基于多源遥感数据的甘蔗霜冻监测评估方法  

Monitoring and Evaluation Method on Sugarcane Frost Injury Using Multi-sources Remote Sensing Images

作　　者：钟仕全[1,2] 陈燕丽 刘吉凯[3] 孙明 丁美花[1] 匡昭敏[1] ZHONG Shi-quan;CHEN Yan-li;Liu Ji-kai;SUN Ming;DING Mei-hua;KUANG Zhao-min(Guangxi Meteorological Disaster Mitigation Institute,Remote Sensing Application and Validation Base of NSMC,Nanning 530022,China;The Collaborative Innovation Center of the Ecological Environment&Integration Development in the Xijiang River Basin,Nanning 530001,China;Nanjing University of Information Science&Technology,Nanjing 210044,China)

机构地区：[1]广西壮族自治区气象减灾研究所,国家卫星气象中心遥感应用试验基地,南宁530022 [2]广西西江流域生态环境与一体化发展协同创新中心,南宁530001 [3]南京信息工程大学,南京210044

出　　处：《科学技术与工程》2018年第9期189-193,共5页Science Technology and Engineering

基　　金：中国气象局气象关键技术集成与应用项目(CMAGJ2013M36)、2014年公益性行业专项重点项目(GYHY201406030)和广西科技厅计划公关项目(桂科攻0816006-8)资助

摘　　要：利用Landsat 8 OLI遥感数据提取云南耿马县甘蔗集中种植区,结合中分辨率成像光谱仪(moderate-resolution imaging spectroradiometer,MODIS)历史数据和野外调查数据制定甘蔗霜冻分级指标,通过多时相甘蔗归一化植被指数(normalized difference vegetation index,NDVI)变化差异对2013年底耿马县甘蔗霜冻进行灾后监测评估。结果表明:利用Landsat 8较高分辨率及光谱可分性强的优势,结合非监督分类、监督分类以及归一化植被指数阈值剔除法可迅速有效地提取甘蔗集中种植区。甘蔗全生育期MODIS NDVI变化曲线表明,正常年份12月甘蔗NDVI平均下降0.03±0.01,结合野外调查制定的分级指标可对甘蔗霜冻进行有效评估,评估结果在空间分布上与实况相符合,面积统计结果误差小于6%。Landsat 8 OLI remote sensing data were utilized to extract sugarcane planting area of Gengma county in Yunnan Province.Sugarcane frost classification index was developed using moderate-resolution imaging spectroradiometer(MODIS)historical series combined with field investigations.Then,frost disaster happened in the end of 2013 were evaluated with multi-phases images by using normalized difference vegetation index(NDVI)difference method.The results show that Landsat 8 OLI(operational land imager)provides an excellent resource to sugarcane classification with its higher resolution and subtle spectrum.Sugarcane distinction becomes more efficiency with the incorporation of non-supervised classification and supervised classification and vegetation index threshold method.MODIS NDVI change curve of sugarcane during the whole stage shows that the normal year drop value of sugarcane NDVI is 0.03±0.01 in December.Combined with field investigation,classification index was made for sugarcane frost evaluation.Remote sensing valuation results are high consistent with the actual survey and the area measurement error is less than 6%.

关 键 词：甘蔗 霜冻 多源遥感 监测评估 

分 类 号：P429[天文地球—大气科学及气象学]