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| 1 | Current issues in high-resolution earth observation technology显示文摘This paper reviewed the developments of the last ten years in the field of international high-resolution earth observation, and introduced the developmental status and plans for China's high-resolution earth observation program. In addition, this paper expounded the transformation mechanism and procedure from earth observation data to geospatial information and geographical knowledge, and examined the key scientific and technological issues, including earth observation networks, high-precision image positioning, image understanding, automatic spatial information extraction, and focus services. These analyses provide a new impetus for pushing the application of China's high-resolution earth observation system from a 'quantity' to 'quality' change, from China to the world, from providing products to providing online service. | LI DeRen TONG QingXi LI RongXing GONG JianYa ZHANG LiangPei | 2012 | Science China Earth Sciences2012，55，7： | 18 |
| 2 | Remote sensing based shrub above-ground biomass and carbon storage mapping in Mu Us desert,China显示文摘The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ecosystems.HJ-1A/B satellite data combined with field measurement data was used for the estimation of shrub AGB and carbon storage in the Mu Us desert,China.The correlations of shrub AGB and spectral reflectance of four bands as well as their combined vegetation indexes were respectively analyzed and stepwise regression analysis was employed to establish AGB prediction equation.The prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than others.Shrub AGB and carbon storage were mapped using the RVI based prediction model in final.The statistics showed the western Mu Us desert has relatively high AGB and carbon storage,and that the gross shrub carton storage in Mu Us desert reaches 16 799 200 t,which has greatly contributed to the carbon fixation in northern China. | XU Min 1,2,CAO ChunXiang 1,TONG QingXi 1,LI ZengYuan 3,ZHANG Hao 1,HE QiSheng 1,2,GAO MengXu 1,2,ZHAO Jian 1,2,ZHENG Sheng 1,2,CHEN Wei 1,2 & ZHENG LanFen 1 1State Key Laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China 2 Graduate School of the Chinese Academy of Sciences,Beijing 100049,China 3 Research Institute of Forest Resources and Information Techniques,Chinese Academy of Forestry,Beijing 10009,China | 2010 | Science China(Technological Sciences)2010，53，S1： | 5 |
| 3 | Framework and development of digital China显示文摘Digital China (DC) has recently drawn much attention. It is a strategic project for China in response to the challenge of sustainable development of population,re-source,and environment. Intending to establish the national information infra-structure (NⅡ),the DC project forms a solid foundation for Chinese informatization. In such an NⅡ,multi-sourced spatial data are integrated. They focus on various themes and have different space and time features. Based on the NⅡ,numerous applications and services can be developed so that spatial information will benefit everyone. Since lots of organizations,such as governments,universities,and en-terprises,are involved in the implementation of DC,the DC project will significantly prompt the relevant scientific research as well as economic progress in China. | WU Lun & TONG QingXi Institute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China | 2008 | Science China(Technological Sciences)2008，51，S1： | 5 |
| 4 | The application of hyperspectral remote sensing to coast environment investigation显示文摘Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast beaches and bottom matter,target recognition,mine detection,oil spill identification and ocean color remote sensing.Finally,what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended. | ZHANG Liang ZHANG Bin CHEN Zhengchao ZHENG Lanfen TONG Qingxi | 2009 | Acta Oceanologica Sinica2009，28，2： | 3 |
| 5 | Pro- gress in Hyperspectral Remote Sensing Sci-ence and Technology in China Over the Past Three Decades 显示文摘 | Qingxi Tong Yongqi Xue Lifu Zhang | 2014 | Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing2014，7，1： | 1 |
| 6 | Relating soil surface moisture to reflectance显示文摘 | Liu Weidong F. Baret Gu Xingfa Tong Qingxi Zheng Lanfen Zhang Bing | 2002 | Remote Sensing of Environment2002，，2： | 1 |
| 7 | A hyperspectral image compression algorithm based on wavelet transformation and fractal composition (AWFC)显示文摘Starting with a fractal-based image-compression algorithm based on wavelet transformation for hyperspectral images, the authors were able to obtain more spectral bands with the help of of hyperspectral remote sensing. Because large amounts of data and limited bandwidth complicate the storage and transmission of data measured by TB-level bits, it is important to compress image data acquired by hyperspectral sensors such as MODIS, PHI, and OMIS; otherwise, conventional lossless compression algorithms cannot reach adequate compression ratios. Other loss-compression methods can reach high compression ratios but lack good image fidelity, especially for hyperspectral image data. Among the third generation of image compression algorithms, fractal image compression based on wavelet transformation is superior to traditional compression methods,because it has high compression ratios and good image fidelity, and requires less computing time. To keep the spectral dimension invariable, the authors compared the results of two compression algorithms based on the storage-file structures of BSQ and of BIP, and improved the HV and Quadtree partitioning and domain-range matching algorithms in order to accelerate their encode/decode efficiency. The authors' Hyperspectral Image Process and Analysis System (HIPAS) software used a VC++6.0 integrated development environment (IDE), with which good experimental results were obtained. Possible modifications of the algorithm and limitations of the method are also discussed. | HU Xingtang ZHANG Bing ZHANG Xia ZHENG Lanfen TONG Qingxi | 2006 | Science China(Technological Sciences)2006，49，z2： | 1 |
| 8 | Calibratio performance evaluation of the spaceborne hyperspectral CHRIS imager显示文摘The CHRIS (Compact High Resolution Imaging Spectrometer) is a new imaging spectrometer, carried on board a new space platform called PROBA (Project for On Board Autonomy). The satellite was successfully launched in October 2001 by the European Space Agency (ESA). CHRIS operates over the visible/near infrared band (400-1050 nm). It has five work modes and can reach a maximum of 62 spectral bands. In this research, atmospheric correction based on hyperspectral images was performed on CHRIS images by using the popular radiance transfer code ACORN (Atmospheric Correction Now) and empirical algorithms. ACORN was also used to evaluate the calibration performance of CHRIS by the retrieved spectra of typical vegetation and soil. As a result,the maize reflectance spectrum corrected by ACORN could characterize vegetation reflectance in the range of 498-750 nm, but gave a fairly large deviation beyond 750 nm,showing the deficiency of spectral calibration beyond 750 nm. The ACORN-derived soil reflectance decreased beyond 800 nm, which was quite inconsistent with field-spectrummeasurement and showed that the calibration accuracy couldn't meet the requirements of ACORN for spectral and radiometric calibration within a certain spectral range. In addition,the stripes on the retrieved water-vapor content map indicated that the radiance-calibration performance of CHRIS is not perfect. As the first spaceborne hyperspectral imager of ESA, the calibration performance of CHRIS needs to be improved. | ZHANG Xia ZHANG Bing HU Fangchao TONG Qingxi | 2006 | Science China(Technological Sciences)2006，49，z2： | 1 |
| 9 | An Operational Method for Fast Detecting Abnormal Channels in Imaging Spectrometers显示文摘Data from abnormal channels in an imaging spectrometer almost always exerts an undesired impact on spectrum matching,classification,pattern recognition and other applications in hyperspectral remote sensing.To solve this problem,researchers should get rid of the data acquired by these channels.Selecting abnormal channels just in the way of visually examining each band image in a imaging data set is a conceivably hard and boring job.To relieve the burden,this paper proposes a method which exploits the spatial and spectral autocorrelations inherent in imaging spectrometer data,and can be used to speed up and,to a great degree,automate the detection of abnormal channels in an imaging spectrometer.This method is applied easily and successfully to one PHI data set and one Hymap data set,and can be applied to remotely sensed data from other hyperspectral sensors. | MA Jiping LI Deren TONG Qingxi ZHENG Lanfen | 2002 | Geo-Spatial Information Science2002，5，4： | 0 |
| 10 | Crop classification based on the spectrotemporal signature derived from vegetation indices and accumulated temperature显示文摘Due to differences in environmental factors,the phenology of the same crop is different every year,causing divergent performances of the classifier built by spectral or time-series features Here,we proposed a random forest classifier(RFC)based on an asymmetric double S curve model fitted by accumulated temperature(AT)and Vegetation Index(VI),which can be applied in different years without ground samples.We built AT and VI time series from Moderate Resolution Imaging Spectroradiometer 8-day composites of land surface temperatures and Sentinel-2 and Landsat-8,respectively.The RFC was trained by characteristics from the asymmetric double S curve.We prepared RFC by ground samples of 2018 and 2019 and then mapped crops of the same region in 2017.Results indicated that,compared with diverse VI-AT series,the overall accuracy based on universal normalized vegetation index(UNVI)was the best of all(2017:F1=0.91,2018:F1=0.92,2019:F1=0.91)and better than that based on the UNVI-TIME series(2017:F1=0.84,2018:F1=0.81,2019:F1=0.88).It proved that the classification features from the VI-AT series have smaller intra-class differences in 2017,2018,and 2019. | Lifu Zhang Liaoran Gao Changping Huang Nan Wang Sa Wang Mingyuan Peng Xia Zhang Qingxi Tong | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
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