国外农情遥感监测系统现状与启示

doi:10.11867/j.issn.1001-8166.2010.10.1003

大范围的可靠农情信息对粮食市场及相关政策的制定至关重要，是保障区域及全球粮食安全的重要依据，在全球气候变化、人口增长、土地利用/覆盖变化剧烈的背景下，对这一信息的需求也更加迫切。传统农情信息的获取依赖于庞大的调查队伍和大量的调查工作，信息的获取存在成本高、时效性差和结果受主观影响大的缺点。伴随着近30年遥感技术本身及其在农情信息获取领域能力的提升，一些国家与国际组织建设了各自的农情遥感监测系统，并开展了运行化的监测。对美国、欧盟、FAO、加拿大、巴西、阿根廷、俄罗斯、印度等主要的农情遥感监测系统进展进行了详细的介绍，并通过对这些系统的分析得到一些农情监测系统建设的启示。指出作物种植面积估算、单产预测、长势监测、旱情监测是农情遥感监测中最主要的4个主题。在面积估算方面，各个系统在遥感技术不断发展的同时对地[JP2]面调查的依赖并没有减少，甚至得到了强化，这与遥感降低地面调查的初衷相违背，导致遥感技术在大范围农情监测中的潜力没有得到充分发挥，在单产预测方面，需要发展独立的遥感预测方法。提升遥感的作用是未来一段时间内农情遥感监测系统建设的主要方向。

关键词: 农情, 遥感, 系统

Dependable information on large-area agricultural production and production estimation are essential for agricultural markets and the formulation of national and international agricultural policies. It can provide information and technical support for regional or global food security. Factors like worldwide climate change, increasing population and fast changes in land use/cover make the need more urgent. Traditional collection of crop information depends on huge in-situ investigation, which is expensive, time consuming and vulnerable to subjective difference. Along with the development in remote sensing technology and its application to crop information acquirement, some operational crop monitoring systems were developed and put into operation by several countries and international organizations. The development of major crop monitoring systems worldwide (United States, Europe, FAO, Canada, Brazil, Argentina, Russia and India) was reviewed and introduced in detail. The paper points out that the crop acreage estimation, crop yield prediction, crop condition monitoring and drought monitoring are the four primary themes in remote sensing based crop monitoring. In crop acreage monitoring, along with the development of remote sensing technology, the dependence of these systems on field survey has not been reduced, or even increased for some reasons. This is against the primary intention of remote sensing application: to reduce or substitute field survey. The potential of remote sensing in large-area crop monitoring has not been fully exerted. Independent crop yield predicting method with remote sensing is also in great need. How to increase the role of remote sensing will be the major direction for the development of remote sensing based crop monitoring systems.

Key words: Crop information, Remote sensing, System

中图分类号:

P237
TP79

[1] FAO. 1.02 billion starving people worldwide, U.N. says[EB/OL]. http://www.news-medical.net/news/20090623/102-billion-starving-people-worldwide-UN-says.aspx,2009.
[2] 郑国光. 科学应对全球变暖提高粮食安全保障能力[EB/OL].http://www.gov.cn/gzdt/ 2009-12/01/content_1477574.htm,2009.
[3] Khabir Ahmad. Global population will increase to nine billion by 2050. UN report[J].The Lancet, 2001, 357(9 259): 864.
[4] GEO. Developing a Strategy for Global Agriculturel Monitoring in the Frame Work of Group on Earth Observations (GEO) Workshop Report [R]. 2007.
[5] Meng Jihua, Wu Bingfang, Li Qiangzi, et al. Research advances and outlook of crop monitoring with remote sensing at field level[J].Remote Sensing Information, 2010, (3):134-140.[蒙继华，吴炳方，李强子,等. 农田农情参数遥感监测进展及应用展望[J].遥感信息, 2010, (3):134-140.]
[6] Li Deren. Towards photogrammetry and remote sensing:Status and future development[J].Journal of Wuhan Technical University of Surveying and Mapping,2000,25(1): 1-5.[李德仁. 摄影测量与遥感的现状及发展趋势[J].武汉测绘科技大学学报,2000,25(1): 1-5.]
[7] Macdonald R B. The LACIE symposium[C]// Lyndon B, ed. Johnson Space Center, National Aeronautics and Space Administration. Houston: NASA,1979.
[8] Hallum C R. Experiment design overview[C]// Proceedings of the Large Area Crop Inventory Experiment (LACIE)Symposium. Houston, Texas: NASA/JSC,1978.
[9] U.S. Department of Agriculture. AgRISTARS Preliminary Technical Program Plan[R]. 1979.
[10] Yates H W, Tarpley J D, Schneider S R, et al. The role of meteorological satellites in agricultural remote sensing[J].Remote Sensing of Environment,1984, 14:219-233.
[11] Kleweno D D, Miller C E. 1980 AgRISTARS DC/LC Project Summary: Crop Area Estimates for Kansas and Iowa[R]. ESS staff report-U.S. Dept. of Agriculture, Economics and Statistics Service.1981. (AGESS810414), 18.
[12] Genovese G. Methodology of the MARS Crop Yield Forecasting System[R]. 2004,114,EUR-report 21291 EN.
[13] Baruth B, Royer A, Genovese G, et al. The use of remote sensing within the MARS crop yield monitoring system of the European commission[C]//ISPRS Archives ‘Remote Sensing Applications for a Sustainable Future’，2006,Vol. XXXVI, Part 8.
[14] USDA FAS. GLAM-Global Agricultural Monitoring [EB/OL]. http://www.pecad.fas.usda.gov/glam.cfm,2005.
[15] Wu Bingfang. China crop watch system with remote sensing[J].Journal of Remote sensing,2004,8(6):482-496.[吴炳方.中国农情遥感速报系统[J].遥感学报,2004,8(6):482-496.]
[16] USDA FAS. Production, Supply and distribution online[EB/OL]. http://www.fas.usda.gov/psdonline/, 2007.
[17] USDA FAS, The FAS crop explorer: A web success story[EB/OL]. http://www.fas.usda.gov/info/fasworldwide/2005/06-2005, 2005.
[18] USDA NASS. History of remote sensing for crop acreage[EB/OL]. http://www.nass.usda.gov/surveys/remotely_sensed_data_crop_acreage/index.asp,2009.
[19] USDA NASS. Cropland data layer[EB/OL]. http://www.nass.usda.gov/research/cropland/SARS1a.htm,2010.
[20] FAO. Famine early warning system network[EB/OL]. http://www.fews.net/pages/default.aspx, 2010.
[21] USDA NASS. Limited use for crop condition and crop yield[EB/OL]. http://www.nass.usda.gov/surveys/remotely_sensed_data_crop_yield/index.asp,2009.
[22] USGS. EROS early warning and environmental monitoring program[EB/OL]. http://earlywarning.usgs.gov/?l=en, 2010.
[23] EC JRC. The monitoring agricultural resources[EB/OL]. http://mars.jrc.ec.europa.eu, 2010.
[24] EC JRC. MARS unit-about us[EB/OL]. http://mars.jrc.it/mars/About-us, 2010.
[25] EC. GMES info [EB/OL]. http://www.gmes.info/, 2010.
[26] EC JRC. MARSOP introduction[EB/OL]. http://www.marsop.info, 2010.
[27] ESA. GMES Services Element (GSE) [EB/OL]. http://www.esa.int/esaLP/SEM2UV2IU7E_LPgmes_0.html, 2006.
[28] EC JRC. The Crop Growth Monitoring System (CGMS) [EB/OL]. http://mars.jrc.it/mars/About-us/AGRI4CAST/Crop-yield-forecast/The-Crop-Growth-Monitoring-System-CGMS,2010.
[29] Bochenek Z. Operational use of NOAA data for crop condition assessment in Poland[C]//EARSeL Symposium on Remote Sensing in the 21st Century: Economic and Environmental Applications. Valladolid, 1999 (in Anglais).
[30] Dabrowska-Zielinska K, Kogan F, Ciolkosz A, et al. Modeling of crop growth conditions and crop yield in Poland using AVHRR-based indices[J].International Journal of Remote Sensing,2002, 23(6):1 109-1 123.
[31] Aleksandra Bujakiewicz, Jozef Jachimski, Romuald Kaczynski. The Polish National Report for Photogrammetry and Remote Sensing 2000-2004[R]. XX ISPRS Congress in Istanbul, 2004.
[32] Zsuzsanna Suba , Gábor Csornai, Csaba Wirnhardt, et al. The Remote Sensing Based Hungarian Crop Production Forecast Program (Cropmon) and Its Other Applications[M]. Springer Berlin Heidelberg, Cartography in Central and Eastern Europe, 2010.
[33] Csornai G. CROPMON: Hungarian crop production forecast by remote sensing[C]//ISPRS Archives XXXVI-8/W48 Workshop proceedings. Remote Sensing Support to Crop Yield Forecast and Area Estimates. Commission VIII, WG VIII/10, Stresa, Italy,2006,36(8/W48).
[34] Martino L. The Agrit System for Short-term Estimates in Agriculture: A Project for 2004[R]. Polish Seminar: Information Systems in Agriculture. Krakow,2003.
[35] Giovacchini A,Brunetti A. Agricultural statistics by remote sensing in Italy: An ultimate cost analysis[C]//Conference on the Application of Remote Sensing to Agricultural Statistics. Belgirate. Office for Publications of the E.C. Luxembourg,1992.
[36] FAO, Global information and early warning system[EB/OL]. http://www.fao.org/WAICENT/faoinfo/economic/giews/english/index.htm, 2010.
[37] Hielkema J U, Snijders F L. Operational use of environmental satellite remote sensing and satellite communications technology for global food security and locust control by FAO: The ARTEMIS and DIANA systems[J].Acta Astronautica,1994, 32(9):603-616.
[38] FAO, WinDisp3.5 user′s manual [EB/OL]. http://www.fao.org/giews/english/windisp/manuals/WD35EN41.htm,1999.
[39] FAO, WinDisp-Map and Image Display and Analysis Software [EB/OL]. http://www.fao.org/giews/english/windisp/dl.htm,2003.[40] Food insecurity and vulnerability information and mapping systems. FIVIMS-better information for targeted action in hunger reduction[EB/OL]. http://www.fivims.org/, 2009.
[41] Statistics Canda. Overview of the crop condition assessment program[EB/OL]. http://www26.statcan.ca/ccap/overview-apercu-eng.jsp,2010.
[42] CONAB, GEOSAFRAS[EB/OL]. http://www.conab.gov.br/conabweb/index.php?PAG=81,2010.
[43] MinAgri-Argentina[EB/OL]. http://www.minagri.gob.ar/,2010.
[44] CONAE, Argentina on space[EB/OL]. http://www.en.argentina.ar/_en/science-and-education/C1477-argentina-on-space. php,2009.
[45] http://www.agrocosmos.gvc.ru/,2010.
[46] National Crop Forecasting Centre (NCFC)[EB/OL]. http://dacnet.nic.in/eands/ncfc/ncfc.htm,2010.
[47] Crop acreage and production estimation[EB/OL]. http://dacnet.nic.in/eands/cape.htm,2010.
[48] Patil V C, Ajit Maru, Shashidhara G B, et al. Remote sensing, geographical information system and precision farming in India: Opportunities and challenges[C]//Asian Agricultural Information Technology & Management. Proceedings of the Third Asian Conference for Information Technology in Agriculture (CAAS, AFITA), Beijing,2002.
[49] Indian space research organisation, forecasting of agriculture outputs through satellite, agrometeorology and land based observations (FASAL) [EB/OL].http://www.isro.org/scripts/rsa_fasal.aspx, 2010.

[1]	原世伟, 李新, 杜二虎. 多主体建模在水资源管理中的应用：进展与展望[J]. 地球科学进展, 2021, 36(9): 899-910.
[2]	田凤云,吴成来,张贺,林朝晖. 基于 CAS-ESM2的青藏高原蒸散发的模拟与预估[J]. 地球科学进展, 2021, 36(8): 797-809.
[3]	王奕佳,刘焱序,宋爽,傅伯杰. 水—粮食—能源—生态系统关联研究进展[J]. 地球科学进展, 2021, 36(7): 684-693.
[4]	王忠静,石羽佳,张腾. TRMM遥感降水低估还是高估中国大陆地区的降水？[J]. 地球科学进展, 2021, 36(6): 604-615.
[5]	范小杉. 国际社会对生态系统服务研究误区的研讨综述[J]. 地球科学进展, 2021, 36(6): 616-624.
[6]	陈仁升, 沈永平, 毛炜峄, 张世强, 吕海深, 刘永强, 刘章文, 房世峰, 张伟, 陈春艳, 韩春坛, 刘俊峰, 赵求东, 郝晓华, 李如琦, 秦艳, 黄维东, 赵成先, 王书峰. 西北干旱区融雪洪水灾害预报预警技术：进展与展望[J]. 地球科学进展, 2021, 36(3): 233-244.
[7]	崔林丽, 史军, 杜华强. 植被物候的遥感提取及其影响因素研究进展[J]. 地球科学进展, 2021, 36(1): 9-16.
[8]	蔡长娥,陈鸿,尚文亮,倪凤玲. 牙形石（ U-Th） /He热定年技术的研究进展[J]. 地球科学进展, 2020, 35(9): 924-932.
[9]	吴佳梅,彭秋志,黄义忠,黄亮. 中国植被覆盖变化研究遥感数据源及研究区域时空热度分析[J]. 地球科学进展, 2020, 35(9): 978-989.
[10]	董治宝,吕萍,李超. 火星风沙地貌研究方法[J]. 地球科学进展, 2020, 35(8): 771-788.
[11]	于德永,郝蕊芳. 生态系统服务研究进展与展望[J]. 地球科学进展, 2020, 35(8): 804-815.
[12]	刘元波, 吴桂平, 赵晓松, 范兴旺, 潘鑫, 甘国靖, 刘永伟, 郭瑞芳, 周晗, 王颖, 王若男, 崔逸凡. 流域水文遥感的科学问题与挑战[J]. 地球科学进展, 2020, 35(5): 488-496.
[13]	刘磊,翁陈思,李书磊,胡帅,叶进,窦芳丽,商建. 太赫兹波被动遥感冰云研究现状及进展[J]. 地球科学进展, 2020, 35(12): 1211-1221.
[14]	艾鑫,马明国,王雪梅,匡鸿海. 全球地球科学研究的可视化分析[J]. 地球科学进展, 2020, 35(12): 1270-1280.
[15]	张菁,路紫,杜欣儒,杜晓辉,高玉健. 京津石多机场系统航空流运行结构及其对比研究[J]. 地球科学进展, 2020, 35(12): 1281-1291.

阅读次数

全文

摘要

Review of Overseas Crop Monitoring Systems with Remote Sensing