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机构地区:[1]重庆师范大学地理与旅游学院,重庆400047 [2]重庆市高校GIS应用研究重点实验室,重庆400047
出 处:《山地学报》2017年第6期919-925,共7页Mountain Research
基 金:中国科学院重点部署项目(KZZD-EW-TZ-18);国家自然科学基金项目(51308575);重庆市气象局开放式研究资助项目(Kfjj-201303)~~
摘 要:时序NDVI数据由于受到云覆盖、大气扰动、传感器角度等因素的影响,存在诸多噪声,在其应用之前需要进行必要的重建,特别是在常年多云雾的重庆地区。本文在QA(Quality Assessment)数据分析的基础上,利用WS法、S-G法和HANTS法对重庆2010—2014年MODIS逐月1 km NDVI(MOD13A3)数据集进行了重建,对整体保真性水平和不同土地覆被类型(分常绿阔叶林、常绿针叶林、落叶阔叶林、常绿阔叶灌木林、水田、旱地和草丛等7种)的保真性进行了对比分析。研究结果表明:WS法不论在总体上还是在不同土地覆被类型下,其重建前后的保真性均好于HANTS法和S-G法,同时,对草丛和常绿阔叶灌木林重建后的数据保真性最高,R值分别为0.8977和0.8624,RMSE值分别为0.0589和0.0669;对水田和落叶阔叶林的保真性较差,R值分别为0.8343和0.8260,RMSE均为0.0766。Due to the influence of cloud cover,atmospheric disturbance and sensor position,time-dependent NDVI data contain many noises and need to be reconstructed before application. Typically in Chongqing,it is a city featured by perennial cloudy weather. Based on the QA( Quality Assessment) data analysis of MODIS product( MOD13 A3),the data set of monthly NDVI collected in Chongqing from 2010 to 2014 was reconstructed by WS method,SG method and HANTS method separately for verification. The data fidelity level of the city in its entirety was compared with those of varied land cover types( evergreen broad-leaved forest,evergreen coniferous forest,deciduous broad-leaved forest,evergreen broad-leaved shrub,paddy field,dry land and grass). Results showed that,no matter how the date fidelity level were evaluated from before or after the data reconstruction,from a view of whole city or from different types of land covers,WS method was better than HANTS method and SG method. There existed the highest data fidelity for grassland and evergreen broad-leaved shrub,with R value 0. 8977 and 0. 8624 respectively,and the RMSE values were 0. 0589 and 0. 0669,respectively. The data fidelity of paddy field and deciduous broad-leaved forest were poor with R values of 0. 8343 and 0. 8260 respectively,and RMSE 0. 0766.
分 类 号:TP79[自动化与计算机技术—检测技术与自动化装置]
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