检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:杨俊泉[1] 陈尚文[1] 沈建中[1] 张远飞[2] 莫伟华[3] 林少雄[4]
机构地区:[1]广西大学林学院 [2]中国有色总公司矿产地质研究院 [3]广西气象台 [4]广西气象局
出 处:《国土资源遥感》1997年第4期7-13,共7页Remote Sensing for Land & Resources
摘 要:本文介绍了利用虫害年度的多时相NOAA-AVHRR图像数据计算监测区归一化差植被指数(NDVI),结合收集到的监测区的马尾松毛虫害历史资料来进行森林病虫害监测和预报的研究成果。从统计编制的分区NDVI时间序列变化曲线的对比来看,虫害区与非虫害区NDVI曲线具有一定的时序变化特征,对监测虫害有一定作用,也显示了NOAA-AVHRR资料在森林病虫害监测预报方面有一定应用前景。Using multi-temporal NOAA-AVHRR data, combine with historical data, this paper deals with how to use NDVI to monitor and forecast pest which mainly caused by pine caterpillar moth (Dendrolimus punctatus walker). First, geometric correction and registration for the images were made; Second, through extracting image data and rejecting cloud contamination pixels in monitor regions, all monitor regions were separated into different districts according to the features of geography and climate, then every district was separated into pest injury and non-injury areas; At last, NDVI values of every pixels were computed, the statistic values about two areas were computed and time-series curves of NDVI statistics about two areas were compared. It was discovered that time-series curves of NDVI average value can be used to monitor forest pest happening, time-series curves of NDVI variation coefficient can be used to forecast. In the end, the paper provids the prospect of using NOAA-AVHRR images to monitor and forecast forest pest injury.
分 类 号:S763.42[农业科学—森林保护学] S718.54[农业科学—林学]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.220