS_SEBS_H are marginally higher than those of VIRR_SEBS_H because the satellite overpass time of the TERRA satellite lags by 25 min to that of the FT3A satellite. Relative evaporation (EFr), which is more time-independent, shows a higher agreement between MODIS and VIRR. Many common features are shared by the VIRR_SEBS_H and the MODIS_SEBS_H, which can be attributed to the SEBS model performance. In May–June, H is over-estimated with more fluctuations and larger rmse, whereas in July–September, H is under-estimated with fewer fluctuations and smaller rmse. Sensitivity analysis shows that potential temperature gradient (delta_T) plays a dominant role in determining the magnitude and fluctuation of H. The largest rmse and over-estimation in H occur in June, which could most likely be attributed to high delta_T, high wind speed, and the complicated thermodynamic state during the transitional period when bare land transforms to dense vegetation cover. 相似文献
20.
Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic CH bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin). 相似文献