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1.
中国陆地区域陆表温度业务化遥感反演算法及产品运行系统 总被引：7，自引：0，他引：7
地表温度反演的裂窗算法已成功应用于NOAA系列卫星热红外遥感数据。目前，裂窗算法中应用较为广泛的一种是Becker等人于1990年提出的局地裂窗算法，主要是通过辐射传输模型模拟不同地表条件和大气状况下，地表温度和发射率对红外辐射亮温的影响，从而发展出一个利用AVHRR4，5通道亮温数据反演地表温度的线性模型。在晴空无云和地表比辐射率能精确估算的情况下，Becker算法反演地表温度的精度在1K以内。Becker算法用Lowtran程序模拟计算地表辐射量，且模型中参数主要针对NOAA-9传感器特性得到。本文在Becker算法的基础上，针对NOAA-16／17传感器热红外通道光谱响应函数特性，利用最新的、计算光谱分辨率更高的MODTRAN程序模拟不同大气状况下，不同地表温度和发射率对NOAAAVHRR4，5通道辐射亮温响应特性的影响，改进Becker算法中模型参数，使之能适用于NOAA-16／17热红外数据。同时，本文利用植被指数NDVI，在中国陆地区域lkm分辨率最新地表分类数据的基础上，得到模型中需要的地表比辐射率参数，将改进的模型应用于1km分辨率NOAA17数据，得到了旬合成中国陆地区域范围地表温度，通过地面气象台站实测数据对比验证．取得了较好的结果。 相似文献
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Trend analysis of the Pathfinder AVHRR Land (PAL) NDVI data for the deserts of central Asia 总被引：4，自引：0，他引：4
We analyzed spatially averaged normalized difference vegetation index (NDVI) time series from the Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset of 11 desert and semidesert ecoregions in central Asia using standard statistical tests for discontinuities and trends. Results from the test for discontinuities reveal that seven ecoregions display significant differences in the data acquired by the AVHRRs on the National Oceanic and Atmospheric Administration satellite 11 (NOAA-11) versus the data acquired by AVHRR on other NOAA satellites (NOAA-7, NOAA-9, and NOAA-14). Across the more than 2/spl times/10/sup 6/ km/sup 2/ of deserts and semideserts in the selected central Asian ecoregions, a significant upward trend in NDVI is evident during the tenure of NOAA-11 (1989-1994). This trend is not found during any other period. We argue that the data from the PAL NDVI dataset for NOAA-11 will pose problems for land surface change analyses, if these significant sensor-related artifacts are ignored. We do not find these artifacts in data from the other three satellites (NOAA-7, NOAA-9, and NOAA-14). We suggest that the comparison of data from any combination of these three AVHRRs can be used for land surface change analyses, but that the inclusion of NOAA-11 AVHRR NDVI data in trend analyses may result in the detection of spurious trends. 相似文献
4.
Testing satellite and ground thermal imaging of low-temperature fumarolic fields: The dormant Nisyros Volcano (Greece) 总被引：1，自引：0，他引：1
E. Lagios S. Vassilopoulou V. Sakkas V. Dietrich B.N. Damiata A. Ganas 《ISPRS Journal of Photogrammetry and Remote Sensing》2007,62(6):447-460
The Nisyros Volcano (Greece) was monitored by satellite and ground thermal imaging during the period 2000–2002. Three night-scheduled Landsat-7 ETM+ thermal (band 6) images of Nisyros Island were processed to obtain land surface temperature. Ground temperature data were also collected during one of the satellite overpasses. Processed results involving orthorectification and 3-D atmospheric correction clearly show the existence of a thermal anomaly inside the Nisyros Caldera. This anomaly is associated mainly with the largest hydrothermal craters and has land surface temperatures 5–10 °C warmer than its surroundings. The ground temperature generally increased by about 4 °C inside the main crater over the period 2000–2002. Ground thermal images of the hydrothermal Stephanos Crater were also collected in 2002 using a portable thermal infrared camera. These images were calibrated to ground temperature data and orthorectified. A difference of about 0–2 °C was observed between the ground thermal images and the ground temperature data. The overall study demonstrates that satellite remote sensing of low-temperature fumarolic fields within calderas can provide a reliable long-term monitoring tool of dormant volcanoes that have the potential to reactivate. Similarly, a portable thermo-imager can easily be deployed for real-time monitoring using telemetric data transfer. The operational costs for both systems are relatively low for an early warning system. 相似文献
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The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift on the RSP time series. 相似文献
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Shui-sen Chen Xiu-zhi Chen Wei-qi Chen Yong-xian Su Da Li 《International Journal of Applied Earth Observation and Geoinformation》2011
The analysis of the passive microwave radiance transfer equation certifies that there is a linear relationship between satellite-generated brightness temperatures (BT) and in situ observation temperature and that land surface temperature (LST) is largely influenced by vegetation cover conditions. Microwave polarization difference index (MPDI) is an effective indicator for characterizing the land surface vegetation cover density. Based on the analysis of LST models from AMSR-E BT with 6.9 GHz MPDI intervals at 0.04, 0.02 and 0.01, respectively, this paper developed a simplified LST regression model with MPDI-based five land cover types, combining observation temperatures from 86 meteorological observation stations. The study shows that smaller MPDI intervals can obtain higher accuracy of AMSR-E LST simulation, and that the combination of HDF Explorer and ArcGIS software was useful for automatically processing the pixel latitude, longitude and BT information from the AMSR-E HDF imagery files. The RMSE of the five LST simulation algorithms is between 1.47 and 1.92 °C, with an average LST retrieval error of 0.91–1.30 °C. Besides, only 7 polarization bands and 5 land surface types are required by the proposed simplified model. The new LST simulation models appears to be more effective for producing LST compared to past most studies, of which the accuracy used to be more than 2 °C. This study is one of the rare applications that combine the meteorological observation temperature with MPDI to produce the LST regression analysis algorithms with less RMSE from AMSR-E data. The results can be referred to similar areas of the world for LST retrieval or land surface process research, in particular under extreme bad weather conditions. 相似文献
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风云三号C星(FY-3C卫星)空间环境监测器(SEM)可监测轨道高度上的高能带电粒子(质子、电子和重离子)辐射环境及其引起的辐射剂量和表面充电等空间天气效应,是空间天气监测预警业务不可或缺的自主数据源之一。为验证FY-3C卫星高能粒子探测数据的有效性,需开展数据的定量检验工作。本文采用与同类卫星同类数据进行交叉比对的方式来进行检验。首先,根据一定的假设条件,对比对数据进行归一化处理,尽量消除不同卫星间观测时间、空间(星下点经、纬度和高度)、方向和能量范围等差异对高能粒子分布的影响,然后进行比对,最后计算比对数据间的相关系数、斜率和标准偏差等统计参数,并据此评价比对数据的一致性。通过空间天气平静期高能质子和高能电子与NOAA-18和FY-3B卫星数据的交叉比对可以看出,FY-3C卫星高能粒子数据与比对卫星数据具有较好的一致性。由于工作原理和技术指标相同,FY-3C与FY-3B卫星高能粒子数据的一致性更好,也证明了载荷技术状态的稳定性。通过对太阳质子事件和高能电子暴的观测实例证明,FY-3C卫星高能粒子数据能够准确地反映空间天气扰动事件的特征和强度。以上结果表明,FY-3C卫星高能粒子数据可信度较高,能够用于空间天气监测、预警以及研究工作。 相似文献
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本文根据地物光谱特性和卫星的信号接收原理，提出了一种利用气象卫星识别水体的简单而有效的方法，使得薄云覆盖下的水体和云影中的水体得到较好的识别效果。在洪水监测中使用该方法，可以充分利用气象卫星数据获取丰富的洪水动态信息．并以１９９１年江淮洪涝灾害为背景，对试验结果进行了分析． 相似文献
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XianWen Ding XiaoFeng Li 《International Journal of Applied Earth Observation and Geoinformation》2011
As an active microwave remote sensing sensor, synthetic aperture radar (SAR) can image the Earth surface with high spatial resolution in both day and night under all weather conditions. In this paper, a digital image processing technique was implemented to extract water area information from SAR images and the result is used to monitor the water area variation of Lake Dongting, the second largest freshwater lake in China. 8-year time series of European Space Agency's ENVISAT ASAR (Advanced Synthetic Aperture Radar) images acquired between 2002 and 2009 were obtained and a land-water classification scheme was implemented. Using independent in situ water level data measured at a lake-side hydrologic station during study period, we derived the relationship between water level and water area of Lake Dongting. The results show that, (1) during dry seasons, the water area is 518 km2 larger than that in the 1990s reported by Yangtze BHYRWRC (Bureau of Hydrology and Yangtze River Water Resources Commission), 2000; (2) the water area of Lake Dongting increased significantly in the 2000s after the Chinese Government's “return land to lake” policy took effect in 1998; (3) the water level of Lake Dongting could be low during a rainy season due to drought; but could be high in a dry season due to discharges from the upstream Three Gorges Dam. In addition, the relationship between water storage change and water area/level change is obtained. 相似文献
10.
Meng Qi Hu Fei Mao Han Sun Ying Yu Hou 《International Journal of Applied Earth Observation and Geoinformation》2011
Using NOAA/AVHRR 10-day composite NDVI data and 10-day meteorological data, including air temperature, precipitation, vapor pressure, wind velocity and sunshine duration, at 19 weather stations in the three-river-source region in the Qinghai–Tibetan Plateau in China from 1982 to 2000, the variations of NDVI and climate factors were analyzed for the purpose of studying the correlation between climate change and vegetation growth as represented by NDVI in this region. Results showed that the NDVI values in this region gradually grew from the west to the east, and the distribution was consistent with that of moisture status. The growing season came earlier due to climate warming, yet because of the reduction of precipitation, maximal NDVI during 1982–2000 did not show a significant change. NDVI related positively to air temperature, vapor pressure and precipitation, but negatively related to sunshine duration and wind velocity. Furthermore, the response of NDVI to climate change showed time lags for different climate factors. Water condition and temperature were found to be the most important factors effecting the variation of NDVI during the growing season in both the semi-arid and the semi-humid areas. In addition, NDVI had a better correlation with vapor pressure than with precipitation. The ratio of precipitation to evapotranspiration, representing water gain and loss, can be regarded as a comprehensive index to analyze NDVI and climate change, especially in areas where the water condition plays a dominant role. 相似文献
11.
Landsat (TM) imagery studies combined with photogeology, heliborne EM-radiometric interpretations and field data provided the fracture pattern in the eastern Chalkidiki peninsula, northern Greece. Processing of the respective data revealed the following four main directions of lineaments trending 070°–080°, 120°–130°, N-S and E-W. This fracture pattern is persistent in all geological units including the Tertiary basins and may represent reactivated older or even Tertiary fractures superimposed on all units. The control and the distribution of the major mineralization such as Pb---Zn (Au---Ag) massive sulphides, Mn (Fe) oxides, and porphyry Cu (Au) are of similar orientation to the deduced fracture pattern.These findings support the remote sensing is an important mineral exploration tool which can become quite effective when combined with ore deposit type, geochemical and geophysical data in partly explored areas. 相似文献
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A. Anand Beena Kumari S. R. Nayak Y. V. N. Krishnamurthy 《Journal of the Indian Society of Remote Sensing》2005,33(4):511-520
Tuna fishery resources are currently under exploited. The resource potential of tunas in the Indian Exclusive Economic Zone
(EEZ) beyond 50 m depths is around 2.09 lakh tonnes as estimated by Fishery Survey of India. The distribution and availability
of the tuna are governed by environmental factors like temperature, thermocline depth, availability of prey, visibility etc.
Remote sensing provides synoptic information on productivity in terms of chlorophyll and Sea Surface Temperature (SST). In
the present paper, satellite remote sensing data from Indian Remote Sensing Satellite IRS- P4 Ocean Colour Monitor (OCM) sensor
for chlorophyll-a and diffuse attenuation coefficient (K) and National Oceanic and Atmospheric Administration (NOAA) - Advanced
Very High Resolution Radiometer (AVHRR) sensor data for sea surface temperature were analysed and correlated within situ catch data of oceanic tunas, Skipjack(Katsuwonus pelamis) and Yellowfin tuna(Thunnus albacares), off Maharashtra coast. Higher catches were found to be associated with moderate to good primary productivity and in the
vicinity of thermal fronts. Relationship between Hooking rate and SST has shown that SST of 28–30°C range is optimum for skipjack
and 28–31°C for yellowfin tuna. Besides satellite derived chlorophyll and SST for identification of potential tuna fishing
zones, role of diffuse attenuation coefficient (K) for visibility factor is also discussed. 相似文献
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The most important advantage of the low resolution National Oceanic and Atmospheric Administration’s Advanced Very High Resolution
Radiometer (NOAA AVHRR) data is its high temporal frequency and high radiometric sensitivity which helps in vegetation detection
in the visible and near-infrared spectral regions. In areas where most of the crop cultivation is in large contiguous areas,
and if the AVHRR data are selected for time period such that the crop of interest is well discriminated from other crops,
these data can be used for monitoring vegetative growth and condition very effectively. The present study deals with the application
of AVHRR data for the monitoring of the wheat crop in its seventeen main growing districts of the Rajasthan state. The fourteen
date AVHRR data covering the entire growth period have been used to generate the normalized difference vegetation index (NDV1)
growth profile for the crop by masking the non-crop pixels following the two-date NDVI change method. The growth profile parameters
and other derived parameters, such as post-anthesis senescence rate and areas under the entire growth profile or under selected
growth periods have been related to the district average wheat yield through statistical regression models. Various methods
adopted for wheat pixels masking have been critically evaluated. It is found that the wheat yield can be predicted well by
the area under the profile in different growth periods. 相似文献
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Clouds contribute significantly to the formation of many of the natural hazards. Hence cloud mapping and its classification
becomes a major component of the various physical models which are used for forecasting natural hazards. The problem of cloud
data classification from NOAA AVHRR (advance very high resolution radiometer) satellite imagery using image transformation
techniques is considered in this paper. The singular value decomposition (SVD) scheme is used to extract the salient spectral
and textural features attributed to satellite snow and cloud data in visible and IR channels. The goals of this paper are
to discriminate between clear sky and clouds in an 8 × 8 pixel array of 1.1 km AVHRR data. If clouds are present then classify
them as low, medium or high range. This scheme can effectively segregate clouds and non-cloud features in the visible and
IR bands of the imagery. It can also classify clouds as low, medium or high range with a success rate of 70–90%. Computer-based
snow and cloud discrimination and automatic cloud classification system will help the forecaster in various climatological
applications, viz., energy balance estimation, precipitation forecasting, landslide forecasting, weather forecasting and avalanche
forecasting etc. 相似文献
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A. K. Mitra Sankar Nath A. K. Sharma 《Journal of the Indian Society of Remote Sensing》2008,36(3):243-253
Operational meteorology is perceived as a fuzzy environment in which information is vaguely defined. The mesoscale processes
such as fog, stratus and convection are generally dependent on the topography of the place and has always been difficult to
forecast for the meteorologists. The main objective of the present study is to introduce the concept of fuzzy inference system (FIS) in the prediction of fog. This approach uses the concept of a pure fuzzy logic system where the fuzzy rule base
consists of a collection of fuzzy IF-THEN rules. The fuzzy inference engine uses these fuzzy IF-THEN rules to determine a mapping from fuzzy sets in the input universe of discourse to fuzzy sets in the output universe of discourse
based on fuzzy logic principles. Basic weather elements, which affect weather characteristics of fog, are fuzzified. These
are then used in fuzzy weather prediction models based on fuzzy inferences. These models are simulated and the crisp results
obtained using developed defuzzification strategies are compared with the actual weather data. The basis of methodology is
to construct the fuzzy rule base domain from the available daily current weather observations in winter season over New Delhi.
The results reveal that dew point spread and rate of change of dew point spread are the most important parameters for the
formation of fog. The results further indicate that fog formation over New Delhi are dominant when (i) dew point is greater
then 7°C along with dew point spread between 1 and 3°C. (ii) rate of change of dew point spread must be negative and wind
speed should be less than 4 knots. This study presents a technique for predicting the probability of fog over New Delhi for
5–6 hours in advance. The skill score indicates that the performance of FIS is appreciably good. The method is found to be
promising for operational application. 相似文献
16.
Satellite data provides important inputs far estimating regional surface emisslviiy and surface temperature. The methodology for estimation of emissivity over heterogeneous areas is based on the calculation of fraction vegetation cover per pixel taking NDVI, reflectances of pure pixels as input. The surface temperature is calculated using a sptit-window equation, which depends on atmospheric water vapour, viewing angle and channel surface emissivities. In the present study model coefficients for atmospheric corrections to NOAA AVHRR thermal data Fqr tropical atmospheres have been derived with a view to operationally use the methodolpgy for generating land surface temperature information from satellite data. The results of the study show that the estimated temperature values are comparable with the ctimatological values over the region Suggesting the possible use of the methodology. 相似文献
17.
基于人工神经网络的赤潮卫星遥感方法研究 总被引：7，自引：1，他引：7
根据赤潮的卫星遥感探测机理，应用人工神经网络技术，建立和利用NOAA AVHRR可见光和热红外波段遥感数据的BP神经网络赤潮信息提取模型。应用实例显示。基于该人工神经网络方法可以提取赤潮发生地点和范围等信息，赤潮探测正确率达到78.5%。研究结果表明，应用人工神经网络方法提取赤潮信息是可行的。本文中建立的BP赤潮信息提取模型适当修改后可移植应用于其它传感器遥感数据进行赤潮信息提取。 相似文献
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Edward R. Valstar Rob G. H. H. Nelissen Johan H. C. Reiber Piet M. Rozing 《ISPRS Journal of Photogrammetry and Remote Sensing》2002,56(5-6)
Roentgen stereophotogrammetry is the most accurate Roentgen technique for three-dimensional assessment of micromotion of orthopaedic implants. The reported accuracy of Roentgen Stereophotogrammetric Analysis (RSA) ranges between 0.05 and 0.5 mm for translations and between 0.15° and 1.15° for rotations. Because of the high accuracy of RSA, small patient groups are in general sufficient to study the effect on prosthetic fixation due to changes in implant design, addition of coatings, or new bone cements. By assessing micromotion of a prosthesis in a short-term (i.e. 2 years) clinical RSA study, a prediction can be made on the chance of long-term (i.e. 10 years) loosening of the prosthesis. Therefore, RSA is an important measurement tool to screen new developments in prosthetic design, and to prevent large groups of patients from being exposed to potentially inferior designs.In this article, the basics of the RSA technique are explained, and the importance of clinical RSA studies is illustrated with two examples of clinical RSA studies which RSA delivered very valuable information. Thereafter, two recent developments in RSA that have been implemented at Leiden University Medical Center are presented: digital automated measurements in RSA radiographs and model-based RSA. 相似文献
20.
Abstract The ability to map and monitor terrestrial carbon is important in tropical regions where land conversion is intense and tropical moist forests store much of Earth's terrestrial carbon. The release of terrestrial carbon in the form of carbon dioxide could alter local, regional, and global weather, and enhance the greenhouse effect. This study analyzed the ability of coarse‐resolution Advanced Very High Resolution Radiometer (AVHRR) remote sensor data to quantify carbon stored in the Guaporé / Itenez River Basin in Bolivia and Brazil. This area was selected because of the amount of land conversion that has occurred there relative to other areas of the Amazon Basin. A supervised vegetation classification map was created with training sites acquired through fieldwork done in the area in summer 1998. Image pixels were classified as tropical moist forest, degraded tropical moist forest, cerrado, grasslands, degraded savanna, or bare ground. Estimated above and below‐ground carbon values of the different land cover types were applied to each class to calculate total carbon values. It was concluded that data such as AVHRR may be used to calculate the amount of carbon in terrestrial ecosystems in regional scale areas. 相似文献