An algorithm for estimation of surface albedo in 16 m resolution from Chinese GF-1WFV image
- Vol. 27, Issue 11, Pages: 2541-2551(2023)
Published： 07 November 2023
DOI： 10.11834/jrs.20211131
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摘要
地表反照率在陆面气候和生物圈模型中起着至关重要的作用。为了更好地满足多领域研究的要求，拓宽定量遥感参数的应用，许多研究学者及团队正在利用不同的算法开发高分辨率地表反照率产品。本文提出的算法基于中国高分一号卫星WFV传感器数据和500 m分辨率的GLASS反照率产品生成高空间分辨率的反照率产品。算法思路首先用直接反演算法反演GF-1 WFV数据得到16 m分辨率初级反照率产品，再将500 m分辨率的GLASS反照率产品与16 m分辨率初级产品的纹理信息进行降尺度融合，最终得到16 m分辨率的融合反照率产品。以2016年—2017年黑河实验区的8个站点的地面观测值对算法结果进行验证，实测数据与反演融合数据的时间序列图表明融合后的16 m分辨率反照率与实测值一致性较好；同时，通过2016年—2017年所有站点散点图分析，融合反照率均方根误差为0.02439，初级反照率则为0.05135，融合反照率比初级反照率更接近实测值。16 m分辨率反照率产品在平均值与500 m分辨率的GLASS反照率产品一致的前提下丰富了空间纹理信息，能够更好地支持在区域尺度研究人类活动对环境的影响。
Abstract
Surface albedo plays a vital role in land surface climate and biosphere models. Many researchers and teams use different algorithms to develop high- resolution surface albedo products for better satisfying the requirements of multi-field research and broaden the application of quantitative remote sensing parameters.The proposed algorithm aims to generate albedo products of high spatial resolution based on the sensor data of GF-1 WFV and the GLASS albedo product with 500 m resolution. The idea of the algorithm is to first invert the GF-1 WFV data with a direct inversion algorithm for obtaining the primary albedo product of 16 m resolution. Then
it downscales the GLASS albedo product of 500 m resolution with the texture information of the primary product of 16 m resolution to obtain the final albedo product of 16 m resolution.The algorithm results are verified with ground observations at eight stations in the Heihe Experimental Area using the data from 2016 to 2017. The time series graphs of the measured data and the inverted fusion data show that the fused albedo product of 16 m resolution agrees well with the measured value. At the same time
through the analysis of the scatter plots of all stations from 2016 to 2017
the root mean square error of the fusion albedo is 0.02439
and the primary albedo is 0.05135. The fusion albedo is closer to the measured value than the primary albedo. The GLASS albedo product of 500 m resolution in the photovoltaic industrial park was compared with the co-located albedo product of 16 m resolution to visually illustrate the effect of the albedo product of 16 m resolution. The albedo product of 16 m resolution could better support the studies on human activities and the environment. The algorithm quantitatively fuses the texture information of 16 m resolution in the GF-1 data with the mean value information of the GLASS albedo product of 500 m resolution to obtain the albedo product of 16 m resolution. It contains two main steps: a simple direct inversion algorithm and a downscale-to-fuse algorithm. The albedo product of 16 m resolution enriches the spatial texture information on the premise that the average value is consistent with that of the GLASS albedo product of 500 m resolution.
关键词
遥感反照率算法降尺度融合高分辨率验证高分一号卫星（GF-1）黑河
Keywords
remote sensingalbedoalgorithmdownscaling fusionhigh resolutionverificationGF-1Hei He
references
Dickinson R E. 1983. Land surface processes and climate-surface albedos and energy balance. Advances in Geophysics, 25: 305-353 [DOI: 10.1016/S0065-2687(08)60176-4http://dx.doi.org/10.1016/S0065-2687(08)60176-4]
Dirmeyer P A and Shukla J. 1994. Albedo as a modulator of climate response to tropical deforestation. Journal of Geophysical Research: Atmospheres, 99(D10): 20863-20877 [DOI: 10.1029/94JD01311http://dx.doi.org/10.1029/94JD01311]
Gao B, Jia L and Menenti M. 2014. An improved method for retrieving land surface albedo over rugged terrain. IEEE Geoscience and Remote Sensing Letters, 11(2): 554-558 [DOI: 10.1109/LGRS.2013.2275072http://dx.doi.org/10.1109/LGRS.2013.2275072]
He T, Liang S L, Wang D D, Cao Y F, Gao F, Yu Y Y and Feng M. 2018. Evaluating land surface albedo estimation from Landsat MSS, TM, ETM+, and OLI data based on the unified direct estimation approach. Remote Sensing of Environment, 204: 181-196 [DOI: 10.1016/j.rse.2017.10.031http://dx.doi.org/10.1016/j.rse.2017.10.031]
He T, Liang S L, Wang D D, Chen X N, Song D X and Jiang B. 2015. Land surface albedo estimation from Chinese HJ satellite data based on the direct estimation approach. Remote Sensing, 7(5): 5495-5510 [DOI: 10.3390/rs70505495http://dx.doi.org/10.3390/rs70505495]
He T, Liang S L, Wang D D, Shuai Y M and Yu Y Y. 2014. Fusion of satellite land surface albedo products across scales using a multiresolution tree method in the North Central United States. IEEE Transactions on Geoscience and Remote Sensing, 52(6): 3428-3439 [DOI: 10.1109/TGRS.2013.2272935http://dx.doi.org/10.1109/TGRS.2013.2272935]
Kotchenova S Y and Eric F V. 2007. Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces. Applied Optics, 46(20): 4455-4464 [DOI: 10.1364/AO.46.004455http://dx.doi.org/10.1364/AO.46.004455]
Lewis P, Brockmann C, Danne O, Fischer J, Guanter L, Heckel A, Krueger O, López G, Muller J, North P and Preusker R. 2011. GlobAlbedo Algorithm Theoretical Basis Document: Version 3.0. [s.n.]
Li C J, Liu L Y, Wang J H and Wang R C. 2004. Comparison of two methods of fusing remote sensing images with fidelity of spectral information. Journal of Image and Graphics, 9(11): 1376-1385
李存军, 刘良云, 王纪华, 王人潮. 2004. 两种高保真遥感影像融合方法比较. 中国图象图形学报, 9(11): 1376-1385 [DOI: 10.3969/j.issn.1006-8961.2004.11.018http://dx.doi.org/10.3969/j.issn.1006-8961.2004.11.018]
Li X, Li X W, Li Z Y, Wang J, Ma M G, Liu Q, Xiao Q, Hu Z Y, Che T, Wang J M, Liu Q H, Chen E X, Yan G J, Liu S M, Wang W Z, Zhang L X, Wang J D, Niu Z, Jin R, Ran Y H and Wang L X. 2012a. Progresses on the watershed allied telemetry experimental research (WATER). Remote Sensing Technology and Application, 27(5): 637-649
李新, 李小文, 李增元, 王建, 马明国, 刘强, 肖青, 胡泽勇, 车涛, 王介民, 柳钦火, 陈尔学, 阎广建, 刘绍民, 王维真, 张立新, 王锦地, 牛铮, 晋锐, 冉有华, 王亮绪. 2012a. 黑河综合遥感联合试验研究进展: 概述. 遥感技术与应用, 27(5): 637-649
Li X, Liu Q, Liu Q H, Wang J, Ma M G, Xiao Q, Che T, Jin R and Ran Y H. 2012b. The progresses on the watershed allied telemetry experimental research (WATER): remote sensing of key hydrological and ecological parameters. Remote Sensing Technology and Application, 27(5): 650-662
李新, 刘强, 柳钦火, 王建, 马明国, 肖青, 车涛, 晋锐, 冉有华. 2012b. 黑河综合遥感联合试验研究进展: 水文与生态参量遥感反演与估算. 遥感技术与应用, 27(5): 650-662
Li X，Liu S M，Liu Q H，Xiao Q，Che T，Ma M G，Jin R，Ran Y H，Wen J G，Xu Z W and Li Z Y. 2023. Heihe remote sensing experiments： Retrospect and prospect. National Remote Sensing Bulletin， 27（2）：224-248
李新，刘绍民，柳钦火，肖青，车涛，马明国，晋锐，冉有华，闻建光，徐自为，李增元.2023.黑河遥感试验：回顾与展望.遥感学报，27（2）： 224-248 [DOI： 10.11834/jrs.20235013http://dx.doi.org/10.11834/jrs.20235013]
Liang S L. 2003. A direct algorithm for estimating land surface broadband albedos from MODIS imagery. IEEE Transactions on Geoscience and Remote Sensing, 41(1): 136-145
Liang S L, Li X W and Wang J D. 2013. Quantitative Remote Sensing: Ideas and Algorithms. Beijing: Science Press
梁顺林, 李小文, 王锦地. 2013. 定量遥感: 理念与算法. 北京: 科学出版社
Liang S L, Strahler A H and Walthall C. 1999. Retrieval of land surface albedo from satellite observations: a simulation study. Journal of Applied Meteorology, 38(6): 712-725 [DOI: 10.1175/1520-0450(1999)038<0712:ROLSAF>2.0.CO;2http://dx.doi.org/10.1175/1520-0450(1999)038<0712:ROLSAF>2.0.CO;2]
Liang S L, Stroeve J and Box J E. 2005. Mapping daily snow/ice shortwave broadband albedo from Moderate Resolution Imaging Spectroradiometer (MODIS): the improved direct retrieval algorithm and validation with Greenland in situ measurement. Journal of Geophysical Research: Atmospheres, 110(D10): D10109 [DOI: 10.1029/2004JD005493http://dx.doi.org/10.1029/2004JD005493]
Liang S L, Wang K C, Zhang X T and Wild M. 2010. Review on estimation of land surface radiation and energy budgets from ground measurement, remote sensing and model simulations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3): 225-240 [DOI: 10.1109/JSTARS.2010.2048556http://dx.doi.org/10.1109/JSTARS.2010.2048556]
Liang S L, Zhao X, Liu S H, Yuan W P, Cheng X, Xiao Z Q, Zhang X T, Liu Q, Cheng J, Tang H R, Qu Y H, Bo Y C, Qu Y, Ren H Z, Yu K and Townshend J. 2013. A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth, 6(S1): 5-33 [DOI: 10.1080/17538947.2013.805262http://dx.doi.org/10.1080/17538947.2013.805262]
Liu J, Wang L M, Yang L B, Teng F, Shao J, Yang F G and Fu C H. 2015. GF-1 satellite image atmospheric correction based on 6S model and its effect. Transactions of the Chinese Society of Agricultural Engineering, 31(19): 159-168
刘佳, 王利民, 杨玲波, 滕飞, 邵杰, 杨福刚, 富长虹. 2015. 基于6S模型的GF-1卫星影像大气校正及效果. 农业工程学报, 31(19): 159-68 [DOI: 10.11975/j.issn.1002-6819.2015.19.022http://dx.doi.org/10.11975/j.issn.1002-6819.2015.19.022]
Liu Q, Wang L Z, Qu Y, Liu N F, Liu S H, Tang H R and Liang S L. 2013. Preliminary evaluation of the long-term GLASS albedo product. International Journal of Digital Earth, 6(S1): 69-95 [DOI: 10.1080/17538947.2013.804601http://dx.doi.org/10.1080/17538947.2013.804601]
Peng J J, Liu Q, Wen J G, Liu Q H, Tang Y, Wang L Z, Dou B C, You D Q, Sun C K, Zhao X J, Feng Y B and Shi J, Multi-scale validation strategy for satellite albedo products and its uncertainty analysis. Science China: Earth Sciences, 45(1): 66-82
彭菁菁, 刘强, 闻建光, 柳钦火, 唐勇, 王立钊, 窦宝成, 游冬琴, 孙长奎, 赵小杰, 冯佑斌, 施健. 2015. 卫星反照率产品的多尺度验证与不确定性分析. 中国科学: 地球科学, 45(1): 66-82 [DOI: 10.1007/s11430-014-4997-yhttp://dx.doi.org/10.1007/s11430-014-4997-y]
Qu Y, Liu Q, Liang S L, Wang L Z, Liu N F and Liu S H. 2014. Direct-estimation algorithm for mapping daily land-surface broadband albedo from MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 52(2): 907-919 [DOI: 10.1109/TGRS.2013.2245670http://dx.doi.org/10.1109/TGRS.2013.2245670]
Sellers P J, Tucker C J, Collatz G J, Los S O, Justice C O, Dazlich D A and Randall D A. 1994. A global 1° by 1° NDVI data set for climate studies. Part 2: the generation of global fields of terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing, 15(17): 3519-3545 [DOI: 10.1080/01431169408954343http://dx.doi.org/10.1080/01431169408954343]
Shang R, Liu R G and Liu Y. 2015. Generation of global long-term albedo product based on the background knowledge. Journal of Geo-Information Science, 17(11): 1313-1322
商荣, 刘荣高, 刘洋. 2015. 基于背景知识的全球长时间序列反照率反演. 地球信息科学学报, 17(11): 1313-1322 [DOI: 10.3724/SP.J.1047.2015.01313http://dx.doi.org/10.3724/SP.J.1047.2015.01313]
Shuai Y M, Masek J G, Gao F, Schaaf C B and He T. 2014. An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge. Remote Sensing of Environment, 152: 467-479 [DOI: 10.1016/j.rse.2014.07.009http://dx.doi.org/10.1016/j.rse.2014.07.009]
Siegel R and Howell J R. 1992. Thermal Radiation Heat Transfer. 3rd ed. Bristol: Hemisphere Publishing
Sundar K J A, Jahnavi M, Lakshmisaritha K. 2017. Multi-sensor image fusion based on empirical wavelet transform//Proceedings of 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques. Mysuru: IEEE: 93-97 [DOI: 10.1109/ICEECCOT.2017.8284646http://dx.doi.org/10.1109/ICEECCOT.2017.8284646]
Wang D D, Liang S L, He T and Yu Y Y. 2013. Direct estimation of land surface albedo from VIIRS data: algorithm improvement and preliminary validation. Journal of Geophysical Research: Atmospheres, 118(22): 12577-12586 [DOI: 10.1002/2013JD020417http://dx.doi.org/10.1002/2013JD020417]
Wang L Z, Zheng X C, Sun L, Liu Q and Liu S H. 2014. Validation of GLASS albedo product through Landsat TM data and ground measurements. Journal of Remote Sensing, 18(3): 547-558
王立钊, 郑学昌, 孙林, 刘强, 刘素红. 2014. 利用Landsat TM数据和地面观测数据验证GLASS反照率产品. 遥感学报, 18(3): 547-558 [DOI: 10.11834/jrs.20143130http://dx.doi.org/10.11834/jrs.20143130]
You D Q, Wen J G, Xiao Q, Liu Q, Liu Q H, Tang Y, Dou B C and Peng J J. 2015. Development of a high resolution BRDF/albedo product by fusing airborne CASI reflectance with MODIS daily reflectance in the Oasis Area of the Heihe River Basin, China. Remote Sensing, 7(6): 6784-6807 [DOI: 10.3390/rs70606784http://dx.doi.org/10.3390/rs70606784]
Zhang H, Jiao Z T, Dong Y D, Li J Y and Li X W. 2015. Albedo retrieved from BRDF archetype and surface directional reflectance. Journal of Remote Sensing, 19(3): 355-367
张虎, 焦子锑, 董亚冬, 李佳悦, 李小文. 2015. 利用BRDF原型和单方向反射率数据估算地表反照率. 遥感学报, 19(3): 355-367 [DOI: 10.11834/jrs.20154131http://dx.doi.org/10.11834/jrs.20154131]
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