Using Formosat-2 Satellite Data to Estimate Leaf Area Index of Rice Crop

Chwen-Ming Yang; Cheng-Chien Liu; Yi-Wen Wang; 楊純明; 劉正千; 王薏雯; Chwen-Ming Yang; Cheng-Chien Liu; Yi-Wen Wang; 楊純明; 劉正千; 王薏雯

doi:10.6574/JPRS.2008.13(4).3

Using Formosat-2 Satellite Data to Estimate Leaf Area Index of Rice Crop

Other Title

利用福衛二號衛星資料估測水稻族群葉面積指數

Journal

航測及遙測學刊

Journal Volume

13

Journal Issue

4

Pages

253-260

Date Issued

2008-12-01

Date

2008-12-01

Author(s)

Chwen-Ming Yang

Cheng-Chien Liu

Yi-Wen Wang

楊純明

劉正千

王薏雯

DOI

10.6574/JPRS.2008.13(4).3

URI

https://scholars.tari.gov.tw/handle/123456789/3643

Abstract

Estimation of plant growth over a large paddy field provides the needed information for site-specific management of crop including rice. With the estimated leaf area index (LAI) as input, growth status of rice crop may be evaluated and yield production at harvest may be assessed through functioning algorithms. This study measured the near-ground hyperspectral reflectance of rice canopy periodically on the dates of plant samplings during crop development, and then established the relationship between LAI(subscript measured) (i.e. the measured LAI) and NDVI(subscript NB) (i.e. normalized difference vegetation index calculated from narrowbands of hyperspectral reflectance) from the collected data. Rice plants of different planting densities, in the range of 0.28-2.78×10^5 hills ha^(-1), were grown in the field to produce varied values (m^2 m^(-2)) of LAI along plant growth for such purpose in the first and the second cropping seasons of 2006. A total of thirty-six multi-spectral images of the study area taken by Formosat-2 satellite on days of ground samplings were also acquired to calculate the broadband values of NDVI (NDVI(subscript BB)) and input to the LAI(subscript measured)-NDVI(subscript NB) relationship to obtain the estimated LAI (LAI(subscript BB)). Results indicate that the high-temporal and high-spatial-resolution images of Formosat-2 satellite are good source for monitoring plant growth of rice crop by providing reasonable estimated values of LAI. Such a capability of Formosat-2 spectral images enables their applicability in areas of precision farming. 在稻作生育期間定期針對大面積水田稻株進行生長估測，以提供稻株生長狀態之即時資訊，乃實施稻作精準管理所必需，俾達到水稻各特定地點之差異性操作。將葉面積指數(leaf area index; LAI)估測值輸入預先研擬之作業決策模組，不僅可以評估稻作之生長狀態，亦可同時預測收穫產量。本研究旨在稻作生育過程中定期同步取樣水稻族群LAI及量測植被高解析反射光譜，據以建立實測LAI（即LAImeasured）與高光譜窄波段標準差植被指數（即NDVINB）之數學關係。試驗係於2006年一、二期稻作期間實施，將水稻植株以8種不同栽植密度栽種於田間，族群密度介於0.28-2.78×105 hills ha-1之間，再於生育季節中定期測定LAI (平方公尺 m-2)及量測光譜。兩期稻作合計收集36幅福衛二號衛星資料（影像及光譜），經幾何與輻射校正後計算得到多頻譜寬波段標準差植被指數（即NDVIBB），將其輸入前述建立之LAImeasured-NDVINB數學關係式以獲得LAI估值（即LAIBB）。試驗結果顯示，具有高時間、高空間解析力特性之福衛二號衛星資料能夠提供合理LAI估值，因此適合作爲追蹤水稻族群生長狀態之資訊來源，此一能力亦使得福衛二號衛星資料具有應用於稻作精準管理之潛力。

Subjects

Growth estimation

Site-specific management

Hyperspectral reflectance spectrum

Normalized difference vegetation index

Satellite image of Formosat-2

生長估測

特定地點精準管理

高解析反射比光譜

標準差植被指數正規化植生指數

福衛二號衛星影像

Publisher

中華民國航空測量及遙感探測學會

Type

journal article

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