国土资源遥感
國土資源遙感
국토자원요감
REMOTE SENSING FOR LAND & RESOURCES
2014年
4期
78-84
,共7页
Landsat%长时间序列数据%格式统一%LEDAPS%反射率转换
Landsat%長時間序列數據%格式統一%LEDAPS%反射率轉換
Landsat%장시간서렬수거%격식통일%LEDAPS%반사솔전환
Landsat%dense time series data%format unification%LEDAPS%surface reflectance conversion
介绍了一种长时间序列遥感影像预处理程序,即陆地卫星生态系统干扰自适应处理系统( landsat ecosystem disturbance adaptive processing system,LEDAPS)。该程序通过使用MODTRAN太阳能输出模型,校正太阳方位、日地距离、TM或ETM+带通以及太阳辐照度,将定标影像转换为表观( top-of-atmosphere,TOA)反射率影像,并将通过浓密植被( dark dense vegetation,DDV)算法插值生成的气溶胶光学厚度( aerosol optical thickness,AOT)以及通过相关资料获得的臭氧(O3)浓度、大气压及水汽值等用于6S辐射传输模型,生成地表反射率产品。以LEDAPS可处理的标准数据Landsat7 ETM+和统一格式后的非标准数据Landsat5 TM影像为例,介绍了长时间(1987-2011年)序列数据的选择、格式统一以及算法的实现过程,同时给出了校正后影像效果评价的方法。结果表明,标准数据和非标准数据经过LEDAPS处理后生成的地表反射率产品能有效降低大气中O3、水汽及气溶胶等对影像真实反射率的影响,为土地覆盖变化和干扰因素等的长时间序列监测和生物物理参数的遥感反演提供科学产品,有助于在国内形成处理长时间序列影像数据的准则。
介紹瞭一種長時間序列遙感影像預處理程序,即陸地衛星生態繫統榦擾自適應處理繫統( landsat ecosystem disturbance adaptive processing system,LEDAPS)。該程序通過使用MODTRAN太暘能輸齣模型,校正太暘方位、日地距離、TM或ETM+帶通以及太暘輻照度,將定標影像轉換為錶觀( top-of-atmosphere,TOA)反射率影像,併將通過濃密植被( dark dense vegetation,DDV)算法插值生成的氣溶膠光學厚度( aerosol optical thickness,AOT)以及通過相關資料穫得的臭氧(O3)濃度、大氣壓及水汽值等用于6S輻射傳輸模型,生成地錶反射率產品。以LEDAPS可處理的標準數據Landsat7 ETM+和統一格式後的非標準數據Landsat5 TM影像為例,介紹瞭長時間(1987-2011年)序列數據的選擇、格式統一以及算法的實現過程,同時給齣瞭校正後影像效果評價的方法。結果錶明,標準數據和非標準數據經過LEDAPS處理後生成的地錶反射率產品能有效降低大氣中O3、水汽及氣溶膠等對影像真實反射率的影響,為土地覆蓋變化和榦擾因素等的長時間序列鑑測和生物物理參數的遙感反縯提供科學產品,有助于在國內形成處理長時間序列影像數據的準則。
개소료일충장시간서렬요감영상예처리정서,즉륙지위성생태계통간우자괄응처리계통( landsat ecosystem disturbance adaptive processing system,LEDAPS)。해정서통과사용MODTRAN태양능수출모형,교정태양방위、일지거리、TM혹ETM+대통이급태양복조도,장정표영상전환위표관( top-of-atmosphere,TOA)반사솔영상,병장통과농밀식피( dark dense vegetation,DDV)산법삽치생성적기용효광학후도( aerosol optical thickness,AOT)이급통과상관자료획득적취양(O3)농도、대기압급수기치등용우6S복사전수모형,생성지표반사솔산품。이LEDAPS가처리적표준수거Landsat7 ETM+화통일격식후적비표준수거Landsat5 TM영상위례,개소료장시간(1987-2011년)서렬수거적선택、격식통일이급산법적실현과정,동시급출료교정후영상효과평개적방법。결과표명,표준수거화비표준수거경과LEDAPS처리후생성적지표반사솔산품능유효강저대기중O3、수기급기용효등대영상진실반사솔적영향,위토지복개변화화간우인소등적장시간서렬감측화생물물리삼수적요감반연제공과학산품,유조우재국내형성처리장시간서렬영상수거적준칙。
This paper introduces a program called landsat ecosystem disturbance adaptive processing system ( LEDAPS) for the image stacks creation of the atmospherically corrected Landsat dense time series standard products from 1987 to 2011. Landsat images were first calibrated to top-of-atmosphere ( TOA) reflectance by using solar zenith, Sun-Earth distance, TM or ETM+ bandpass, and solar irradiance ( using the MODTRAN solar output model ) . The interpolated aerosol optical thickness ( AOT ) which was interpolated spatially between the“dark dense vegetation ( DDV)” using a spline algorithm, ozone, atmospheric pressure, and water vapor were supplied to the 6 S radioactive transfer algorithm to convert TOA reflectance into ground surface reflectance for each 30 m pixel. The algorithm was applied to the LEDAPS standard data of Landsat7 ETM+ and non-standard data of Landsat5 TM to illustrate the data choice, data format unification and the algorithm implementation of the dense Landsat time series. Finally, a method for the validation of the corrected images was provided. The results show that the surface reflectance products resulting from the LEDAPS processing could effectively reduce the influence caused by ozone, water vapor, and aerosol particles in the atmosphere on the true image surface reflectance. The surface reflectivity is more precise and provides standard products for multiple scientific applications, such as land cover change or forest disturbance dynamic characterization and remote sensing based biophysical parameters retrieval, thus beneficial to formulating criteria for processing sequence image data in China.
