海洋技术学报
海洋技術學報
해양기술학보
Journal Of Ocean Technology
2015年
2期
1-8
,共8页
田震%马毅%张靖宇%梁建
田震%馬毅%張靖宇%樑建
전진%마의%장정우%량건
LiDAR测深%遥感水深反演%统计方法
LiDAR測深%遙感水深反縯%統計方法
LiDAR측심%요감수심반연%통계방법
LiDAR bathymetry%remote sensing bathymetry inversion%statistical approach
主被动遥感结合反演远海岛礁周边水深信息,不仅可以有效弥补传统测深方法覆盖范围小且费时费力的不足,也可为航运安全、海洋减灾、生态环境保护等领域提供基础资料。以夏威夷瓦胡岛周边水深反演为例,应用Landsat-8多光谱遥感数据和机载LiDAR测深数据,开展了不同密度LiDAR测深数据对水深多光谱遥感反演精度的影响分析、不同水深网格化处理方法对水深遥感反演结果的影响分析和基于少量LiDAR控制区块的大区域水深反演能力分析三方面的研究工作。结果表明:(1) LiDAR测深数据密度的改变对水深反演结果的影响不大,变化后的水深反演结果与原始的水深反演结果相比,平均相对误差变化在0.3%以内,平均绝对误差变化在0.03 m以内;(2)采用均值格网处理方法的多光谱遥感水深反演精度要略高于采用中值格网处理方法的水深反演精度,具体体现在均值的平均绝对误差要比中值的低0.04~0.05 m,平均相对误差低1%~10%,反演结果的残差分布显示在0~2 m和20~25 m的水深段内均值统计法的残差分布更集中且其平均值接近于0 m,而在其它水深段二者的残差分布基本相同;(3)基于少量LiDAR控制区块的大区域遥感水深反演结果较为理想,两个检查区块的水深反演结果R2、平均绝对误差和平均相对误差分别为:0.877,1.66 m,3.5%和0.941,1.62 m,28.4%。反演结果分段分析表明各水深段内反演的精度都比较理想,平均绝对误差除20~25 m水深段外,均低于2.5 m,平均相对误差除0~2 m,2~5 m外,均低于25%。
主被動遙感結閤反縯遠海島礁週邊水深信息,不僅可以有效瀰補傳統測深方法覆蓋範圍小且費時費力的不足,也可為航運安全、海洋減災、生態環境保護等領域提供基礎資料。以夏威夷瓦鬍島週邊水深反縯為例,應用Landsat-8多光譜遙感數據和機載LiDAR測深數據,開展瞭不同密度LiDAR測深數據對水深多光譜遙感反縯精度的影響分析、不同水深網格化處理方法對水深遙感反縯結果的影響分析和基于少量LiDAR控製區塊的大區域水深反縯能力分析三方麵的研究工作。結果錶明:(1) LiDAR測深數據密度的改變對水深反縯結果的影響不大,變化後的水深反縯結果與原始的水深反縯結果相比,平均相對誤差變化在0.3%以內,平均絕對誤差變化在0.03 m以內;(2)採用均值格網處理方法的多光譜遙感水深反縯精度要略高于採用中值格網處理方法的水深反縯精度,具體體現在均值的平均絕對誤差要比中值的低0.04~0.05 m,平均相對誤差低1%~10%,反縯結果的殘差分佈顯示在0~2 m和20~25 m的水深段內均值統計法的殘差分佈更集中且其平均值接近于0 m,而在其它水深段二者的殘差分佈基本相同;(3)基于少量LiDAR控製區塊的大區域遙感水深反縯結果較為理想,兩箇檢查區塊的水深反縯結果R2、平均絕對誤差和平均相對誤差分彆為:0.877,1.66 m,3.5%和0.941,1.62 m,28.4%。反縯結果分段分析錶明各水深段內反縯的精度都比較理想,平均絕對誤差除20~25 m水深段外,均低于2.5 m,平均相對誤差除0~2 m,2~5 m外,均低于25%。
주피동요감결합반연원해도초주변수심신식,불부가이유효미보전통측심방법복개범위소차비시비력적불족,야가위항운안전、해양감재、생태배경보호등영역제공기출자료。이하위이와호도주변수심반연위례,응용Landsat-8다광보요감수거화궤재LiDAR측심수거,개전료불동밀도LiDAR측심수거대수심다광보요감반연정도적영향분석、불동수심망격화처리방법대수심요감반연결과적영향분석화기우소량LiDAR공제구괴적대구역수심반연능력분석삼방면적연구공작。결과표명:(1) LiDAR측심수거밀도적개변대수심반연결과적영향불대,변화후적수심반연결과여원시적수심반연결과상비,평균상대오차변화재0.3%이내,평균절대오차변화재0.03 m이내;(2)채용균치격망처리방법적다광보요감수심반연정도요략고우채용중치격망처리방법적수심반연정도,구체체현재균치적평균절대오차요비중치적저0.04~0.05 m,평균상대오차저1%~10%,반연결과적잔차분포현시재0~2 m화20~25 m적수심단내균치통계법적잔차분포경집중차기평균치접근우0 m,이재기타수심단이자적잔차분포기본상동;(3)기우소량LiDAR공제구괴적대구역요감수심반연결과교위이상,량개검사구괴적수심반연결과R2、평균절대오차화평균상대오차분별위:0.877,1.66 m,3.5%화0.941,1.62 m,28.4%。반연결과분단분석표명각수심단내반연적정도도비교이상,평균절대오차제20~25 m수심단외,균저우2.5 m,평균상대오차제0~2 m,2~5 m외,균저우25%。
Traditional bathymetry methods have the drawbacks of small coverage, long duration and high energy consumption, while the bathymetry inversion around islands by integrated active and passive remote sensing can not only overcome the weakness of traditional methods, but also provide fundamental data for shipping safety, marine disaster reduction and marine eco-environmental protection. Taking the Oahu Island of Hawaii as an example, this paper studies the impacts of different point-density LiDAR data and different gridding approaches on the inversion accuracy, as well as analyzes the ability of large-scale water depth inversion using a few LiDAR controlled blocks based on the multi-spectral images of Landsat-8 and LiDAR bathymetry data. The following results have been obtained. (1) The inversion accuracy is not severely affected by the change of point-density of LiDAR data, with the difference of mean relative error lower than 0.3% and mean absolute error less than 0.03 m. (2) The bathymetry inversion accuracy with the equalization method is slightly higher than that with the median method, which is proved by the fact that the mean absolute error of the equalized value decreases by 0.04-0.05 m as against that of the median value, with the mean relative error lowering by 1%-10%. Besides, the residual distribution of inversion results shows that the equalization approach has a more concentrated residual and its mean value is close to 0 m in the depth ranges of 0-2 m and 20-25 m, while both approaches show a basically same distribution trend in other depth ranges. (3) Bathymetry inversion based on a few LiDAR controlled blocks achieves relatively ideal results. The R 2, mean absolute error and mean relative error of 2 check blocks are 0.877, 1.66 m, 23.5% and 0.941, 1.62 m, 28.4%, respectively. Analysis indicates that the inversion precisions in different depth ranges are satisfactory in general. Except the 20-25 m range, almost all the mean absolute errors are below 2.5 m; and only the ranges of 0-2 m and 2-5 m have the mean absolute error of beyond 25%.