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1.
吸收性气溶胶指数AAI(Absorbing Aerosol Index)是基于卫星观测的紫外后向散射辐射导出的参数,与大气中对紫外线有吸收作用的气溶胶(简称吸收性气溶胶)有关,能够定性反应吸收性气溶胶的存在与空间分布特征。由于臭氧在AAI反演波段对紫外线仍然存在弱吸收作用,因此AAI可能与大气臭氧总量有关,臭氧反演的误差也可能对AAI的反演精度造成影响。为了研究臭氧总量与AAI的关系,臭氧反演的精度对AAI反演的影响,利用辐射传输模型通过敏感性实验,来模拟吸收性气溶胶指数和臭氧总量之间的关系,臭氧反演误差对吸收气溶胶指数的反演的影响。采用沙漠气溶胶,不改变气溶胶的含量,通过改变中纬度夏季的臭氧总量来计算大气模型。对臭氧总量、气溶胶含量与AAI的内在关系,臭氧总量对AAI反演精度的影响进行了模拟,模拟结果表明,气溶胶指数与臭氧总量的改变存在正相关关系,而臭氧总量的反演误差对AAI指数的反演影响不大。基于风云三号气象卫星紫外臭氧总量探测仪(FY-3/TOU)的臭氧总量和吸收性气溶胶指数数据(2012年),分析了青藏高原地区7月份臭氧总量与吸收性气溶胶指数空间分布特征的关系,与模拟结果一致。 相似文献
2.
为提高风云三号气象卫星(FY-3)紫外臭氧总量探测仪(TOU)观测数据得到的吸收性气溶胶指数AAI(Absorbing Aerosol Index)或AI(Aerosol Index)的可靠性,需要了解AAI指数与相对湿度之间的内在关系。本研究利用大气辐射传输模型DAK(Doubling-Adding KNMI)分别模拟了在城市气溶胶和乡村气溶胶模式下AAI同相对湿度之间的关系,并将结果同已观测到的实际结果进行对比。结果发现,在相对湿度呈高值时AAI指数出现很大的变化,但相对湿度对两种气溶胶模型的影响具有相反的效应,分析显示当大气中含有吸收性气溶胶如含碳类气溶胶(在中国北部的污染过程中很常见)时,AAI结果对RH(Relative Humidity)有很强的依赖。在应用AAI指数产品检测污染过程中需要注意气溶胶的具体类型和相对湿度的影响,必要时在高相对湿度过程中进行数据校正或剔除。 相似文献
3.
临边探测器垂直分辨率高,辐射信号的变化主要受大气参数影响,且辐射校准后几乎不受背景辐射影响,对痕量气体可探测性强,探测高度约为10—100 km,对臭氧层的大气遥感监测具有特殊意义。红外临边传感器经过40余年的发展过程,在通道数目、信噪比、可探测目标种类、冷冻技术、在轨寿命方面都有明显改进。本文以平流层O_3及其相关的痕量气体为中心,按照传感器搭载的卫星平台及卫星发射时间的先后顺序,比较了国际上已有的LRIR、LIMS、SAMS、ISAMS、CLAES、MIPAS、HIRDLS、TES共8个星载红外临边探测器的特性、探测目标、技术改进、性能提升等;介绍了红外临边探测大气成分的反演原理;总结了红外临边探测器在痕量气体,平流层云与气溶胶,重力波与极涡,非局部热力学平衡效应4个方面的应用成果。最后对红外临边探测的前景趋势提出了思考。 相似文献
4.
《International Journal of Digital Earth》2013,6(6):157-171
The Moderate Resolution Imaging Spectroradiometer (MODIS)-Terra surface reflectance product (MOD09A1), with bands 1 to 7, is a gridded, eight-day composite product derived from the MODIS-Terra top of atmosphere reflectance swaths. It performs cloud detection and corrects for the effects of atmospheric gases and aerosols. The cloud mask (CM) algorithms for MODIS are based on empirical thresholds on spectral reflectance and brightness temperature. Since the spatial resolution of the thermal band is 1000 m, while that of MOD09A1 is 500 m, many undetected and false clouds are observed in MOD09A1. These errors always result in temporal and spatial inconsistencies in higher-level products. In this paper, a cloud detection algorithm (TSCD) based on a MOD09A1 time series is introduced. Time series cloud detection (TSCD) algorithm is based on the relative stability of ground reflectance and the sudden variations in reflectance that result from cloud cover. The algorithm first searches the clear-sky reference data, and then discriminates clouded and unclouded pixels by detecting a sudden change of reflectance in the blue wavelength and spectral correlation coefficient at the pixel level. Compared with cloud cover assessments obtained from MODIS' original CM, TSCD provides similar or better discrimination in most situations when the land surface changes slowly. 相似文献
5.
基于6S传输模型,本文利用中分辨率成像光谱仪（MODIS）数据并结合较新的NASA的V5．2气溶胶业务反演算法,以上海市MODIS数据为研究数据源,结合晴朗天气（晴朗且无云或云稀薄）与AERONET发布的探测日（即发布AOD探测值日期）选取8组MODISLIB数据集,对其进行气溶胶厚度反演。同时将反演结果与AERONET架设在太湖区域点（31N,120E）的太阳光度观测的光学厚度进行验证。结果表明：V5．2反演算法结果与观测值呈现相同的变化趋势,反演值与观测值误差不大,在气溶胶光学厚度反演中具有较好的应用。 相似文献
6.
Barry Tyler Wilson Christopher W Woodall Douglas M Griffith 《Carbon balance and management》2013,8(1):1-15
The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). 相似文献
7.
ABSTRACTAtmospheric aerosols can alter the direct and diffuse components of global solar radiation, which further influences terrestrial gross primary productivity (GPP) via photosynthesis. To investigate the impact of aerosols on GPP, GPP is modeled using the Boreal Ecosystem Productivity Simulator (BEPS) under two aerosol scenarios (S1& S2) over cropland and grassland ecosystems in the highly polluted North China. In S1, the aerosol-effect is not considered and an original empirical method is used when estimating direct and diffuse solar radiation in BEPS. In S2, BEPS is improved by a new empirical method which incorporates the impact of aerosols using the remote sensing-based aerosol optical depth (AOD). Results suggest that aerosols can reduce GPP of the sunlit leaves by decreasing direct solar radiation, but increase GPP of the shaded leaves by increasing diffuse solar radiation. The impact of aerosols on GPP is more significant over the cropland ecosystem (p < 0.05) with a more complex canopy structure during the peak period of the growing season. Furthermore, an AOD value of 0.3–0.6 with a diffuse fraction (the fraction of diffuse solar radiation in global solar radiation) around 30-40% can largely increase total GPP over the cropland ecosystem. The study improves the accuracy of GPP modeling using BEPS by highlighting the aerosol-effect on GPP via solar radiation over highly polluted regions.Abbreviations: gross primary productivity (GPP); aerosol optical depth (AOD); boreal ecosystem productivity simulator (BEPS) 相似文献
8.
Adrianos Retalis Nicolaos Sifakis 《ISPRS Journal of Photogrammetry and Remote Sensing》2010,65(1):17-25
Low and moderate spatial resolution satellite sensors (such as TOMS, AVHRR, SeaWiFS) have already shown their capability in tracking aerosols at a global scale. Sensors with moderate to high spatial resolution (such as MODIS and MERIS) seem also to be appropriate for aerosol retrieval at a regional scale. We investigated in this study the potential of MERIS-ENVISAT data to resolve the horizontal spatial distribution of aerosols over urban areas, such as the Athens metropolitan area, by using the differential textural analysis (DTA) code. The code was applied to a set of geo-corrected images to retrieve and map aerosol optical thickness (AOT) values relative to a reference image assumed to be clean of pollution with a homogeneous atmosphere. The comparison of satellite retrieved AOT against PM10 data measured at ground level showed a high positive correlation particularly for the AOT values calculated using the 5th MERIS’ spectral band (R2=0.83). These first results suggest that the application of the DTA code on cloud free areas of MERIS images can be used to provide AOT related to air quality in this urban region. The accuracy of retrieved AOT mainly depends on the overall quality, the pollution cleanness and the atmospheric homogeneity of the reference image. 相似文献
9.
A multi‐phased approach was used to estimate potential impacts of climate change on forests of the eastern United States. Phase I was at community‐level and Phase II examined selected species, both using three 2 x CO2 climate scenarios. Geographic information systems (GIS) and statistical modeling techniques were used to manipulate and analyze climate and vegetation data, and model vegetation responses to climate change. The first two stages of the study indicated possible large‐scale alteration of forest communities by future climate change. Although results varied among climate models, several trends were apparent. In northern states of the study area, ranges of several conifers declined significantly and ranges of oaks and hickories moved northward. In central states, ranges of sugar maple and tulip poplar became much smaller, with concomitant increases in ranges of southern oaks and loblolly pine. In . southern states, American beech declined and ranges of southern oaks increased northward. This paper discusses results of the first two phases and current progress of the third phase. 相似文献
10.
本文借助Google Earth Engine(GEE)云平台,以Landsat影像、气温降水和土地利用类型为基础,利用Theil-Sen Median趋势分析、Mann-Kendall检验、偏相关性和多元回归残差分析法,分析了1999—2018年陕北黄土高原植被覆盖时空特征、变化趋势及气候变化与人类活动对于不同土地利用类型的影响,得出以下结论:(1)1999—2018年陕北黄土高原年际FVC呈改善趋势,其平均增速为0.004 9/a(P<0.01),植被覆盖度呈增加趋势的面积占总面积的74.43%;(2)植被覆盖度与降水和气温的偏相关系数具有明显的空间差异,植被生长对降水变化较敏感;(3)气候变化和人类活动的共同作用是植被生长的主要原因,其中气候变化对植被FVC的影响范围为-0.001 0/a~0.003 6/a,而人类活动对植被FVC的影响范围为-0.046 1/a~0.049 0/a;(4)在不同土地利用类型中,气候变化对水体增幅影响最大,对针叶林和阔叶林增幅影响最小,而人类活动变化对人类占用地增幅影响最大,对阔叶林增幅影响最小。 相似文献
11.
定量分析气溶胶与痕量气体之间的时空变化关系有助于进一步研究气粒转化。本文采用2006年—2015年MODIS气溶胶光学厚度(AOD)、细粒子模态比(FMF)和OMI痕量气体(SO_2、NO_2和HCHO)数据,对黄海、东海和南海区域上空的细粒子气溶胶与痕量气体进行定量分析。先对气溶胶和痕量气体作均值分析发现:AOD_(fine)、SO_2、NO_2和HCHO的均值在黄海、南海、东海均依次减小;再对气溶胶对痕量气体的敏感度分析发现:黄海地区的AOD_(fine)对SO_2最敏感,敏感度为0.424,这与中国东部沿海城市的人为排放有关;而东海和南海地区对HCHO的敏感度较高,依次为0.664和0.545,主要受东南亚和中国南方地区生物质燃烧影响。最后,对3个区域的气溶胶与痕量气体按季节作相关性分析发现:黄海地区AOD_(fine)在夏秋两季与SO_2的相关性较强(R0.5),主要由于夏秋两季的温湿度大,利于发生气—粒转化;东海地区夏季HCHO与AOD_(fine)相关性较明显(R=0.57);南海春季HCHO与AOD_(fine)相关性较好(R=0.57),呈现出区域与季节性的变化。最终发现,气溶胶与痕量气体随着时空变化存在相关关系。 相似文献
12.
Mark Broich Matthew C. Hansen Peter Potapov Bernard Adusei Erik Lindquist Stephen V. Stehman 《International Journal of Applied Earth Observation and Geoinformation》2011
Monitoring loss of humid tropical forests via remotely sensed imagery is critical for a number of environmental monitoring objectives, including carbon accounting, biodiversity, and climate modeling science applications. Landsat imagery, provided free of charge by the U.S. Geological Survey Center for Earth Resources Observation and Science (USGS/EROS), enables consistent and timely forest cover loss updates from regional to biome scales. The Indonesian islands of Sumatra and Kalimantan are a center of significant forest cover change within the humid tropics with implications for carbon dynamics, biodiversity maintenance and local livelihoods. Sumatra and Kalimantan feature poor observational coverage compared to other centers of humid tropical forest change, such as Mato Grosso, Brazil, due to the lack of ongoing acquisitions from nearby ground stations and the persistence of cloud cover obscuring the land surface. At the same time, forest change in Indonesia is transient and does not always result in deforestation, as cleared forests are rapidly replaced by timber plantations and oil palm estates. Epochal composites, where single best observations are selected over a given time interval and used to quantify change, are one option for monitoring forest change in cloudy regions. However, the frequency of forest cover change in Indonesia confounds the ability of image composite pairs to quantify all change. Transient change occurring between composite periods is often missed and the length of time required for creating a cloud-free composite often obscures change occurring within the composite period itself. In this paper, we analyzed all Landsat 7 imagery with <50% cloud cover and data and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify forest cover loss for Sumatra and Kalimantan from 2000 to 2005. We demonstrated that time-series approaches examining all good land observations are more accurate in mapping forest cover change in Indonesia than change maps based on image composites. Unlike other time-series analyses employing observations with a consistent periodicity, our study area was characterized by highly unequal observation counts and frequencies due to persistent cloud cover, scan line corrector off (SLC-off) gaps, and the absence of a complete archive. Our method accounts for this variation by generating a generic variable space. We evaluated our results against an independent probability sample-based estimate of gross forest cover loss and expert mapped gross forest cover loss at 64 sample sites. The mapped gross forest cover loss for Sumatra and Kalimantan was 2.86% of the land area, or 2.86 Mha from 2000 to 2005, with the highest concentration having occurred in Riau and Kalimantan Tengah provinces. 相似文献
13.
Acquisition probability differences in cloud coverage of the available Landsat observations over mainland Southeast Asia from 1986 to 2015 总被引：1，自引：0，他引：1
Landsat data are the longest available records that consistently document global change. However, the extent and degree of cloud coverage typically determine its usability, especially in the tropics. In this study, scene-based metadata from the U.S. Geological Survey Landsat inventories, ten-day, monthly, seasonal, and annual acquisition probabilities (AP) of targeted images at various cloud coverage thresholds (10% to 100%) were statistically analyzed using available Landsat TM, ETM+, and OLI observations over mainland Southeast Asia (MSEA) from 1986 to 2015. Four significant results were found. First, the cumulative average acquisition probability of available Landsat observations over MSEA at the 30% cloud cover (CC) threshold was approximately 41.05%. Second, monthly and ten-day level probability statistics for the 30% CC threshold coincide with the temporal distribution of the dry and rainy seasons. This demonstrates that Landsat images acquired during the dry season satisfy the requirements needed for land cover monitoring. Third, differences in acquisition probabilities at the 30% CC threshold are different between the western and eastern regions of MSEA. Finally, the ability of TM, ETM+, and OLI to acquire high-quality imagery has gradually enhanced over time, especially during the dry season, along with consequently larger probabilities at lower CC thresholds. 相似文献
14.
15.
遥感臭氧产品对于监测大气臭氧的时空分布及变化规律十分重要。然而,搭载于Aura卫星上的臭氧监测仪器提供的臭氧总量产品OMTO3e（ozone monitoring total ozone level 3 expanded）,自2006年末开始出现信息缺失问题,每个数据的缺失区域占到三分之一甚至更多,严重阻碍了该产品的正常使用。根据OMTO3e数据的特点,针对包括中国大陆的矩形区域提出了一种时相拟合法来进行缺失数据的修复。该方法考虑多个时相的空间信息,首先选取参考像元,然后利用参考像元求得回归关系,并通过加权求和得到缺失数据的预测值。模拟实验和真实实验证明,相对于传统方法,所提方法具有更高的修复精度。 相似文献
16.
大量研究利用PathfinderAVHRR NDVI资料分析植被状况与气温、降水等气候要素之间的关系。许多分析指出Pathfinder资料包含误差 ,并分析这些资料误差对大尺度NDVI 气温耦合关系检测结果的影响。利用奇异值分解方法 (SVD) ,通过比较不同NDVI资料误差情况下北半球春季NDVI对气温变化响应的时空特征的差异 ,对资料误差造成的分析结果的可靠性进行判断。考虑了 4种误差形式 ,分别是不同强度的连续误差、不连续误差、强火山喷发造成的误差及趋势误差。分析结果表明 ,利用SVD分析大尺度的NDVI 气温耦合特征时 ,允许的NDVI资料误差的最大上限阈值大致在 0 5σ左右。PathfinderAVHRR NDVI原始资料包含的误差很可能低于此阈值 ,得到的分析结果有较高的可信度。此外 ,在不知道NDVI原始资料误差的情况下进行植被对气候变化响应的检测时 ,可以借鉴此方法对结果的可靠性进行检查和验证。 相似文献
17.
北极臭氧年际变化特征及其与极涡的关系 总被引：2，自引：0，他引：2
利用风云三号卫星搭载的紫外臭氧总量探测仪(TOU)和国际同类卫星的臭氧总量数据对1979年—2011年北半球春季臭氧特征进行了分析,发现北极臭氧年际变化显著,它与平流层温度变化一致(相关系数为0.75)。北极臭氧损耗异常强弱年的月均和日变化特征有明显差异,春季北极臭氧损耗强年有明显的化学损耗过程(1997年和2011年),而弱年化学作用影响不明显(1999年和2010年)。损耗弱年的日变化型在不同年份特征不同,它的臭氧变化可能更多受天气过程的影响。综合分析北极涛动、极涡和平流层温度等大气环流背景场的变化,表明春季北极臭氧损耗强弱受大气环流变化影响。北极涛动指数正位相,极涡偏强偏冷,北极臭氧损耗异常偏高。北极涛动指数负位相,极涡偏弱偏暖,北极臭氧损耗异常偏低。 相似文献
18.
基于先进的微波扫描辐射计AMSR-E/2观测的辐射值,利用-维变分算法(1D-Var)反演各类水成物(云水、雨水和云冰)的垂直廓线,并对其反演结果进行检验。以2014年8月台风"夏浪"为例,分两步对变分反演的云微物理参数进行了检验。首先,将反演的各类水成物含量补充到辐射传输模式的输入场,观测算子模拟的AMSR-2各通道亮温与实况观测相比非常接近,可以很好地模拟出台风外形、强度及螺旋结构。其次,将反演的水成物廓线与载在Cloud Sat上的云雷达CPR同时段观测的雷达反射率因子进行对比,发现反演出的云水、雨水含量大值区与毫米波云雷达观测的雷达反射率因子高值区一一对应,进一步说明1D-Var反演的水成物参数精度很高。然而,由于星载AMSR-E/2观测通道少且空间分辨率低,对尺度较小、较薄的云不敏感,同时对云层较厚的密闭云区和多层云区反演能力也有限。 相似文献
19.
Spatio‐temporal prediction and forecasting of land surface temperature (LST) are relevant. However, several factors limit their usage, such as missing pixels, line drops, and cloud cover in satellite images. Being measured close to the Earth's surface, LST is mainly influenced by the land use/land cover (LULC) distribution of the terrain. This article presents a spatio‐temporal interpolation method which semantically models LULC information for the analysis of LST. The proposed spatio‐temporal semantic kriging (ST‐SemK) approach is presented in two variants: non‐separable ST‐SemK (ST‐SemKNSep) and separable ST‐SemK (ST‐SemKSep). Empirical studies have been carried out with derived Landsat 7 ETM+ satellite images of LST for two spatial regions: Kolkata, India and Dallas, Texas, U.S. It has been observed that semantically enhanced spatio‐temporal modeling by ST‐SemK yields more accurate prediction results than spatio‐temporal ordinary kriging and other existing methods. 相似文献
20.
《ISPRS Journal of Photogrammetry and Remote Sensing》2007,61(6):355-370
Point cloud acquisition by using laser scanners provides an efficient way for 3D as-built modelling of industrial installations. Covering such an installation with point cloud data often requires data acquisition from multiple standpoints. Before the actual modelling can start the transformation parameters of all scans need to be determined. Two methods to register point clouds of industrial scenes with different coordinate definitions are presented. Corresponding object models in different scans are used to determine the translation and rotation parameters of the scans. The first method, called Indirect method, is a two-step approach as object fitting and registration of the scenes is done separately. The second method, called Direct method simultaneously determines the shape and pose parameters of the objects as well as the registration parameters. Both methods are designed such that optimal use can be made of the knowledge of shapes present in industrial environments. Compared to ICP the presented approach combines registration and modelling and thus avoids the accumulation of errors. Furthermore, the simultaneous registration of multiple scans is possible. The presented approaches are based on non-linear least squares and provide quality measures in the form of covariance matrix of the estimated parameters, which can be used to decide if more scans are needed, and how and where they should be captured. Results are presented on some point cloud data-sets from actual industrial sites, where registration was done without using any artificial targets. 相似文献