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Estimating leaf area index by inversion of reflectance model for semiarid natural grasslands

Science China Earth Sciences 2009年第1期52卷 66-84页

作者： ZHANG Na zhao yingshi College of Resources and Environment Graduate University of Chinese Academy of SciencesBeijing 100049China

The study developed an integrated reflectance model combining radiative transfer and geometric optical properties in order to inverse leaf area index(LAI) of semiarid natural *** order to better link remote sensing information with land plants,and facilitate regional and global climate change studies,the model introduced a simple but important geometrical similarity parameter related to plant crown *** model revealed the influences of different plant crown shapes(such as spherical,cylindrical/cuboidal and conic crowns) on leaf/branch angle distribution frequencies,shadow ground coverage,shadowed or sunlit background fractions,canopy reflectance,and scene *** modeled reflectance data agreed with the measured ones in the three Leymus chinensis steppes with different degradation degrees,which validated the reflectance *** lower the degradation degree was,the better the modeled data agreed with the measured *** this reflectance model was coupled with the optimization inversion method,LAI over the entire study region was estimated once every eight days using the eight-day products of surface reflectance obtained by multi-spectral Moderate-Resolution Imaging Spectroradiometer(MODIS) during the growing seasons in *** temporal and spatial patterns of inversed LAI for the steppes with different cover degrees,swamps,flood plains,and croplands agreed with the general laws and measurements very *** for unused land cover types(sands,saline,and barren lands) and forestlands,totally accounting for about 10% of the study region,the reasonable LAI values were not derived by inversing,requiring further revising of the model or the development of a new model for them.

关键词： leaf area index plant crown shape geometrical similarity parameter reflectance model radiative transfer geometric optics inversion semiarid natural grassland

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A new semi-empirical model for soil moisture content retrieval by ASAR and TM data in vegetation-covered areas

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Science China Earth Sciences 2011年第12期54卷 1955-1964页

作者： YU Fan zhao yingshi Chinese Academy of Surveying and Mapping Beijing 100830 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

Active microwave and passive optical remote sensing data have demonstrated their respective advantages in inversion of surface soil moisture content. A new semi-empirical model is presented for soil moisture content retrieval in vegetation-covered areas, using ENVISAT-ASAR and LANDSAT-TM data collaboratively. Derivation of the algorithm is based on simplification of the Michigan Microwave Canopy Scattering Model （MIMICS）. In the model, the ground surface is divided into a canopy layer and a soil layer, and empirical relationships simulated among vegetation water mass We, the backscatter coefficient σpq1, the bidirectional scattering coefficient σpq2 and the extinction coefficient τp. The key input parameters of the semi-empirical model are reduced to only the leaf area index （LAI）, which can be easily inverted by the optical model PROSAIL, allowing coupling of the microwave and optical models to be achieved. Also, vegetation RMS height （Svcg） is introduced to correct for the radar-shadow effect caused by over-laying vegetation. Analysis of the parameter sensitivity of the semi-empirical model showed that when the regional Leaf Area Index is small （LAI≤3）, the model is more applicable. Soil moisture distribution in the study area was mapped using the semi-empirical model and field ground measurements used for model validation. This showed that, after correction of the radar-shadow effect, the average relative error （Er） between ground-measured and semi-empirical model-derived estimates of soil moisture decreased from 17.6% to 10.4%, while the RMS reduced from 0.055 to 0.031 g cm^-3. The accuracy of soil moisture estimates from the semi-empirical model is much better than for the MIMICS model （Er = 22.7%, RMS = 0.068 g cm^-3）, showing that the semi-empirical model is efficient at obtaining regional surface soil moisture contents when LAI is small.

关键词： microwave and optic remote sensing MIMICS PROSAIL soil moisture

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Assimilation of ASAR Data with a Hydrologic and Semi-empirical Backscattering Coupled Model to Estimate Soil Moisture

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Chinese Geographical Science 2010年第3期20卷 218-225页

作者： LIU Qian WANG Mingyu zhao yingshi College of Resource and Environment Graduate University of the Chinese Academy of Sciences Beijing 100049 China

The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling. However, there is much uncertainty in the assimilation process, which affects the assimilation results. This research developed a one-dimensional soil moisture assimilation scheme based on the Ensemble Kalman Filter (EnKF) and Genetic Algorithm (GA). A two-dimensional hydrologic model-Distributed Hydrology-Soil-Vegetation Model (DHSVM) was coupled with a semi-empirical backscattering model (Oh). The Advanced Synthetic Aperture Radar (ASAR) data were assimilated with this coupled model and the field observation data were used to validate this scheme in the soil moisture assimilation experiment. In order to improve the assimilation results, a cost function was set up based on the distance between the simulated backscattering coefficient from the coupled model and the observed backscattering coefficient from ASAR. The EnKF and GA were used to re-initialize and re-parameterize the simulation process, respectively. The assimilation results were compared with the free-run simulations from hydrologic model and the field observation data. The results obtained indicate that this assimilation scheme is practical and it can improve the accuracy of soil moisture estimation significantly.

关键词： Advanced Synthetic Aperture Radar (ASAR) Distributed Hydrology-Soil-Vegetation Model (DHSVM) Oh Model couple soil moisture data assimilation

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A Methodology for Estimating Leaf Area Index by Assimilating Remote Sensing Data into Crop Model Based on Temporal and Spatial Knowledge

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Chinese Geographical Science 2013年第5期23卷 550-561页

作者： ZHU Xiaohua zhao yingshi FENG Xiaoming Key Laboratory of Quantitative Remote Sensing Information Technology Academy of Opto-ElectronicsChinese Academy of Sciences Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences University of Chinese Academy of Sciences Research Center of Eco-environmental Science Chinese Academy of Sciences

In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial ***,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal *** calibrated crop model will be used as the forecast ***,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) *** calibrated LAI result was used as the observation ***,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop *** results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI *** root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to *** these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.

关键词： assimilation temporal and spatial knowledge Leaf Area Index (LAI) crop model Ensemble Kalman Filter (EnKF)

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Multi-scale MSDT inversion based on LAI spatial knowledge

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Science China Earth Sciences 2012年第2期55卷 1297-1305页

作者： ZHU XiaoHua FENG XiaoMing zhao yingshi Institute of Remote Sensing Applications Chinese Academy of SciencesBeijing 100101China Graduate School of the Chinese Academy of Sciences Beijing 100049China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China

Quantitative remote sensing inversion is ill-posed. The Moderate Resolution Imaging Spectroradiometer at 250 m resolution （MODIS_250m） contains two bands. To deal with this ill-posed inversion of MODIS_250m data, we propose a framework, the Multi-scale, Multi-stage, Sample-direction Dependent, Target-decisions （Multi-scale MSDT） inversion method, based on spa- tial knowledge. First, MODIS images （1 km, 500 m, 250 m） are used to extract multi-scale spatial knowledge. The inversion accuracy of MODIS_lkm data is improved by reducing the impact of spatial heterogeneity. Then, coarse-scale inversion is taken as prior knowledge for the fine scale, again by inversion. The prior knowledge is updated after each inversion step. At each scale, MODIS_lkm to MODIS_250m, the inversion is directed by the Uncertainty and Sensitivity Matrix （USM）, and the most uncertain parameters are inversed by the most sensitive data. All remote sensing data are involved in the inversion, during which multi-scale spatial knowledge is introduced, to reduce the impact of spatial heterogeneity. The USM analysis is used to implement a reasonable allocation of limited remote sensing data in the model space. In the entire multi-scale inversion process field data, spatial knowledge and multi-scale remote sensing data are all involved. As the multi-scale, multi-stage inversion is gradually refined, initial expectations of parameters become more reasonable and their uncertainty range is effectively reduced, so that the inversion becomes increasingly targeted. Finally, the method is tested by retrieving the Leaf Area Index （LAI） of the crop canopy in the Heihe River Basin. The results show that the proposed method is reliable.

关键词： ill-posed inversion prior knowledge MSDT multi-scale

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Research on the method for retrieving soil moisture using thermal inertia model

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Science China Earth Sciences 2006年第5期49卷 539-545页

作者： LIU Zhenhua1 & zhao yingshi2 1. Information College, South China Agricultural University, Guangzhou 510642, China 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China 1. Information College South China Agricultural University Guangzhou 510642 China 2. Graduate University of Chinese Academy of Sciences Beijing 100049 China

In order to improve accuracy of soil moisture inversion using remote sensing, a new thermal inertia model is proposed in this paper. The improved model needs only surface maximum temperature as the temperature parameter input instead of input of the surface temperature difference, as well as the surface sensible and latent fluxes are introduced into boundary conditions of thermal conductivity equation. Furthermore, surface soil conductive heat transfer equation of two-layer model is used to solve the soil thermal inertia so that the remote sensing thermal inertia method can be ap- plied to regions with better-covered vegetation, but usually only for the bare areas or worse vegetation covered areas. The model has been tested at several locations in the area of west Inner Mongolia. Comparing the simulation of the new model with the measurements obtained by apparent thermal inertia and by field test, the result shows that the inertia thermal model can be used to estimate soil moisture in more reasonable accuracy.

关键词： thermal model, thermal conductivity equation, soil initial, sensible flux, latent flux, two-layer model.

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基于主被动遥感数据融合的土壤水分信息提取

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农业工程学报 2011年第6期27卷 187-192,I0003页

作者：余凡赵英时中国测绘科学研究院北京100830 中国科学院研究生院北京100049

为改善西北半干旱地区的土壤含水率监测精度,该文选择张掖地区黑河流域为研究区,提出了一种基于主被动遥感融合数据贝叶斯网络分类的土壤水分信息提取方法。该方法依据光学与雷达遥感数据本身在反演土壤水方面的各自优势,首先利用小波... 详细信息

为改善西北半干旱地区的土壤含水率监测精度,该文选择张掖地区黑河流域为研究区,提出了一种基于主被动遥感融合数据贝叶斯网络分类的土壤水分信息提取方法。该方法依据光学与雷达遥感数据本身在反演土壤水方面的各自优势,首先利用小波变换与IHS结合的算法将TM5、4、3与ASAR数据融合,融合规则采用局部距离最大替代法,在突出融合影像细节的同时,一定程度上保留了TM数据的光谱信息。然后构建BN网络进行分类,以融合后新的R'、G'、B'分量和TM6波段作为网络的输入,输出为5个不同的类别,分别对应5个不同等级的土壤水分含量。经实测数据对融合前后分类结果的比较分析,结果表明,此方法在植被区能取得更好的效果,分类精度达到76.1%,对荒漠区效果欠佳。因此该方法在植被覆盖区对提取区域土壤水分信息是可行的、有效的。

关键词：土壤水分遥感数据融合贝叶斯分类

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基于遗传算法的不同光照条件下植被和土壤组分温度反演

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农业工程学报 2012年第1期28卷 161-166,I0002页

作者：刘振华赵英时华南农业大学信息学院广州510642 中国科学院研究生院北京100049

为了提高地表土壤组分温度的反演精度,该研究利用ASTER反射光谱数据获取像元组分比,将直方图法引入遗传算法中,从而缩小了获取遗传算法最佳搜索参数的范围,并利用遗传算法对盈科研究区内地表非同温像元进行组分温度分解,对非同温像元下... 详细信息

为了提高地表土壤组分温度的反演精度,该研究利用ASTER反射光谱数据获取像元组分比,将直方图法引入遗传算法中,从而缩小了获取遗传算法最佳搜索参数的范围,并利用遗传算法对盈科研究区内地表非同温像元进行组分温度分解,对非同温像元下植被、遮阴土壤、光照裸土的组分温度进行模拟。该研究采用遗传算法直接对ASTER热红外数据进行地表混合像元组分温度分解的方法验证。结果表明,在考虑反射波段情况下,模拟的组分温度与地表同步实测温度的相对误差为7.63%～8.867%,在不考虑反射波段情况下,模拟的组分温度与地表同步实测温度的相对误差为8.955%～11.832%,表明了此方法在研究地表组分温度反演是可行性。该研究为地表组分温度反演提供新思路。

关键词：遥感遗传算法土壤组分温度直方图

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On MSDT inversion with multi-angle remote sensing data

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Science China Earth Sciences 2007年第3期50卷 422-429页

作者： FENG XiaoMing1,2 & zhao yingshi1 1 College of Resources and Environment, Graduate University of the Chinese Academy of Sciences, Beijing 100049, China 2 Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 1. College of Resources and Environment Graduate University of the Chinese Academy of Sciences Beijing 100049 China 2. Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China

With the wavelet transform, image of multi-angle remote sensing is decomposed into multi-resolution. With data of each resolution, we try target-based multi-stages inversion, taking the inversion result of coarse resolution as the prior information of the next inversion. The result gets finer and finer until the resolution of satellite observation. In this way, the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage. With MISR data, we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region. The result proves that this way is efficient.

关键词： target-based multi-stages inversion multi-angle remote sensing wavelet transform

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自动化技术在机械设计制造中的应用探讨

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智能建筑与工程机械 2021年第5期3卷 45-47页

作者：赵应时中铁二局集团有限公司四川成都610031

多年以来,我国的机械化取得了一定的发展成效,各种机械设备逐步被应用在各个方面,正是因为生产领域的机械需求陆续增多,使得行业对机械设计制造也提出了越来越高的标准,相关设计制造厂商在当下的机械设计制造中,要注重自动化技术的应用... 详细信息

多年以来,我国的机械化取得了一定的发展成效,各种机械设备逐步被应用在各个方面,正是因为生产领域的机械需求陆续增多,使得行业对机械设计制造也提出了越来越高的标准,相关设计制造厂商在当下的机械设计制造中,要注重自动化技术的应用,以提升机械设备的整体性能和功能。当下随着机械行业的现代化发展,自动化技术已然成为了机械设计制造中的关键技术。基于此,本文详细分析了机械设计制造中的自动化技术应用,有利于转变机械设计制造的理念和思路。

关键词：机械设计制造自动化技术应用

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