Estimation of air temperature from MODIS data in east China

Air temperature, T _a, with high spatial and temporal resolution is desired for global change, agricultural disaster, land surface studies, and modelling applications. A statistical algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) data is developed for daytime T _a retrievals over east China at a resolution of 0.05° × 0.05°. The approach first applies a statistical regression of the first guess, i.e. the preliminary estimate, of T _a to MODIS 11 μm and 12 μm brightness temperature (T _11μm and T _12μm) and site data (longitude, latitude and altitude) for east China. Then the first guess of T _a is further corrected with a series of bias equations for different latitude zones in east China. Further quantitative validation with measured T _a using 335 synoptic weather stations for the whole of 2006 indicates that the algorithm performs well with overall statistics of R = 0.96, RMSE = 3.23°C, and bias = ?0.09°C. 75% of the estimated T _a is within 3°C of the actual T _a and 92% of the estimated T _a is within 5°C of the actual T _a. This bias correction algorithm can be applied to other geostationary and sun-synchronous satellite instruments for T _a retrieval.     

Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data

A vegetation index (VI) model for predicting evapotranspiration (ET) from data from the Moderate Resolution Imaging Spectrometer (MODIS) on the EOS-1 Terra satellite and ground meteorological data was developed for riparian vegetation along the Middle Rio Grande River in New Mexico. Ground ET measurements obtained from eddy covariance towers at four riparian sites were correlated with MODIS VIs, MODIS land surface temperatures (LSTs), and ground micrometeorological data over four years. Sites included two saltcedar (Tamarix ramosissima) and two Rio Grande cottonwood (Populus deltoides ssp. Wislizennii) dominated stands. The Enhanced Vegetation Index (EVI) was more closely correlated (r=0.76) with ET than the Normalized Difference Vegetation Index (NDVI; r=0.68) for ET data combined over sites and species. Air temperature (T_a) measured over the canopy from towers was the meteorological variable that was most closely correlated with ET (r=0.82). MODIS LST data at 1- and 5-km resolutions were too coarse to accurately measure the radiant surface temperature within the narrow riparian corridor; hence, energy balance methods for estimating ET using MODIS LSTs were not successful. On the other hand, a multivariate regression equation for predicting ET from EVI and T_a had an r²=0.82 across sites, species, and years. The equation was similar to VI-ET models developed for crop species. The finding that ET predictions did not require species-specific equations is significant, inasmuch as these are mixed vegetation zones that cannot be easily mapped at the species level.     

Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa

The estimation of near surface air temperature (Ta) is useful for a wide range of applications such as agriculture, climate related diseases and climate change studies. Air temperature is commonly obtained from synoptic measurements in weather stations. In Africa, the spatial distribution of weather stations is often limited and the dissemination of temperature data is variable, therefore limiting their use for real-time applications. Compensation for this paucity of information may be obtained by using satellite-based methods. However, the derivation of near surface air temperature (Ta), from the land surface temperature (Ts) derived from satellite is far from straight forward. Some studies have tried to derive maximum Ta from satellites through regression analysis but the accuracy obtained is quite variable according to the study. The main objective of this study was to explore the possibility of retrieving high-resolution Ta data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Ts products over different ecosystems in Africa. First, comparisons between night MODIS Ts data with minimum Ta showed that MODIS nighttime products provide a good estimation of minimum Ta over different ecosystems (with (ΔTs − Ta) centered at 0 °C, a mean absolute error (MAE) = 1.73 °C and a standard deviation = 2.4 °C). Secondly, comparisons between day MODIS Ts data with maximum Ta showed that (ΔTs − Ta) strongly varies according to the seasonality, the ecosystems, the solar radiation, and cloud-cover. Two factors proposed in the literature to retrieve maximum Ta from Ts, i.e. the Normalized Difference Vegetation Index (NDVI) and the Solar Zenith Angle (SZA), were analyzed. No strong relationship between (ΔTs − Ta) and (i) NDVI and (ii) SZA was observed, therefore requiring further research on robust methods to retrieve maximum Ta.     

Evaluation of MODIS data for improved monitoring of the Caspian Sea

Moderate-Resolution Imaging Spectroradiometer (MODIS) optical and infrared data are used to monitor changes in the Caspian Sea coastline. The information extracted from MODIS images is converted into total water volume and mean lake level by combining a digital elevation model (DEM) with remote-sensing data. The elevation estimates were enhanced by reprocessing the MODIS data at the sub-pixel scale. The water volume variations estimated from MODIS data along with DEM are compared to other estimations derived from altimetry data sets, and show fair agreement.     

Detection of haze and its intensity based on visibility and relative humidity estimated from MODIS data

Over recent years, air pollution has become a serious environmental problem with frequent occurrence of hazy days in many Chinese cities. In this study, a satellite-based method was developed to detect haze and its intensity for the Chinese city of Nanjing. This detection was based on the joint consideration of two indices, visibility, and relative humidity. They were determined from the Moderate Resolution Imaging Spectroradiometer-derived aerosol optical thickness, surface temperature, and precipitable water vapour data. Evaluated against the in situ measured results, haze and its intensity were found to be detected at a maximum accuracy of 81.7% and 60%, respectively. Of the two indices, visibility plays a more important role than relative humidity in affecting the detection accuracy. It is concluded that it is feasible to detect haze and its intensity from satellite data.     

Evaluation of MODIS water vapour products over China using radiosonde data

Radiosonde data collected from 83 stations in China from January to December 2012 were used to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) and thermal infrared (IR) total precipitable water vapour (PWV) products. The results indicate that MODIS NIR PWV products shows better agreement with radiosonde data than with IR PWV products, with the correlation coefficients up to 0.95. The root mean square errors (RMSEs) of NIR PWV range from 2 to 8 mm with different stations, which shows significant regional differences over China. The mean RMSE is about 5.03 mm (~35%) with a positive deviation of 2.56 mm (~18%), indicating the occurrence of a slight overestimation. Moreover, MODIS IR PWV during night-time has a better agreement with radiosonde PWV than that during daytime. The mean RMSE of IR PWV during daytime was ~6.02 mm (~42%), with a positive deviation of 1.54 mm (~11%). The mean RMSE of IR PWV during night-time was ~5.81 mm (~40%), with a negative deviation of approximately ?0.04 mm (~0.25%). Both the NIR and IR PWV products during daytime tend to be higher than radiosonde PWV.     

Red tide detection in the Strait of Hormuz (east of the Persian Gulf) using MODIS fluorescence data

A monstrous red tide appeared on October 2008 and expanded to the west on November 2008 off the Iranian coasts in the Hormuz Strait (east of the Persian Gulf). MODIS satellite data, hydrographic and bio-optical field measurements were used to detect the red tide. MODIS fluorescence line height (FLH in w m^?2 μm^?1 sr^?1) data showed the highest correlation with near-concurrent in situ chlorophyll concentration of 0.74 (100(FLH))^1.23 (r?=?0.9, n?=?44). In contrast, the band-ratio Chlorophyll product of MODIS showed more inconsistency with in situ chlorophyll data due to the interference of other water constituents. High FLH value patches >0.18 were confirmed to be located at the medium to high (10⁴–10⁶ cells l^?1) concentrations of Cochlodinium polykrikoides, and also showed a chlorophyll anomaly >1 mg m^?3, which means the potential of red tide occurrences. The FLH imagery also showed that the bloom started in early September along Bandar-Abbas port, and developed and moved to the west along the coastal regions. The results revealed that MODIS FLH and enhanced RGB (ERGB) imagery plus in situ data are adequate tools for red tide monitoring.     

Evaluating drought response of Southern Cape Indigenous Forests,South Africa,using MODIS data

Indigenous forests in South Africa cover less than 0.5% of the total land area but are a valued resource under threat from fragmentation, fires, exploitation, and climate change. The largest indigenous forest complex is located along the southern coast of the Western Cape Province. This complex is made up of sub-forests distinguished by different structural and edaphoclimatic attributes. It has been hypothesized that these sub-forests exhibit different resistance to stressors, such as drought. A time series of MODIS 250 m enhanced vegetation index (EVI) data were used to characterize the foliage condition of the three distinctive sub-forests before, during, and after a severe drought in 2009. The goal was to determine how these sub-forests responded to this disturbance. EVI anomalies for the drought and post-drought periods were calculated using annual median EVI values, since removal of outliers based on quality control flags that accompany the MODIS products or noise-filtering techniques proved to be ineffective. Results of the study indicated that pre-drought foliage density EVI was not controlled by differences in water availability, but may have been due to other edaphoclimatic or structural attributes. Maximum foliage loss occurred one year after the driest year, indicating the cumulative effects of drought stress on forest production and retention of foliage. The hypothesized stress resistance capacity of the three sub-forests was found to correspond to their rate of post-drought recovery. There is a need to tie these satellite observations of forest drought response to ground observations of forest condition, growth, and specific site attributes.     

Characterizing post-fire recovery of fynbos vegetation in the Western Cape Region of South Africa using MODIS data

Post-fire recovery trajectories of five fynbos vegetation stands in the Western Cape Region of South Africa were characterized using moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 250 m data. Indices of NDVI recovery relative to pre-fire values or values from unburnt control plots indicated full recovery within 7 years and particularly rapid recovery in the first two post-fire years. Intra-stand variability of pixel NDVIs generally increased after fires and also exhibited a rapid recovery to pre-fire conditions. While stand age was the dominant determinant of NDVI recovery, drought interrupted the recovery pathways and this effect was amplified on drier, equator-facing slopes. Post-fire recovery characteristics of fynbos NDVI were found to be similar to those documented for chaparral vegetation in California despite contrasting rainfall and soil nutrient conditions in the two regions.     

地面气象资料数据访问接口设计与实现

针对用户对高质量、高时效气象数据服务的需求,在对气象资料服务现状剖析的基础上,基于MDOS数据库设计实现了地面气象资料数据访问接口。在提高数据服务效率的同时可屏蔽底层数据结构变化对用户应用的影响,保证数据服务的规范性、稳定性和安全性。     

Evaluating MODIS data for mapping wildlife habitat distribution

Habitat distribution models have a long history in ecological research. With the development of geospatial information technology, including remote sensing, these models are now applied to an ever-increasing number of species, particularly those located in areas in which it is logistically difficult to collect habitat data in the field. Many habitat studies have used data acquired by multi-spectral sensor systems such as the Landsat Thematic Mapper (TM), due mostly to their availability and relatively high spatial resolution (30 m/pixel). The use of data collected by other sensor systems with lower spatial resolutions but high frequency of acquisitions has largely been neglected, due to the perception that such low spatial resolution data are too coarse for habitat mapping. In this study we compare two models using data from different satellite sensor systems for mapping the spatial distribution of giant panda habitat in Wolong Nature Reserve, China. The first one is a four-category scheme model based on combining forest cover (derived from a digital land cover classification of Landsat TM imagery acquired in June, 2001) with information on elevation and slope (derived from a digital elevation model obtained from topographic maps of the study area). The second model is based on the Ecological Niche Factor Analysis (ENFA) of a time series of weekly composites of WDRVI (Wide Dynamic Range Vegetation Index) images derived from MODIS (Moderate Resolution Imaging Spectroradiometer – 250 m/pixel) for 2001. A series of field plots was established in the reserve during the summer–autumn months of 2001–2003. The locations of the plots with panda feces were used to calibrate the ENFA model and to validate the results of both models. Results showed that the model using the seasonal variability of MODIS-WDRVI had a similar prediction success to that using Landsat TM and digital elevation model data, albeit having a coarser spatial resolution. This suggests that the phenological characterization of the land surface provides an appropriate environmental predictor for giant panda habitat mapping. Therefore, the information contained in remotely sensed data acquired with low spatial resolution but high frequency of acquisitions has considerable potential for mapping the habitat distribution of wildlife species.     

Visualization of scattered meteorological data

Considers how rain-gauge data, scattered in two dimensions, aid the study of El Nino-caused rainstorms in normally arid coastal Peru. Continuous realization techniques can extract qualitative information from the data. The techniques described were developed with IBM Visualization Data Explorer, a general-purpose software package for scientific data visualization and analysis. Data Explorer provides tools for both scattered and gridded data     

Algorithms for estimation of air-specific humidity using TMI data

We developed two empirical algorithms for estimating the surface air-specific humidity (Q _a) at 10 m over the ocean using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) brightness temperature data. We used the in situ data included in the International Comprehensive Ocean-Atmosphere Data Set for 2003–2006 as true values in this study. We estimated the Q _a using the developed regression formulae and validated the results by comparing with moored buoy data. The biases of our product were relatively small, i.e. 0.03 and 0.29 g kg^–1 for TMI_4CH and TMI_9CH, respectively, when compared with other Q _a retrievals. Moreover, we investigated the relationship between the brightness temperature observed by each channel and the in situ Q _a. We concluded that the use of the brightness temperature determined by the 85 GHz polarized radiation can considerably reduce the bias.     

极轨气象卫星有效载荷航空校飞数据地理定位

航空校飞数据的地理定位方法用来确定数据中每一个像素的地理经纬度,它是整个数据处理过程的基础。介绍了一种用于航空校飞试验数据的地理定位方法。首先给出了问题的描述;其次建立了航迹和姿态模型;然后给出了地理定位方法的算法;最后给出计算结果及误差分析,验证了方法的可行性以及高精度。地理定位方法不仅仅可以用于极轨气象卫星的校飞试验数据处理,同时也适用于其他遥感卫星的校飞试验数据处理,具有非常重要的意义。     

基于HBase的气象地面分钟数据分布式存储系统

针对气象地面分钟数据要素多样、信息量大、产生频次高等特点,传统的关系型数据库系统在存储和管理数据上出现负载饱满、读写性能不理想等问题。结合对分布式数据库HBase的存储模型的研究,行主键(row key)采用时间加站号的方式设计了气象分钟数据存储结构模型,实现对海量气象数据的分布式存储和元信息管理。对HBase的唯一索引在面对气象业务的复杂查询用例时响应时间过长的问题,使用搜索引擎solr提供的API接口并参考气象业务中的查询用例对相关字段建立辅助索引,来满足业务检索时效。实验结果表明,该系统具有很好的存储能力和检索效率,入库效率最高可达每秒34000条,并且在常规查询用例的结果返回时效达到毫秒级,能够满足大规模气象数据在业务应用中对存储和查询时效的性能要求。     

Evaluation of SeaWiFS,MODIS Terra and MODIS Aqua coverage for studies of phytoplankton diurnal variability

Contemporaneous satellite ocean colour data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and MODIS Aqua instruments are consistently calibrated and uniformly processed using equivalent code and algorithms. These sensors cover the globe at different times of a local day. Combining the three instruments provides an unprecedented opportunity to monitor global and local oceanic phytoplankton fluctuations continuously throughout the day. While a daily maximum of 3 hours of coverage is expected from the three sensors, longer observation periods are achieved by combining hourly coverage from a number of consecutive days. The southern hemisphere is then observed continually between 9 am and 3 pm local time. The northern hemisphere is monitored for shorter periods, largely between 10 am and 2 pm local time. This study proposes methodologies to investigate diurnal variability in phytoplankton optical properties from satellite instruments. It also makes an initial attempt to extract diurnal phytoplankton trends from the data and highlights the requirements for accurate instrument calibration and algorithm consistency in ocean colour.     

SeaWiFS global data represented in MODIS land projections

Abstract

During and after the Gulf Conflict. DLR's,German Remote,Sensing Data Center (DFD) continuousry acquired NOAA-11 passes over the GunRegion showing smoke plume phenomena and surface conlamination effects both in desert and vegetated areas. The position of the receiving station in Oberpfaffenhofen, near Munich, meant that restrictions concerning the data's temporal and spatial resolution had to be accepted. Qualitative information regarding spatial distribution, height, thickness and some dynamic aspects of the smoke plumes were able to be derived. In addition to ihis, the investigation of satellite imagery during April, May, and June proved that large vegetated areas in the southern Mesopotamian region are obviously affected by the fall-out. As the affected region belongs to the most important agricultural areas in Iraq, a fundamental lack of food supply must be expected.     

Spectral shape-based temporal compositing algorithms for MODIS surface reflectance data

Spectral similarity metrics have previously been used to select representative spectra from a class for use in spectral mixture modeling. Since the tasks of spectral selection for spectral mixture modeling and spectral selection for temporal compositing are similar, these metrics may have utility for temporal compositing. This paper explores the use of two spectral similarity metrics, endmember average root mean square error (EAR) and minimum average spectral angle (MASA), for constructing temporal composites. EAR and MASA compositing algorithms were compared against four previously used algorithms, including maximum NDVI, minimum view zenith angle, minimum blue, and median red. A total of 10 different algorithms were used to create 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data over a 6-year period. Algorithm performance was assessed based on short-term temporal variability in spectral reflectance and in a selection of indices, both within a southwestern California study area and within five land-cover class subsets. EAR compositing produced the lowest variability for 4 out of 7 MODIS bands, as measured by the root mean square of time series residuals. MASA or EAR compositing produced the lowest root mean square residual values for all of the tested indices. To assess how compositing algorithms might affect remote sensing correlations with biophysical variables, correlations between indices calculated from different composites and live fuel moisture were compared. Correlations between indices and live fuel moisture were higher for shape-based composites compared with the standard composites.     

气象卫星资料虚拟存储系统设计与实现

利用服务器连接（SAS）技术和存储局域网（SAN）技术构建气象卫星资料存储系统。实现群集环境中计算机系统间的存储资源共享,设计虚拟存储管理软件对不同的物理存储设备进行逻辑管理,可以简化存储设备的使用,可以提高系统运行效率,国家卫星气象中心的气象卫星资料存储系统的运行结果表明,虚拟存储是解决群体环境中不同物理存储设备有效使用的一条切实可行的技术路线。     

Detecting and tracking regional outliers in meteorological data

Detecting spatial outliers can help identify significant anomalies in spatial data sequences. In the field of meteorological data processing, spatial outliers are frequently associated with natural disasters such as tornadoes and hurricanes. Previous studies on spatial outliers mainly focused on identifying single location points over a static data frame. In this paper, we propose and implement a systematic methodology to detect and track regional outliers in a sequence of meteorological data frames. First, a wavelet transformation such as the Mexican Hat or Morlet is used to filter noise and enhance the data variation. Second, an image segmentation method, λ-connected segmentation, is employed to identify the outlier regions. Finally, a regression technique is applied to track the center movement of the outlying regions for consecutive frames. In addition, we conducted experimental evaluations using real-world meteorological data and events such as Hurricane Isabel to demonstrate the effectiveness of our proposed approach.