光谱学与光谱分析 |
|
|
|
|
|
Precipitable Water Vapor Retrieval with MODIS Near Infrared Data |
ZHANG Tian-long1, WEI Jing1*, GAN Jing-min1, ZHU Qian-qian2, YANG Dong-xu2 |
1. Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China 2. Zhejiang Tourism College, Hangzhou 310000, China |
|
|
Abstract Precipitable water vapor (PWV) shows great significance in remote sensing quantitative application and ecological research. Aiming at solving the problems of traditional methods, an Improved Continuum Interpolated Band Ratio (ICIBR) algorithm was proposed based on the ratios of apparent reflectance of multi-channels in this paper. The ICIBR algorithm considers the absorption characteristics of water vapor absorption in three MODIS near infrared channels (Bands 17, 18 and 19) and the relationship between the PWV and the ICIBRs of above three channels were simulated by using the MORTRAN model. Then the PWV retrieval model for MODIS data was constructed. Texas, Oklahoma region, a typical arid/semi-arid areas, located in North South America were selected as the study area and four different MODIS 1B data were obtained to perform PWV retrieval experiments using the ICIBR algorithm. Last, the corresponding GPS PWV ground observation data provided by SuomiNet and the MODIS PWV product (MOD05) were obtained to verify the experiment results. Evaluation and comparison results showed that the PWV retrievals showed a higher consistency (r=0.967) with the GPS ground measured PWV data with smaller RMSE~0.276 cm and a total of 71.08% of observation points falling within PWV Expected Errors (EE~±0.05+0.15PWVgps). Moreover, the ICIBR algorithm showed an obviously great improvement in PWV estimation, which can effectively reduce 61% overestimation of PWV retrievals than MOD05 PWV products. This new algorithm is more simple and practical with an overall more reliable retrieval accuracy.
|
Received: 2016-01-04
Accepted: 2016-05-12
|
|
Corresponding Authors:
WEI Jing
E-mail: weijing_rs@163.com
|
|
[1] ZHANG Sheng-lan, LIU Hai-lei, DENG Xiao-bo, et al(张升兰, 刘海磊, 邓小波, 等). Remote Sensing Technology and Application(遥感技术与应用), 2014, 29(4): 575. [2] ZHOU Yi, QIN Zhi-hao, BAO Gang(周 义, 覃志豪, 包 刚). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2014, 34(2): 364. [3] Schroedter-Homscheidt M, Drews A, Heise S. Remote Sensing of Environment, 2008, 112(1): 249. [4] GU Xiao-ping, WANG Xin-ming, WU Zhan-ping, et al(谷晓平, 王新明, 吴战平, 等). Plateau Meteorology(高原气象), 2009, 28(2): 446. [5] Frouin R, Deschamps P Y, Lecomte P. Journal of Applied Meteorology, 1990, 29(6): 448. [6] Bevis M, Businger S, Chiswell S, et al. Journal of Applied Meteorology, 1994, 33: 379. [7] CHEN Hong-bin, Lü Da-ren, WEI Chong, et al(陈洪滨, 吕达仁, 魏 重, 等). Scientia Atmosphere Sinica(大气科学), 1996, 6: 757. [8] HU Xiu-qing, ZHANG Yu-xiang, HUANG Yi-fen, et al(胡秀清, 张玉香, 黄意玢, 等). Meteorological Science and Technology(气象科技), 2001, 3: 12. [9] HUANG Yi-fen, DONG Chao-hua(黄意玢, 董超华). Journal of Applied Meteorological Science(应用气象学报), 2002, 13(2): 184. [10] LI Hong-lin, LI Wan-biao(李红林, 李万彪). Acta Scientiarum Naturalium Universitatis Pekinensis(北京大学学报·自然科学版), 2008, 44(1): 121. [11] Kaufman Y J, Gao B C. IEEE Transactions on Geosciences and Remote Sensing, 1992, 30(5): 871. [12] LIU Yu-jie, YANG Zhong-dong (刘玉洁, 杨忠东). The Principle and Algorithm of MODIS Remote Sensing Information Processing(遥感信息处理原理与算法). Beijing: Science Press(北京: 科学出版社), 2001. 66. [13] Ware R H, Fulker D W, Stein S A, et al. Bulletin of the American Meteorological Society, 2000, 81(4): 677. [14] MENG Xian-hong, Lü Shi-hua, ZHANG Tang-tang(孟宪红, 吕世华, 张堂堂). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2007, 26(2): 107. [15] Gao B C, Alexander F H Geotz. Journal of Geophysical Research, 1990, (95): 3549. [16] MAO Ke-biao, QIN Zhi-hao(毛克彪, 覃志豪). Remote Sensing Information(遥感信息), 2004, 4: 47. [17] Vermote E F, Tanre D, Deuze J L, et al. IEEE Transactions on Geoscience and Remote Sensing, 1994, 35(3): 675. [18] Gao B C, Kaufman Y J. Journal of Geophysical Research Atmospheres, 2003, 108(13): 4389. [19] Schlpfer D, Borel C, Keller J,et al. Remote Sensing of Environment, 1998, 65: 353. [20] Sun L, Wei J, Bilal M, et al. Remote Sensing, 2016, 8:23. |
[1] |
LI Chun-qiang1, 2, GAO Yong-gang1, 2, XU Han-qiu1, 2*. Cross Comparison Between Landsat New Land Surface Temperature
Product and the Corresponding MODIS Product[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 940-948. |
[2] |
LONG Ze-hao1, QIN Qi-ming1, 2, 3*, ZHANG Tian-yuan1, XU Wei1. Prediction of Continuous Time Series Leaf Area Index Based on Long Short-Term Memory Network: a Case Study of Winter Wheat[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(03): 898-904. |
[3] |
YANG Dong-xu1,2, WEI Jing3,4*, ZHONG Yong-de1*. Aerosol Optical Depth Retrieval over Beijing Using MODIS Satellite Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(11): 3464-3469. |
[4] |
ZHAO Shuai-yang1, HU Xing-bang1, JING Xin2, JIANG Si-jia1, HE Li-qin1, MA Ai-nai1, YAN Lei1*. Analyses of Land Surface Emissivity Characteristics in Mid-Infrared Bands[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1393-1399. |
[5] |
CHANG Hao-xue1, CAI Xiao-bin2, CHEN Xiao-ling1, 3*, SUN Kun1. Response Characteristics Analysis of Different Vegetation Indices to Leaf Area Index of Rice[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(01): 205-211. |
[6] |
LIU Huan-jun, NING Dong-hao, KANG Ran, JIN Hui-ning, ZHANG Xin-le*, SHENG Lei . A Study on Predicting Model of Organic Matter Contend Incorporating Soil Moisture Variation [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(02): 566-570. |
[7] |
DONG Xue1,2, TIAN Jing1*, ZHANG Ren-hua1,HE Dong-xian3, CHEN Qing-mei1 . Study on the Relationship between Soil Emissivity Spectra and Content of Soil Elements[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(02): 557-565. |
[8] |
GE Wei1, CHEN Liang-fu1, SI Yi-dan1, GE Qiang2, FAN Meng1*, LI Shen-shen1*. Haze Spectral Analysis and Detection Algorithm Using Satellite Remote Sensing Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(12): 3817-3824. |
[9] |
LI Huo-qing1, WU Xin-ping2, Ali Mamtimin3, HUO Wen3, YANG Xing-hua3, YANG Fan3, HE Qing3, LIU Yong-qiang1,4*. Estimating Surface Broadband Emissivity of the Taklimakan Desert with FTIR and MODIS Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(08): 2414-2419. |
[10] |
LI Yao1, 2, ZHANG Li-fu1*, HUANG Chang-ping1, WANG Jin-nian1, CEN Yi1. Monitor of Cyanobacteria Bloom in Lake Taihu from 2001 to 2013 Based on MODIS Temporal Spectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(05): 1406-1411. |
[11] |
Shakir Muhammad1,2, NIU Zheng1*, WANG Li1,2, Abdullah Aablikim3, HAO Peng-yu1,2, WANG Chang-yao1. Crop Classification Based on Time Series MODIS EVI and Ground Observation for Three Adjoining Years in Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(05): 1345-1350. |
[12] |
DU Ling-tong1,2, TIAN Qing-jiu2, WANG Lei1,2 . Impact of Vegetation Structure on Drought Indices Based on MODIS Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(04): 982-986. |
[13] |
YU Chao1, 2, CHEN Liang-fu1*, LI Shen-shen1, TAO Jin-hua1, SU Lin1 . Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(03): 739-745. |
[14] |
LIU Yan1, LI Yang1, YANG Yun2, JIAN Ji3 . Spectrum Similarities-Based Analysis of Spatial Difference of Snow Cover for Multi-Scale Satellite Data—a Case Study of MODIS and HJ-1B Data [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(05): 1306-1311. |
[15] |
WU Meng-quan1, GUO Hao1,2,3, ZHANG An-ding1*, JIA Li-li1, XIAO Lu-xiang1, WANG Jing-pu4 . Research on the Characteristics of Ulva. Prolifera in Shandong Peninsula During 2008—2012 Based on MODIS Data [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(05): 1312-1318. |
|
|
|
|