农业遥感卫星发展现状及我国监测需求分析
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摘要
中国现代农业的发展以及乡村振兴战略的实施需要大量及时有效的农业环境、生产条件、状态及过程信息。基于农业内在的特点,卫星遥感是农业信息快速准确获取的关键技术手段之一。发达国家可用于农业应用的遥感卫星已经形成星座或体系进行联合观测,具有较高的观测时间分辨率,卫星遥感器载荷设计较为充分地考虑了农业应用的需求,观测手段不断创新、观测性能不断提高。目前,我国农业遥感卫星应用还存在很多问题,例如传感器多光谱遥感为主、观测要素缺乏,受遥感传感器性能和遥感卫星地面应用系统能力不足制约,缺少光学与微波等多手段同时相协同观测能力、遥感数据保障率和质量有待提高等,遥感监测手段与国外先进水平存在一定差距。从国内农业生产常规监测、国外农业生产常规监测、重大农业政策执行情况监测和绘制重要农业资源图四个方面全面分析了中国当前遥感卫星业务需求,并考虑未来发展深入分析了农业对遥感卫星应用装备的需求。建议构建编队顺序飞行的,具备多光谱、高光谱、红外以及微波等多种手段的农业卫星星座系统,有效提高多源数据融合精度,综合提供不同波段、不同极化、主动被动、光学微波相互融合的多尺度卫星遥感数据及产品,促进农业遥感技术的快速发展,推动"天空地"数字农业的一体化发展。最后,提出了立足于用户需求,建立中国民用遥感领域农业综合观测卫星系统采用"分步走"战略建议。
With the development of China's modern agriculture, information agriculture and smart agriculture, and the implementation of national rural revitalization strategy, there are very strong demands for timely and effective retrieving information for agricultural environment, production conditions, status, and procedure. Because of the inherent characteristics of agriculture, satellite remote sensing is one of the critical techniques in agricultural information acquisition. Based on the analysis of the applications of agricultural remote sensing satellites abroad and in China, the authors analyzed the technical demand and engineering demand of China's remote sensing satellites development according to the demand of modern agricultural development, in order to provide suggestions for the construction agricultural remote sensing satellite system in the national digital agriculture system. In developed economies, remote sensing satellites that can be used for agricultural applications have formed constellations or systems for integrative observation. Their designs of payloads and sensors onboard remote sensing satellites have taken full account of the demand for agricultural applications. Their technical innovation and information retrieval capability have been greatly enhanced in agricultural applications of satellite remote sensing. In contrast with that in the advanced foreign countries, the agricultural satellite remote sensing applications in China have quite a few problems and shortcomings. We rely mainly multi-spectral remote sensing systems, which leads to inadequate observation elements in agricultural remote sensing applications. Limited by the performance of remote sensing sensors and the inadequate ability of remote sensing satellite ground application system, there is a certain gap between quantitative remote sensing monitoring means in China and foreign developed countries. Based on a comprehensive analysis of the current and future demands of agricultural remote sensing applications in China, this paper suggests the agricultural requirements for the application capability and equipment of remote sensing satellites. It is suggested that a constellation system of agricultural satellites flying in a tandem sequence should be constructed. The constellation has multi-spectral, hyperspectral, infrared and microwave sensors, which can acquire the comprehensive features of the same objects in the same temporal phase, and thus obtain the data with high spatial-temporal consistency and consistency of solar illumination conditions. The precision of multi-source data fusion can comprehensively provide multi-scale remote sensing products with different bands, different polarization, active/passive, microwave/optical fusion. With help of this advanced agricultural remote sensing satellite system and national spatial infrastructure in China, it will enhance the capability to promote the rapid development of agricultural remote sensing technology and the integration of three-dimensional space-air-ground based digital agriculture in China.
With the development of China's modern agriculture, information agriculture and smart agriculture, and the implementation of national rural revitalization strategy, there are very strong demands for timely and effective retrieving information for agricultural environment, production conditions, status, and procedure. Because of the inherent characteristics of agriculture, satellite remote sensing is one of the critical techniques in agricultural information acquisition. Based on the analysis of the applications of agricultural remote sensing satellites abroad and in China, the authors analyzed the technical demand and engineering demand of China's remote sensing satellites development according to the demand of modern agricultural development, in order to provide suggestions for the construction agricultural remote sensing satellite system in the national digital agriculture system. In developed economies, remote sensing satellites that can be used for agricultural applications have formed constellations or systems for integrative observation. Their designs of payloads and sensors onboard remote sensing satellites have taken full account of the demand for agricultural applications. Their technical innovation and information retrieval capability have been greatly enhanced in agricultural applications of satellite remote sensing. In contrast with that in the advanced foreign countries, the agricultural satellite remote sensing applications in China have quite a few problems and shortcomings. We rely mainly multi-spectral remote sensing systems, which leads to inadequate observation elements in agricultural remote sensing applications. Limited by the performance of remote sensing sensors and the inadequate ability of remote sensing satellite ground application system, there is a certain gap between quantitative remote sensing monitoring means in China and foreign developed countries. Based on a comprehensive analysis of the current and future demands of agricultural remote sensing applications in China, this paper suggests the agricultural requirements for the application capability and equipment of remote sensing satellites. It is suggested that a constellation system of agricultural satellites flying in a tandem sequence should be constructed. The constellation has multi-spectral, hyperspectral, infrared and microwave sensors, which can acquire the comprehensive features of the same objects in the same temporal phase, and thus obtain the data with high spatial-temporal consistency and consistency of solar illumination conditions. The precision of multi-source data fusion can comprehensively provide multi-scale remote sensing products with different bands, different polarization, active/passive, microwave/optical fusion. With help of this advanced agricultural remote sensing satellite system and national spatial infrastructure in China, it will enhance the capability to promote the rapid development of agricultural remote sensing technology and the integration of three-dimensional space-air-ground based digital agriculture in China.
引文
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[26]陈兵,李少昆,王克如,等.作物病虫害遥感监测研究进展[J].棉花学报,2007,19(1):57-63.Chen B,Li S,Wang K,et al.Studies of Remote Sensing on Monitoring Crop Diseases and Pests[J].Cotton Science,2007,19(1):57-63.
[27]Guan K,Berry J,Zhang Y,et al.Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence[J].Glob Change Biol,2015,22(2):716-726.
[28]Guan K,Wu J,Kimball J S,et al.The shared and unique values of optical,fluorescence,thermal and microwave satellite data for estimating large-scale crop yields[J].Remote Sensing of Environment,2017,199:333-349.
[29]张立福,王思恒,黄长平.太阳诱导叶绿素荧光的卫星遥感反演方法[J].遥感学报,2018,22(1):1-12.Zhang L,Wang S,Huang C.Top-of-atmosphere hyperspectral remote sensing of solar-induced chlorophyll fluorescence:a review of methods[J].Journal of Remote Sensing,2018,22(1):1-12
[30]Liu L,Guan L,Liu X.Directly estimating diurnal changes in GPP for C3 and C4 crops using far-red sun-induced chlorophyll fluorescence[J].Agricultural and Forest Meteorology,2017,232(Complete):1-9.
[31]孙丽,陈焕伟,赵立军,等.遥感监测旱情的研究进展[J].农业环境科学学报,2004,23(1):202-206.Sun L,Chen H,Zhao L,et al.The Advance of Drought Monitoring by Remote Sensing[J].Journal of AgroEnvironment Science,2004,23(1):202-206.
[32]王鹏新,龚健雅,李小文,等.基于植被指数和土地表面温度的干旱监测模型[J].地球科学进展,2003 18(4):527-533.Wang P,Gong J,Li X,et al.Advances in drought monitoring by using remotely sensed normalized difference vegetation index and land surface temperature products[J].Advance in Earth Sciences,2003,18(4):527-533.
[33]王利民,刘佳,邓辉,等.我国农业干旱遥感监测的现状与展望[J].中国农业资源与区划,2008,29(06):4-8.Wang L,Liu J,Deng H,et al.Present status and prospect of remote sensing supervision and test for arid agriculture in China[J].Chinese Journal of Agricultural Resources and Regional Planning.2008,29(06):4-8.
[34]Adams J R,Berg A A,Mcnairn H,et al.Sensitivity of C-band SAR polarimetric variables to unvegetated agricultural fields[J].Canadian Journal of Remote Sensing,2013,39(1):1-16.
[35]何连,秦其明,任华忠,等.利用多时相Sentinel-1 SAR数据反演农田地表土壤水分[J].农业工程学报,2016,32(3):142-148.He L,Qin Q,Ren H,et al.Soil moisture retrieval using multi-temporal Sentinel-1 SAR data in agricultural areas[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(3):142-148.
[36]Lambert A,Santee M L.Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS,COSMICGPS RO,and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds[J].Atmospheric Chemistry and Physics,2018,18(3):1945-1975.
[2]Colwell J,Rice D,Nalepka R.Wheat yield forecasts using Landsat data[C].proc.of the 11th Intern.Symp.on Remote Sensing of Environment,1977:1245-1254.
[3]陈仲新,任建强,唐华俊,等.我国农业遥感研究应用进展与展望[J].遥感学报,2016,20(5):748-765.Chen Z,Ren J,Tang H.et al.Progress and perspectives on agricultural remote sensing research and applications in China[J].Journal of Remote Sensing,2016,20(5):748-767
[4]Whitcraft A,Becker-Reshef I.Justice C.A Framework for Defining Spatially Explicit Earth Observation Requirements for a Global Agricultural Monitoring Initiative(GEOGLAM)[J].Remote Sens.2015,(7):1461-1481.
[5]黄季焜.四十年中国农业发展改革和未来政策选择[J].农业技术经济,2018,37(3):4-15.Huang J.Forty years of China's agricultural development reformand future policychoices[J].Agriculturaltechnology economy,2018,37(3):4-15.
[6]国家民用空间基础设施中长期发展规划(2015-2025年)[J].卫星应用,2015,6(11):64-70.Medium and long-term development plan for national civil space infrastructure(2015-2025)[J].Satellite Application,2015,6(11):64-70.
[7]SENTINEL Overview[EB/OL].esa[2019-01-09].https://sentinel.esa.int/web/sentinel/missions.
[8]TerraSAR-X/TanDEM-X[EB/OL].esa[2019-01-09].https://earth.esa.int/web/guest/missions/3rd-party-missions/current-missions/terrasar-x.
[9]RapidEye[EB/OL].esa[2019-01-09].https://earth.esa.int/web/guest/missions/3rd-party-missions/current-missions/rapideye.
[10]WorldView-3 Satellite Sensor[EB/OL].Satellite imaging corporation[2019-01-09].https://www.satimagingcorp.com/satellite-sensors/worldview-3/.
[11]Planet[EB/OL].2019 Planet Labs Inc.[2019-01-09].https://www.planet.com/.
[12]About ALOS-Overview and objectives[EB/OL].ALOSResearch and Application Project of EORC,JAXA[2019-01-09].https://www.eorc.jaxa.jp/ALOS/en/about/about_index.htm.
[13]Fox P,Tyc G,Beckett K.The UrtheCast SAR-XL multiband,multi-aperture spaceborne SAR system[C].Radar Conference,2017:1761-1764.
[14]Hao P,Tang H,Chen Z,Liu Z.Early-season crop mapping using improved artificial immune network(IAIN)and Sentinel data[J].Peer J 6:e5431.
[15]Gao F,Anderson M,Daughtry C,et al.Assessing the variability of corn and soybean yields in central iowa using high spatiotemporal resolution multi-satellite imagery[J].Remote Sens.2018,10,1489.
[16]高分一号[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/3076.shtml.
[17]高分二号[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/3128.shtml.
[18]环境一号A/B/C星[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/3064.shtml.
[19]资源一号01/02星[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/3056.shtml.
[20]蔡亚宁,肖鹏飞,何德华,等.数字化技术在高分三号卫星总装设计中的应用[J].航天器工程,2017,26(06):137-142.Cai Y,Xiao P,He D,et al.Application of digital technologies to assembly design for GF-3 Satellite[J].Spacecraft Engineering,2017,26(06):137-142.
[21]资源一号04星[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/4308.shtml.
[22]Chen Z,Zhou Q,Liu J,et.al.Charms-China agricultural remote sensing monitoring system[C].IEEE International Geoscience and Remote Sensing Symposium,2011.3530-3533.
[23]资源一号02C星[EB/OL].中国资源卫星应用中心[2019-01-09].http://www.cresda.com/CN/Satellite/3067.shtml.
[24]王迪,周清波,陈仲新,等.基于合成孔径雷达的农作物识别研究进展[J].农业工程学报,2014,30(16):203-212.Wang D.Zhou Q,Chen Z,et al.Research advances on crop identification using synthetic aperture radar[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(16):203-212.
[25]丁娅萍,陈仲新.基于最小距离法的RADARSAT-2遥感数据旱地作物识别[J].中国农业资源与区划,2014,35(6):79-84.Ding Y.Chen Z.Dry land crop classification using minimum distance method based on Radarsat-2 Data[J].Chinese Journal of Agricultural Resources and Regional Planning,2014,35(6):79-84.
[26]陈兵,李少昆,王克如,等.作物病虫害遥感监测研究进展[J].棉花学报,2007,19(1):57-63.Chen B,Li S,Wang K,et al.Studies of Remote Sensing on Monitoring Crop Diseases and Pests[J].Cotton Science,2007,19(1):57-63.
[27]Guan K,Berry J,Zhang Y,et al.Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence[J].Glob Change Biol,2015,22(2):716-726.
[28]Guan K,Wu J,Kimball J S,et al.The shared and unique values of optical,fluorescence,thermal and microwave satellite data for estimating large-scale crop yields[J].Remote Sensing of Environment,2017,199:333-349.
[29]张立福,王思恒,黄长平.太阳诱导叶绿素荧光的卫星遥感反演方法[J].遥感学报,2018,22(1):1-12.Zhang L,Wang S,Huang C.Top-of-atmosphere hyperspectral remote sensing of solar-induced chlorophyll fluorescence:a review of methods[J].Journal of Remote Sensing,2018,22(1):1-12
[30]Liu L,Guan L,Liu X.Directly estimating diurnal changes in GPP for C3 and C4 crops using far-red sun-induced chlorophyll fluorescence[J].Agricultural and Forest Meteorology,2017,232(Complete):1-9.
[31]孙丽,陈焕伟,赵立军,等.遥感监测旱情的研究进展[J].农业环境科学学报,2004,23(1):202-206.Sun L,Chen H,Zhao L,et al.The Advance of Drought Monitoring by Remote Sensing[J].Journal of AgroEnvironment Science,2004,23(1):202-206.
[32]王鹏新,龚健雅,李小文,等.基于植被指数和土地表面温度的干旱监测模型[J].地球科学进展,2003 18(4):527-533.Wang P,Gong J,Li X,et al.Advances in drought monitoring by using remotely sensed normalized difference vegetation index and land surface temperature products[J].Advance in Earth Sciences,2003,18(4):527-533.
[33]王利民,刘佳,邓辉,等.我国农业干旱遥感监测的现状与展望[J].中国农业资源与区划,2008,29(06):4-8.Wang L,Liu J,Deng H,et al.Present status and prospect of remote sensing supervision and test for arid agriculture in China[J].Chinese Journal of Agricultural Resources and Regional Planning.2008,29(06):4-8.
[34]Adams J R,Berg A A,Mcnairn H,et al.Sensitivity of C-band SAR polarimetric variables to unvegetated agricultural fields[J].Canadian Journal of Remote Sensing,2013,39(1):1-16.
[35]何连,秦其明,任华忠,等.利用多时相Sentinel-1 SAR数据反演农田地表土壤水分[J].农业工程学报,2016,32(3):142-148.He L,Qin Q,Ren H,et al.Soil moisture retrieval using multi-temporal Sentinel-1 SAR data in agricultural areas[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(3):142-148.
[36]Lambert A,Santee M L.Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS,COSMICGPS RO,and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds[J].Atmospheric Chemistry and Physics,2018,18(3):1945-1975.