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SPOT衛星影像之輻射改正

Radiometric Correction of SPOT Satellite Imagery

摘要


對於光學遙測而言,地表物反射率之求取一直是最主要的課題。這是因為對於同一地表物,衛星量測灰度值影像隨感測器,太陽一觀測幾何,大氣和地形起伏等因素而不同。因此為了得到一合理與上述變因無關之物理量,使其恢復地表物之反射特性,必須輻射改正衛星灰度值影像,以求得地表反射率。本文目的在輻射改正SPOT衛星影像。首先研究地表反射特性與觀測-太陽幾何及大氣混濁度變化,包括提出最佳觀測角應定義為用以估計反照率之最佳觀測方向,且與地表物,太陽天頂角以及大氣之光學特性無關。其次發展一自影像本身求取反射率之大氣改正模式。在平地模式上,提出疊代法,以由影像本身自動疊代求氣溶膠特性,以改正大氣中氣溶膠之影響。接著利用多時多角度影像,反演城市之雙向反射率分布函數(BRDF)。隨後建議以其BRDF所求正規反射率來建立光譜知識,用以自動化分類衛星影像。在山區模式上,由於疊代法不適用於山區,因此發展強制法用以改正影像之大氣效應。研究結果顯示,檢證 Kimes及Sellers1985)所求得之最佳觀測角在不同混濁程度大氣中之適用性。在地表物反射率範圍0.0∼0.6中,所反演之地表反射率RMSE可達0.01-0.02。正規化反射率建立光譜知識,此改進Wharton(1987)所提只適用於Landsat TM之缺點,用以自動化分類衛星影像。山區反射率影像之求取,可減少地形效應。由非監督性分類結果顯示,改正前影像分類出不同照射程度,但同屬於一森林類;改正後影像則自動聚集為一類。改正後影像較原始影像,亦有助於研究地表變遷。

並列摘要


Mapping of surface reflectance has been considered as a primary task for optical remote sensing, since the remotely sensed data is dependent of sensor characteristics, solar-viewing geometry, the atmosphere and topography for a given canopy. In order to retrieve its intrinsic reflective characteristics that is reasonablly indepent of the above external factors, determination of reflectance by using radiometric correction of satellite image is considered to be indispensable.The purpose of the dissertation is radiometric correction of SPOT satellite imagery. Firstly, the variability of surface reflective characteristics due to solar-viewing geometry and the atmospheric haziness is studied. We propose the optimal view angle should be defined as the direction that could be used to estimate the albedo and is insensitive to cover types, solar zenith angle and the optical properties of the atmosphere. Secondly, the atmospheric correction model of satellite image in horizontal surface is proposed. The aerosol characteristics are iteratively retrieved from the image itself. Thirdly, urban bidirectional reflectance distribution furction (BRDF) is retrieved by using multi-temporal, multiangle SPOT imageries. Fourth, we suggested the normalized reflectance determined by its intrinsic BRDF is much suitable than bidirectional reflectance factor (BRF) as the spectral knowledge. Finally, a robust algorithm for retrieving aerosol optical depth from satellite image over a mountainous area is proposed.The results show that the optimal view angle determined by Kimes and Sellers (1985) would be insensitive to the aerosol optical depth. The RMSE of derived surface reflectance in the horizontal surface is about 0.01-0.02 over reflectance range 0.0-0.6. Spectral knowledge determined from normalized reflectance is much suitable than that proposed by Wharton (1987). Determination of reflectance image can reduce the topographic effect of image mountainous area. Without atmospheric correction, terrain related classes of forest class would be classified from unsupervised classification, whereas they automatically merge to one class after atmospheric correction. Radiometric corrected image is more suitable for change detection analysis than raw image.

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