CAS Institute of Remote Sensing Applications

Beijing, China

CAS Institute of Remote Sensing Applications

Beijing, China
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Yang X.,CAS Institute of Remote Sensing Applications | Li X.,National Oceanic and Atmospheric Administration | Pichel W.G.,The Center for Satellite Applications and Research | Li Z.,CAS Institute of Remote Sensing Applications
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

In this paper, we perform a comparison of wind speed measurements from the ENVISAT Advanced Synthetic Aperture Radar (ASAR), the MetOp-A Advanced Scatterometer (ASCAT), the U.S. National Data Buoy Center's moored buoys, and the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model. These comparisons were made in near U.S. coast regions over a 17-month period from March 2009 to July 2010. The ASAR wind speed retrieval agreed well with the scatterometer and model estimates, with mean differences ranging from-0.69 to 0.85 m/s and standard deviations between 1.16 and 1.77 m/s, depending upon the ASAR beam mode type. The results indicate that ASAR-derived ocean surface wind speeds are as accurate as the ASCAT and NOGAPS wind products. Comparisons between ASCAT winds and synthetic aperture radar (SAR) winds averaged at different spatial resolutions show very little change. This demonstrates that it is suitable that the scatterometer wind retrieval geophysical model function, i.e., CMOD5, is used for SAR wind retrieval. The impact of C-band VV polarization SAR calibration error on wind retrieval is also discussed. © 2011 IEEE.

Li W.,George Mason University | Yanga C.,George Mason University | Yang C.,CAS Institute of Remote Sensing Applications
International Journal of Geographical Information Science | Year: 2010

The increased popularity of standards for geospatial interoperability has led to an increasing number of geospatial Web services (GWSs), such as Web Map Services (WMSs), becoming publicly available on the Internet. However, finding the services in a quick and precise fashion is still a challenge. Traditional methods collect the services through centralized registries, where services can be manually registered. But the metadata of the registered services cannot be updated timely. This paper addresses the above challenges by developing an effective crawler to discover and update the services in (1) proposing an accumulated term frequency (ATF)-based conditional probability model for prioritized crawling, (2) utilizing concurrent multi-threading technique, and (3) adopting an automatic mechanism to update the metadata of identified services. Experiments show that the proposed crawler achieves good performance in both crawling efficiency and results' coverage/liveliness. In addition, an interesting finding regarding the distribution pattern of WMSs is discussed. We expect this research to contribute to automatic GWS discovery over the large-scale and dynamic World Wide Web and the promotion of operational interoperable distributed geospatial services. © 2010 Taylor & Francis.

Li X.,College Park | Zhang J.A.,National Oceanic and Atmospheric Administration | Yang X.,CAS Institute of Remote Sensing Applications | Pichel W.G.,College Park | And 3 more authors.
Bulletin of the American Meteorological Society | Year: 2013

Sea surface imprints of 83 hurricanes show features such as eye structure, mesovortices, rainbands, and arc clouds, along with rarities such as high winds within an eye. Atlantic tropical cyclones and western Pacific counterpart typhoons have been extensively monitored from operational polar-orbiting and geostationary satellite sensors. The striking tropical cyclone cloud pictures taken by these conventional weather satellites have appeared in many journal/magazine covers, newspapers, and television programs. These images are acquired by passive remote sensing instruments operating in the visible and infrared (IR) bands. These images are viewed to gather information about the cloud-top structure of the tropical cyclones at kilometer spatial resolution. Microwave data are also used extensively for tropical cyclone analysis with advance of spaceborne microwave remote sensing.

Wu C.,CAS Institute of Remote Sensing Applications | Wu C.,University of Toronto | Chen J.M.,University of Toronto | Huang N.,CAS Institute of Remote Sensing Applications
Remote Sensing of Environment | Year: 2011

The approach of using primarily satellite observations to estimate ecosystem gross primary production (GPP) without resorting to interpolation of many surface observations has recently shown promising results. Previous work has shown that the remote sensing based greenness and radiation (GR) model can give accurate GPP estimates in crops. However, the feasibility of its application and the model calibration to other ecosystems remain unknown. With the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) images and the surface based estimates of photosynthetically active radiation (PAR), we provide an analysis of the GR model for estimating monthly GPP using flux measurements at fifteen sites, representing a wide range of ecosystems with various canopy structures and climate characteristics. Results demonstrate that the GR model can provide better estimates of GPP than that of the temperature and greenness (TG) model for the overall data classified as non-forest (NF), deciduous forest (DF) and evergreen forest (EF) sites. Calibration of the GR model is also conducted and has shown reasonable results for all sites with a root mean square error of 47.18gC/m2/month. Different coefficients acquired for the three plant functional types indicate that there are shifts of importance among various factors that determine the monthly vegetation GPP. The analysis firstly shows the potential use of the GR model in estimating GPP across biomes while it also points to the needs of further considerations in future operational applications. © 2011 Elsevier Inc.

Duan A.,CAS Institute of Atmospheric Physics | Wang M.,University of Chinese Academy of Sciences | Lei Y.,CAS Institute of Remote Sensing Applications | Cui Y.,CAS Institute of Atmospheric Physics
Journal of Climate | Year: 2013

The impacts of the thermal forcing over the Tibetan Plateau (TP) in spring on changes in summer rainfall in China are investigated using historical records from the period between 1980 and 2008. The spring sensible heat (SH) flux and snow depth over the TP both decreased over this time period, although the trend in SH was more significant than that in snow depth. The similarity between patterns of precipitation trends over China and corresponding patterns of regression coefficients on the leading mode of spring SH change over the TP demonstrates the distinct contribution of changes in TP SH during spring. Enhanced precipitation in southern China was accompanied by increases in heavy rainfall, precipitation intensity, and the frequency of precipitation events, while reduced precipitation in northern China and northeastern China was primarily associated with decreases in the frequency of precipitation events. Further analysis using observational data and numerical simulations reveals that the reductions in SH over the TP have weakened the monsoon circulation and postponed the seasonal reversal of the land-sea thermal contrast in East Asia. In addition, the positive spring SH anomaly may generate a stronger summer atmospheric heat source over the TP due to the positive feedback between diabatic heating and local circulation. © 2013 American Meteorological Society.

Tao M.,CAS Institute of Remote Sensing Applications | Tao M.,University of Chinese Academy of Sciences | Chen L.,CAS Institute of Remote Sensing Applications | Su L.,CAS Institute of Remote Sensing Applications | Tao J.,CAS Institute of Remote Sensing Applications
Journal of Geophysical Research: Atmospheres | Year: 2012

Haze clouds often form over the North China Plain (NCP) of eastern China, where large amounts of aerosol particles and their precursors are emitted. To obtain general insights into regional pollution, a large-scale, long-term study was conducted using A-Train satellite observations, ground measurements, and meteorological data. Contrary to previous analyses, most of the haze clouds appeared to form abruptly (within 2-3h). Case studies show that natural sources contribute significantly to the formation of regional haze. Dust plumes can mix with local pollutants, causing smog clouds to form abruptly, while moist airflows can cause widespread haze-fog pollution. The combined observations revealed highly inhomogeneous haze clouds, in terms of both vertical and horizontal distribution, leading to clear discrepancies between site measurements near the surface and satellite observations at the top of the atmosphere. Surprisingly, prevailing dust plumes, which are closely connected with the haze clouds, were observed in winter. Airborne dust and water vapor transported from outside the region are the main drivers of regional haze over the NCP. Accumulation of local pollutants also leads to common occurrences of urban smog; however, the occurrence of most haze clouds shows no obvious correlation with local pollution. Local- and regional-scale haze pollution are common over the NCP, but they have differing formation mechanisms, and contrasting chemical and physical properties. The present findings improve our understanding of heavy pollution over eastern China and its links to climate. © 2012 American Geophysical Union. All Rights Reserved.

Xin X.,CAS Institute of Remote Sensing Applications | Liu Q.,CAS Institute of Remote Sensing Applications
Hydrology and Earth System Sciences | Year: 2010

A Two-layer Surface Energy Balance Parameterization Scheme (TSEBPS) is proposed for the estimation of surface heat fluxes using Thermal Infrared (TIR) data over sparsely vegetated surfaces. TSEBPS is based on the theory of the classical two-layer energy balance model, as well as a set of new formulations derived from assumption of the energy balance at limiting cases. Two experimental data sets are used to assess the reliabilities of TSEBPS. Based on these case studies, TSEBPS has proven to be capable of estimating heat fluxes at vegetation surfaces with acceptable accuracy. The uncertainties in the estimated heat fluxes are comparable to in-situ measurement uncertainties. © 2010 Author(s).

Wu B.,CAS Institute of Remote Sensing Applications | Li Q.,CAS Institute of Remote Sensing Applications
International Journal of Applied Earth Observation and Geoinformation | Year: 2012

This study presents a crop planting and type proportion (CPTP) method for crop acreage estimation of complex and diverse agricultural landscapes. CPTP has three major components: (1) Crop planting proportion (CPP), estimated with wide-swath satellite remote sensing data to completely cover the monitoring area by segmenting cropped and non-cropped areas through unsupervised classification. (2) Crop type proportion (CTP), estimated by transect sampling and a special GPS-Video-GIS instrument (GVG) and a visual interpretation of crop type proportion in collected pictures for different strata. (3) Multiplication of CPP and CTP with arable land area at the strata level, summed to the province and national level. Validation has been done with in situ data for different agricultural landscapes over China. Both CPP estimation with remote sensing data and CTP estimation through ground survey have a high accuracy with average relative error (RE) and root mean square error (RMSE) equal to 1.42% and 1.67% for CPP and to 2.63% and 2.25% for CTP. The RE for crop acreage estimation equals to 4.09%. The CPTP method thus has a high accuracy, yields timely information at low costs, and is robust and provides objective results. The study concludes that the CPTP method can be used for large area crop acreage estimation of complex agriculture landscapes. © 2011 Elsevier B.V.

Lei Y.,CAS Institute of Remote Sensing Applications | Duan A.,CAS Institute of Atmospheric Physics
International Journal of Climatology | Year: 2011

Prolonged dry episodes, defined by the 90th percentile of long durations without efficient precipitation (above the 0.1 mm/day threshold) in both the wet and dry seasons, have been investigated from 1958 to 2008 at 404 stations over China. Associated with droughts over northern China in summer, the enhancement of the prolonged dry episode duration is an essential feature, together with a lack of precipitation and the negative Palmer drought severity index (PDSI) in the wet season. In the dry season, durations of prolonged dry episodes have significantly increased over southern China and the Yellow River valley during the last 51 years. The prolonged dry episodes highlight the impact of a decrease in precipitation frequency, and are useful for representing short-term droughts, particularly over semi-arid regions and in the dry season. The occurrence of the maximum prolonged dry episodes over vulnerable regions in the early twenty-first century is suggestive of a greater risk of droughts during both the wet and dry seasons in a warmer climate over China. © 2010 Royal Meteorological Society.

Meng J.,CAS Institute of Remote Sensing Applications | Du X.,CAS Institute of Remote Sensing Applications | Wu B.,CAS Institute of Remote Sensing Applications
International Journal of Digital Earth | Year: 2013

While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties, the temporal resolution of the data is rather low, which can be easily made worse by cloud contamination. In contrast, although Moderate Resolution Imaging Spectroradiometer (MODIS) can only achieve a spatial resolution of 250 m in its normalised difference vegetation index (NDVI) product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution and high temporal resolution of different data sources, a new method (Spatial and Temporal Adaptive Vegetation index Fusion Model [STAVFM]) for blending NDVI of different spatial and temporal resolutions to produce high spatial-temporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). STAVFM defines a time window according to the temporal variation of crops, takes crop phenophase into consideration and improves the temporal weighting algorithm. The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of HJ-1 CCD NDVI to generate an NDVI dataset with both high spatial and high temporal resolution. An application of the generated NDVI dataset in crop biomass estimation was provided. An average absolute error of 17.2% was achieved. The estimated winter wheat biomass correlated well with observed biomass (R2 of 0.876). We conclude that the new dataset will improve the application of crop biomass estimation by describing the crop biomass accumulation in detail. There is potential to apply the approach in many other studies, including crop production estimation, crop growth monitoring and agricultural ecosystem carbon cycle research, which will contribute to the implementation of Digital Earth by describing land surface processes in detail. © 2013 Taylor & Francis.

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