查詢結果分析
相關文獻
- 以近地面高解析植被光譜及模擬SPOT衛星寬頻光譜估測水稻生長性狀的變化
- Estimation of Rice Growth from Reflectance Spectra of Vegetative Cover
- SPOT衛星影像反演與地面多角度量測水稻反射率初探
- 苗床密度對紅檜1-0幼苗在穴植管中生長的影響
- The Relationships between the Crack-tip Stress Fields and the CreepCrack Growth Rates
- 溫度與大豆植株在營養生長期生長發育之關係
- 水分對楓香及烏心石苗木生長之影響
- Using Formosat-2 Satellite Data to Estimate Leaf Area Index of Rice Crop
- Effects of Thrombin on the Growth, Protein Synthesis, Attachment, Clustering and Alkaline Phosphatase Activity of Cultured Human Periodontal Ligament Fibroblasts
- In戓Ga[fec5]P Grown by All Solid Source Molecular Beam Epitaxy
頁籤選單縮合
題 名 | 以近地面高解析植被光譜及模擬SPOT衛星寬頻光譜估測水稻生長性狀的變化=Estimating Rice Growth Using Ground-Based Hyperspectral Reflectance Data and Simulated SPOT Broad Band Data |
---|---|
作 者 | 陳榮坤; 楊純明; | 書刊名 | 中華農業研究 |
卷 期 | 51:4 2002.12[民91.12] |
頁 次 | 頁1-18 |
分類號 | 434.113 |
關鍵詞 | 近地面高解析植被光譜; 光譜特徵模式; 植被指數; 生長; SPOT衛星; Ground-based hyperspectral reflectance data; Spectral characteristic model; Vegetation index; Growth; SPOT satellite; |
語 文 | 中文(Chinese) |
中文摘要 | 利用2000年一、二期稻作近地面植被高解析光譜(350-2500nm)與生長性狀資料,篩檢與生長有關之植被光譜特徵,並建立光譜特徵模式以估測水稻生長,又比較窄波段與模擬SPOT衛星寬波段之植被指數估測生長之差異,以評估利用SPOT衛星光譜資料監測水稻生長可行性。由全生育期三維動態植被反射光譜,發現水稻與一般綠色植物的反射光譜曲線類似。由不同生長性狀之全生育期分佈圖,約於抽穗期前後達到最高峰而呈現曲線分佈。以量測光譜之反射比與各生長性狀進行相關強度分析,顯示抽穗前及抽穗後的相關趨勢雷同,但抽穗後相關性較低。由多元直線複迴歸分析的逐步迴歸選取程序,選出2-3個波長變數,建立多特徵窄波段組合的關係模式。在檢定的六種植被指數中,抽穗前以GREEN/NIR對各性狀的相關性最佳,抽穗後各指數與生長性狀的相關性均較低,以RED/NIR的相關性較佳。無論抽穗前或抽穗後,模擬SPOT衛星寬波段頻譜的植被指數與各性狀的相關性略低於窄波段光譜植被指數,但預測結果的相似度均高於98%。 |
英文摘要 | Ground-based remotely sensed high-resolution reflectance spectra and growth traits of rice plants grown in the 1st and the 2nd cropping seasons of 2000 were used for establishing spectral characteristic models to estimate rice growth. Differences in plant growth from the estimates of spectral indices with narrow bands and simulated SPOT broad bands were compared. The 3-dimensional reflectance spectra of rice canopy were similar to those of other green plants. The patterns of growth traits were curvilinear, reached the climax near heading and differed between cropping seasons. By correlation intensity analysis between reflectance of narrow bands and growth traits, it showed that the correlation intensity curves were similar before and after heading, with lesser degree of correlation after heading. By the multiple linear regression (MLR) analysis, the best-2 and best-3 MLR models were established. Among the examined spectral indices, the GREEN/NIR ratio had the best correlation with growth traits before heading yet it was the RED/NIR ratio after heading. Differences in growth traits from spectral index estimations by narrow bands and the simulated SPOT broad bands were not significant. |
本系統中英文摘要資訊取自各篇刊載內容。