Subjects: Geosciences >> Space Physics submitted time 2017-03-10
Abstract：目前对火星CH4气体的探测是探索火星生命的一项重要手段，圈定出火星表面CH4源区的位置可为将来火星生命的探索选取合适的目标点。本文在对火星CH4气体共振散射进行探测的基础上，通过数值模拟的方法对火星CH4气体的空间分布进行了反演。反演结果能再现模型的密度分布，辨认出CH4气体密度分布较为稠密的区域，从而可以确定出火星表面CH4源区的位置。
Peer Review Status:
Awaiting Review
Subjects: Statistics >> Social Statistics submitted time 2023-12-04 Cooperative journals: 《智慧农业（中英文）》
Abstract： Objectives Chlorophyll content and water content are key physiological indicators of crop growth, and their non-destructive detection is a key technology to realize the monitoring of crop growth status such as drought stress. This study took maize as an object to develop a hyperspectral-based approach for the rapid and non-destructive acquisition of the leaf chlorophyll content and water content for drought stress assessment. Methods Drought treatment experiments were carried out in a greenhouse of the College of Agriculture, Guangxi University. Maize plants were subjected to drought stress treatment at the seedling stage (four leaves). Four drought treatments were set up for normal water treatment CK , mild drought W1 , moderate drought W2 , and severe drought W3 , respectively. Leaf samples were collected at the 3rd, 6th, and 9th days after drought treatments, and 288 leaf samples were collected in total, with the corresponding chlorophyll content and water content measured in a standard laboratory protocol. A pair of push-broom hyperspectral cameras were used to collect images of the 288 seedling maize leaf samples, and image processing techniques were used to extract the mean spectra of the leaf lamina part. The algorithm flow framework of "pre-processing - feature extraction - machine learning inversion" was adopted for processing the extracted spectral data. The effects of different pre-processing methods, feature wavelength extraction methods and machine learning regression models were analyzed systematically on the prediction performance of chlorophyll content and water content, respectively. Accordingly, the optimal chlorophyll content and water content inversion models were constructed. Firstly, 70% of the spectral data was randomly sampled and used as the training dataset for training the inversion model, whereas the remaining 30% was used as the testing dataset to evaluate the performance of the inversion model. Subsequently, the effects of different spectral preprocessing methods on the prediction performance of chlorophyll content and water content were compared. Different feature wavelengths were extracted from the optimal pre-processed spectra using different algorithms, then their capabilities in preserve the information useful for the inversion of leaf chlorophyll content and water content were compared. Finally, the performances of different machine learning regression model were compared, and the optimal inversion model was constructed and used to visualize the chlorophyll content and water content. Additionally, the construction of vegetation coefficients were explored for the inversion of chlorophyll content and water content and evaluated their inversion ability. The performance evaluation indexes used include determination coefficient and root mean squared error (RMSE). Results and Discussions With the aggravation of stress, the reflectivity of leaves in the wavelength range of 400~1700 nm gradually increased with the degree of drought stress. For the inversion of leaf chlorophyll content and water content, combining stepwise regression (SR) feature extraction with Stacking regression could obtain an optimal performance for chlorophyll content prediction, with an R2 of 0.878 and an RMSE of 0.317 mg/g. Compared with the full-band stacking model, SR-Stacking not only improved R2 by 2.9%, reduced RMSE by 0.0356mg/g, but also reduced the number of model input variables from 1301 to 9. Combining the successive projection algorithm (SPA) feature extraction with Stacking regression could obtain the optimal performance for water content prediction, with an R2 of 0.859 and RMSE of 3.75%. Compared with the full-band stacking model, SPA-Stacking not only increased R2 by 0.2%, reduced RMSE by 0.03%, but also reduced the number of model input variables from 1301 to 16. As the newly constructed vegetation coefficients, normalized difference vegetation index(NDVI) (R410-R559)/(R410+R559) and ratio index (RI) (R400/R1171) had the highest accuracy and were significantly higher than the traditional vegetation coefficients for chlorophyll content and water content inversion, respectively. Their R2 were 0.803 and 0.827, and their RMSE were 0.403 mg/g and 3.28%, respectively. The chlorophyll content and water content of leaves were visualized. The results showed that the physiological parameters of leaves could be visualized and the differences of physiological parameters in different regions of the same leaves can be found more intuitively and in detail. Conclusions The inversion models and vegetation indices constructed based on hyperspectral information can achieve accurate and non-destructive measurement of chlorophyll content and water content in maize leaves. This study can provide a theoretical basis and technical support for real-time monitoring of corn growth status. Through the leaf spectral information, according to the optimal model, the water content and chlorophyll content of each pixel of the hyperspectral image can be predicted, and the distribution of water content and chlorophyll content can be intuitively displayed by color. Because the field environment is more complex, transfer learning will be carried out in future work to improve its generalization ability in different environments subsequently and strive to develop an online monitoring system for field drought and nutrient stress.
Subjects: Mathematics >> Mathematics （General） submitted time 2024-02-17
Abstract： In this paper, we first study the monotone intervals in the neighborhood of x=0 for the series y=a1x+a2x2+a3x3+…+anxn+… by using the Lagrange inversion series method. Then, for the more general series equation, we give a calculation method of the nonzero and minimum real roots.
Peer Review Status:Awaiting Review
Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2018-02-01 Cooperative journals: 《工程热物理学报》
Abstract： The direct calculation models of spectral transmittance of single and double window were developed, and a novel inversion method of optical constants (k is extinction coefficient and n is refractive index) of materials was proposed based on transmittance spectrograms of double window. Differences between the new method and two others currently used methods were studied, and application ranges of methods were also investigated. Optical constants of selenide glass attained in references were selected as true values, and spectral transmittances of glass simulated based on direct calculation model were regarded as experimental values. Optical constants of selenide glass were achieved by inverse models. Influences of measurement error on inverse results were also determined. The results show that, (1) the inversed calculation precision of the new method is similar as two others methods. (2) Effects of optical constants on three inversion methods are urgent larger, but inversed calculation precision are higher in most application ranges. (3) Influences of measurement errors existed in experimental datum on the inverse precision of three methods are urgent distinctness.
Subjects: Geosciences >> Space Physics submitted time 2016-05-13
Abstract： The inverse imaging is a key issue for microwave interferometric radiometers,but the inverse process is ill-posed and doesnt provide a unique and stable solution.For the problem that there exists a large reconstruction bias with G matrix model used generally in the inversion algorithm,an improved G matrix model applied in FPIR system was presented.The simulation results show that,compared with conventional G matrix model,the improved G matrix model can greatly reduce the reconstruction bias in the FPIR system.The improved G matrix model can obtain more accurately the brightness temperature distribution of the observed scene,so as to meet requirements of measuring wind field of the ocean surface and soil moisture for FPIR.
Peer Review Status:Awaiting Review
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-02-17 Cooperative journals: 《智慧农业（中英文）》
Abstract： Ground-penetrating radar (GPR) is one of the emerging technologies for soil moisture measurement. However, the measurement accuracy is difficult to determine due to some influence factors including radar wave frequency, soil texture type, etc. The GPR equipment with 1000 MHz center frequency and the measurement method of common midpoint (CMP) were adopted in the research to collect radar wave raw data in the selected field area under arid soil and moist soil conditions. The transmitter and receiver antennas of the GPR equipment were moved 0.01 m respectively in opposite directions on each radar wave raw data collection. Therefore, a CMP radar image consisted of 100 pieces of radar wave raw data by increasing the antenna distance from 0 m to 2 m. Each radar wave raw data indicated that the radar waves were reflected in the reflective layer with different dielectric constant under the same antenna distance. And the reflected and refracted radar waves were acquired by the receiving antenna at different two-way travel time respectively, and recorded in the computer. The collection of CMP soundings aimed to determine the inversion accuracy, optimum inversion depth, effective inversion depth and optimal inversion model of soil moisture content at different depth ranges and adjacent reflective layers by GPR at field scale. The reflected and refracted radar wave data were extracted from the raw data. The velocities of the surface waves and reflected waves were obtained respectively from the line slope of the surface wave data and the hyperbolic curves fitting of the reflected wave data. In addition, the relative dielectric constant of the soil at specified depth were deduced according to the soil dielectric constant and its reflected wave velocity. Moreover, 4 different models including Topp, Roth, Herkelrath and Ferre were used to figure out the soil volumetric water content inversion. Meanwhile, the measured data of soil volumetric moisture content obtained by oven drying method were used to verify the accuracy of the inversion results. The results showed that the effective inversion depth of 1000 MHz GPR ranged from 0 to 50 cm. The best inversion depth was 50 cm in arid soil and 40 cm in moist soil. The Roth model had the best correlation and stability with the highest R2 was 0.750, the Root Mean Square Error (RMSE) was 0.0114 m3/m3 and the lowest Relative Error (RE) was 3.0%. The GPR could possess the capacity of quick, precise and non-destructive measurement of specified depth soil moisture in field scale. The inversion model of soil moisture content needs to be calibrated according to different soil conditions.
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2020-06-19 Cooperative journals: 《干旱区研究》
Abstract：基于Sentinel-2A遥感数据，结合白城市表层土壤采样的全盐含量化验值，利用统计与拟合分析的方法，建立土壤盐渍化遥感监测模型，对研究区表层土壤含盐量进行反演分析。结果表明：① 研究区土壤的反射率与含盐量呈正相关，相关系数在Sentinel-2A第5波段（中心波长为0.705 μm）达到最大值，为r=0.902，利用第5波段反射率建立的土壤含盐量反演模型TSC=50.776R5-8.262，模型的决定系数R 2=0.813，检验样本的均方根误差RMSE=0.814g·kg-1；② 将反射率进行指数、幂、S曲线等数学变换后，可以显著提高拟合精度，其中，第8波段反射率的幂函数变换后，建立土壤含盐量的单波段反演模型TSC=77.51x2.346精度最好，模型的决定系数R 2=0.888；③ 利用多元逐步回归分析的方法建立土壤含盐量的多波段反演模型TSC=-13.810+38.973R5-14.122eR5+23.896R82.248+1.743ln(R9)，模型的决定系数为R2=0.924，检验样本的均方根误差为RMSE=0.736g·kg-1。
Subjects: Astronomy >> Astrophysical processes submitted time 2023-06-07 Cooperative journals: 《天文学进展》
Abstract： When smaller asteroids are heated up by the sunlight, they re-radiate eventually the energy away in the thermal waveband, which creates a tiny thrust in turn. Due to irregular shape, thrusts on the different parts of asteroid result in a thermal torque complemented by scattered sunlight, which can modify the rotation rates and obliquities of small astreoids. This rotational variant has been named as Yarkovsky-O’Keefe-Radzievskii-Paddack (YORP) effect. During recent years, the YORP effect has been used to resolve many mysteries in asteroid science. In this paper, we review some key results especially in observational field,and preview the future goals for this work. Firstly, the paper introduces the great significance of YORP research. Beside explaining the rotation and size distribution of asteroids, YORP effect also is applied to assessing near earth asteroid impact threat precisely, constraining asteroid physical characteristics, explain#2;ing surface material migration and asteroid activity triggering, even act as a important role on planetary system evolution. Secondly, the paper introduces the theoretical framework of YORP effect, and illustrates the principle and application conditions. The torque calculation of the YORP effect and its influence on the rotation rate and obliquities of asteroids are reviewed in detail. More similar effects, such as BYORP effect, Orbital YORP effect, TYORP effect, are also introduced comprehensively. Thirdly, the paper presents a progress on the rotational acceleration driven by YORP through observation, which is very dependent on the shape inversion model and thermophys#2;ical model of asteroid. So far, only 6 near earth asteroids have been measured and confirmed rotational acceleration, and all of them are speeding up. Also, the asteroids which have opportunity to measure rotational acceleration in the future are given. Fourthly, the paper presents the role of YORP effect in the statistical distribution of asteroid rotation state, mainly including: 1) flatting the rotational speed distribution in the asteroid belt, and driving that of near earth asteroids as a bimodal distribution; 2) alignment of the rotation axes of asteroids, especially evidence in asteroid families. Furthermore, the YORP factor (CY) is used to estimate the degree of YORP effect. Finally, the paper discusses some key points should be accounted in target selection of measurable YORP effect, also including the influence of surface micro-structure charac#2;teristics, rough surface thermal-infrared beaming and global self-heating of asteroid on the quantitative evaluation of YORP effect.
Subjects: Mechanics >> Applied Mechanics submitted time 2022-12-21 Cooperative journals: 《应用力学学报》
Abstract：
The rapid development of numerical technology and intelligent algorithm provides a new way to identify the internal defects of structures.In this paper,an inverse analysis model for crack detection is established by combining extended finite element method(XFEM)and error-back-propagation multilayer feedforward(BP)neural network.The BP neural network is trained by the displacement data obtained from the forward analysis of XFEM.On this basis,the network is used for the inverse identification of cracks.The feasibility and accuracy of the model are verified by two typical examples.The results show that the proposed method can accurately retrieve the geometric information of cracks.At the same time,the influence of the layout of measuring points and the input data noise on the identification accuracy is also discussed.
Subjects: Geosciences >> Space Physics submitted time 2016-12-26
Abstract：FY-3气象卫星上搭载的紫外臭氧总量探测仪TOU是我国自主开发研制的首台用于全球臭氧总量定量测量的探测仪，自发射以来已成功在轨运行近两年。由于TOU发射前辐亮度定标存在偏差，为了得到高精度的产品，TOU必须进行在轨定标。本文介绍了基于辐射传输模式计算对TOU辐亮度进行在轨道定标的方法，定标过程中用于模拟辐亮度计算的臭氧总量由与TOU观测时刻相近的国外臭氧总量探测仪器MetOp/GOME-2提供。文章将在轨定标后TOU的反演结果与AURA/OMI以及地基的产品进行比较，研究结果表明，用辐射传输模式对TOU辐亮度进行在轨定标的方法是可行的，反演结果能够真实的反映臭氧的时空分布特性，在全球部分地基观测站所处的位置上对TOU, OMI以及地基的臭氧总量进行比较的结果表明，TOU与OMI的相对偏差均方根约为2.52%， TOU与地基以及OMI与地基观测结果之间的相对偏差均方根分别为4.45%和3.89%。
Peer Review Status:Awaiting Review
Subjects: Geosciences >> Geography submitted time 2023-04-07 Cooperative journals: 《干旱区地理》
Abstract： Accurate monitoring of runoff from small and medium-sized rivers is of great significance for ecological stability in arid areas. However, it is difficult to accurately retrieve the flow of small and medium-sized rivers by remote sensing. Taking the Zhongfengchang river section of Kashi River in Nilka County, Xinjiang, China, as an example, this study constructed a power function relationship model between river width, water depth, and discharge based on the relationship fitting method and measured hydrological data, unmanned aerial vehicle data, and satellite data. Using the time series of satellite data, the runoff volume of the monitored river section was inferred 24 times in different periods. The results show that when the runoff rate is 0-50 m3 ·s −1 and 50-100 m3 ·s −1 , the inversion of the runoff rate based on the hydraulic geometry of the river width is optimal, with root mean square errors (RMSEs) of 7.15 m3 ·s −1 and 2.81 m3 ·s −1 , respectively; when the runoff rate is 100-200 m3 ·s −1 and > 200 m3 ·s −1 , the inversion of the hydraulic geometry based on water depth and river width is the best, with RMSEs of 13.37 m3 ·s−1 and 1.06 m3 ·s−1 , respectively. These findings provide a new method for the fine monitoring and management of runoff of small and medium-sized rivers in areas lacking hydrologic data and have high reference value for flood disaster prediction, hydropower resource development, and water ecosystem restoration.
Subjects: Mechanics >> Applied Mechanics submitted time 2023-03-20 Cooperative journals: 《应用力学学报》
Abstract： Crack identification is an important issue in structural health monitoring.Based on the principleof inverse analysis , this paper combines the numerical manifold method (NMM) with the Elman neuralnetwork to carry out crack identification. To serve the learming of Elman neural network , the NMM is usedto obtain the displacement data of measuring points under various crack configurations.On this basis , thetrained Elman network is used for straight crack inversion. 'The feasibility and accuracy of NMM-Elmancollaborative method are verified by two typical examples.At the same time , the effects of measuring pointlayout and input data noise on crack inversion accuracy are analyzed.The research shows that the methodproposed in this paper can accurately reflect the crack tip coordinates of single and complex cracks.Thiswork provides a new pathway for efficient and accurate detection of complex cracks.
Subjects: Geosciences >> Geography submitted time 2024-06-12 Cooperative journals: 《干旱区研究》
Abstract： Exploring the dynamic change characteristics of soil moisture and vegetation water demand in the Northwest Arid Zone can provide scientific basis for the amount of water required at different stages of ecological recovery and the optimal allocation of water resources. Based on this, the Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI), and Vegetation-adjusted Perpendicular Drought Index (VAPDI) were constructed by using the Sentinel-2 L2A and Landsat8 OLI remote sensing images, combined with the 111 data from 0-10 cm of the measured soil in the north and south mountains of Lanzhou City as the study area. Perpendicular Drought Index (PDI), Modified Perpendicular Drought Index (MPDI) and Vegetation-adjusted Perpendicular Drought Index (VAPDI) were constructed respectively, and the quantitative coefficients of determination (R2), Mean absolute Arrors (MAE), Mean Relative Errors (MRE), and average relative errors of the four model indicators were used. (MAE), mean relative error (MRE), and root mean square error (RMSE) to evaluate the accuracy of the model inversion, select the optimal soil moisture inversion model and combine the soil moisture limiting coefficients with the spatial data of forest, grassland, and cropland vegetation area in the study area in 2019, and the evapotranspiration of the reference crop within the growing season at each site, and finally construct the ecological water demand model of the vegetation, to clarify the soil moisture and vegetation ecological water demand in the study area. The results showed that: (1) there were different degrees of linear negative correlations between PDI, MPDI, VAPDI and measured data under the two data sources, of which the R2 was 0.37, 0.64 and 0.59, respectively, and from the results of the evaluation indexes, the fit coefficient of determination of the soil moisture regression model of MPDI was the highest, and the spatial soil moisture regression model of the two remote sensing data inversions had the highest coefficient of determination. data inversion of soil moisture spatial distribution pattern had consistency. (2) The soil moisture inversion of Sentinel-2 L2A with high resolution is more refined, and the overall soil moisture shows a fluctuating growth trend, with the average value of soil moisture for multiple time periods being 23.27%, showing a decrease and then an increase and then a decrease, with an overall increase of 74.07%. (3) The monthly average value of vegetation water demand in April-October in the north and south mountains of Lanzhou City showed an increase and then a decrease, which was consistent with the change of soil moisture content, and the value of vegetation water demand was the largest in April-October, 3.98×107 m3 in July, and the smallest vegetation ecological water demand was 0.97×107 m3 in October, which appeared in October. month. With the implementation of the environmental greening project, the north and south hills of Lanzhou City have gradually formed a community structure with a combination of multiple species from only drought-tolerant herbs and low shrubs. This study can provide a reference for the rational use of soil and water resources and vegetation restoration in the north and south mountains of Lanzhou City.
Subjects: Geosciences >> Geography submitted time 2024-04-01 Cooperative journals: 《干旱区地理》
Abstract：耕地保护关系到国家粮食安全和经济社会可持续发展，对生态环境保护具有重要作用，快速精准的获取耕地土壤盐分含量及空间分布信息是耕地保护的必然要求。以宁夏平罗县为研究区，利用Landsat 9 OLI和Sentinel-1遥感影像，提取光谱指数和雷达极化组合指数，基于变量投影重要性法与灰度关联法筛选特征变量，然后运用反向传播神经网络、支持向量机和随机森林3种机器学习算法构建模型，并用最佳模型反演耕地土壤含盐量空间分布情况。结果表明：（1）利用变量投影重要性法筛选变量建立的模型验证集决定系数（R2）大于灰度关联法筛选变量建立的模型。（2）利用随机森林算法，组合光谱指数和雷达极化组合指数协同反演模型效果最佳，建模集R2为0.791，均方根误差（RMSE）为1.016，R2较单一数据源模型分别提高0.065和0.085，RMSE分别降低0.147和0.189；验证集R2为0.780，RMSE为1.132，R2较单一数据源模型分别提高0.091和0.237，RMSE分别降低0.175和0.377。（3）平罗县耕地轻度盐渍化和中度盐渍化土壤分布范围广，占比分别为23.77%和33.54%，重度盐渍化达15.37%。研究结果发现，组合多源遥感数据建模能够有效提高土壤含盐量反演精度，可为干旱区耕地土壤含盐量的反演和当地农业可持续发展提供有效的技术参考。
Subjects: Geosciences >> Geography submitted time 2023-09-19 Cooperative journals: 《干旱区地理》
Abstract：利用较高空间分辨率的Landsat卫星数据，以覃志豪单窗算法反演黄河源区19902018年（间隔3~5 a）的夏季（7月或8月）地表温度，并对反演结果进行相关性分析。结果表明：（1） 黄河源区夏季地表温度平均值与MODIS地表温度产品的平均值相关系数不高，约为0.5，主要原因是Landsat数据与MODIS产品的空间分辨率不一致。（2） 水体的地表温度基本保持不变，其他地物的地表温度均呈现上升趋势，冰川的地表温度升高最快。（3） 黄河源区各年份地表温度与高程存在明显的负相关关系，相关系数平均值为-0.65。（4） 空间上，黄河源区地表温度值与土壤湿度值的空间分布存在负相关关系。（5） 在气候因素中，降水与地表温度存在明显的负相关关系，其相关系数小于-0.5的区域约占整个源区面积的70%。
Subjects: Astronomy >> Astrophysical processes submitted time 2023-06-07 Cooperative journals: 《天文学进展》
Abstract： The radio interferometer achieves signal correlation by acquiring the time delays of the signal from a common celestial objects between radio telescopes, and thus forms a radio telescope with high angular resolution, which plays an important role in fine mapping and high precision positioning of celestial objects. However, as a wet component of the atmosphere, water vapor in radio interferometer observation results in extra delay independent of the position and structure of celestial bodies, which has the characteristics of fast varia#2;tion and low regularity, hence it is difficult to establish an accurate model. Accordingly, the delay due to water vapor needs to be corrected. Water vapour radiometer is an important observation equipment for measuring water vapour content in the atmosphere. It can be used to correct the time delay caused by water vapour to reduce the phase fluctuation of radio interference. Compared with other water vapor detection methods, the water vapor radiometer has higher time resolution. In this paper, the principle, research progress and application of water vapour radiometer in radio interferometers are introduced. Finally, the trend of water vapour radiometer development in the future is prospected.
Subjects: Geosciences >> Other Disciplines of Geosciences submitted time 2019-09-11 Cooperative journals: 《干旱区研究》
Abstract：研究大气水汽的反演及了解其时空变化，对有效评估大气生态服务功能具有重要现实意义。基于石家庄地区CE-318观测的大气水汽数据，结合探空水汽数据和地面水汽压数据，运用传统回归分析、改进型回归分析、分段反演等方法，构建传统回归模型、基于CE-318的大气水汽改进型模型和分季节模型3种大气水汽反演模型，并经过精度对比评估选出适用于研究区的大气水汽最优反演模型。检验结果表明，基于CE-318的大气水汽改进型反演模型的各项精度检验指标均为3个模型中的最佳值，是该地区最优的大气水汽反演模型。
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2018-11-08 Cooperative journals: 《干旱区研究》
Abstract：土壤含水率是影响干旱区植物生长的重要因素，获取区域尺度土壤含水率数据，能够为干旱半干旱区生态恢复和脆弱生态系统保护提供科学依据。结合MODIS地表温度和反射率数据及全球陆面数据同化系统（GLDAS）土壤含水率数据，利用表观热惯量法和统计降尺度方法反演疏勒河流域土壤含水率，研究其时空变化及其与植被的相关性，得到以下结论：2016年整个疏勒河流域年均土壤含水率偏低，且季节变化显著，其均值、离散程度存在7月＞10月＞4月＞12月的趋势；流域东部土壤含水率整体高于西部；流域土壤含水率空间分布的季节变化显著，其变异系数的空间分布与年均土壤含水率相似；土壤含水率与归一化植被指数NDVI正相关，但不同区域两者相关程度不同，灌区土壤含水率与植被的相关性最高。
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Basic Disciplines of Agriculture submitted time 2017-11-09 Cooperative journals: 《中国生态农业学报》
Abstract：准确估算草地生物量, 对全球气候变化背景下的陆地生态系统碳循环研究具有重要意义。过去几十年, 草地生物量估算研究大多集中在北方, 而南方草地具有类型繁多和分布零散等特征, 对其生物量进行评估的报道较少。本文以云南省为例, 应用2012—2014 年草地生物量野外调查资料和同期MODIS 遥感数据, 建立草地地上生物量(AGB)遥感估算模型; 再引入草地植被群落特征(高度和盖度)信息对统计模型进行优化, 并进行生物量空间反演。结果表明: 优化后模型的估算精度由原来的35.0%提升为43.7%; 反演得到云南省3 年年均AGB 的总量介于1 026.86 万~1 408.54 万t, 平均为1 221.11 万t; 从空间分布上看, 云南省草地AGB 密度总体上呈现西部高东部低、南部高北部低的格局。本研究首次将遥感植被指数数据与实测植被群落特征参数结合, 使估算精度比传统的纯粹光学遥感模拟方法显著提升24.9%, 但精确估算大面积的草地AGB, 需要进一步探索如何将激光雷达数据或遥感立体影像中提取的植被特征信息应用于草地AGB 估算研究。
Subjects: Geosciences >> Space Physics submitted time 2017-03-10
Abstract：针对风云三号C星微波湿温探测仪(FY-3C/MWHTS)的陆地晴空观测资料，建立了一维变分反演系统，对大气的温湿廓线进行反演。为了更好的描述温湿廓线的相关性，同时减小温度和湿度在反演过程中相互之间的误差传递，提出了使用背景协方差矩阵的联合矩阵和单独矩阵进行组合反演的方法。对于MWHTS模拟亮温和观测亮温之间的偏差，使用逐扫描点的统计回归方法进行校正。选择我国部分陆地区域的晴空观测亮温进行温湿廓线的反演，并利用欧洲中期天气预报中心(ECMWF)再分析数据、美国国家环境预报中心(NCEP)分析数据以及无线电探空观测(RAOB)数据对反演结果进行验证，温湿廓线的反演结果与ECMWF再分析数据验证的最大均方根误差分别是2.59 K和11.87%，与NCEP分析数据验证的最大均方根误差分别是1.88 K和21.50%，与RAOB数据验证的最大均方根误差分别是3.43 K和25.48%，验证结果表明了反演结果的可靠性。另外与国外同类载荷AMSU观测亮温的物理方法和统计方法反演精度进行了对比，结果表明：MWHTS具有较强的湿度廓线以及高空温度廓线的探测能力，且针对MWHTS的观测亮温建立的一维变分反演系统具有较高的反演精度。与NCEP 6小时预报廓线的验证结果表明：反演的湿度廓线可以提高预报廓线的精度。
Peer Review Status:Awaiting Review
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