| 摘要: | 地表能量傳遞與轉換的過程在區域天氣、氣候和水循環中扮演著關鍵角色，而理解能量交換過程的特性對於提升許多應用的效率與效用相當重要，例如天氣預報系統、水文過程數值模擬、水資源管理、土地利用規劃、森林脆弱性評估等。長久以來，地面觀測一直被當作地表熱通量估算的逐點測量方法，但是其使用通常侷限於設定的地點，以及空間覆蓋範圍，從而導致難以在區域性的尺度操作。隨著以衛星為基礎的系統發展，空間科學和技術已成為全球觀測系統的關鍵要素，這為地-氣熱交換研究提供了高水準的時空效率、經濟效益之資料來源，根據來自遙測資料不同程度的輸入要求，已有許多不同的執行方法。以遙測資料為主要輸入，地表能量平衡模式中的物理過程方法被廣泛用於估計陸-氣界面的能量交換。然而，這些方法涉及建立複雜的物理過程，並且仍然侷限於代表地面觀測系統的設定地點。
多光譜遙測技術已被普遍用於收集影響陸-氣界面傳熱過程的地表特性，利用反射率的差異，可以藉由分析光譜反射率特性來了解地表特徵。在本研究中，提出了一種新的多光譜指數，即「常態化差異潛熱指數」（NDLI），用於從衛星影像中推估潛熱通量。它利用了綠色、紅色和短波紅外光三個波段的反射率觀測數值，而這三個波段通常用於衛星地球觀測任務。NDLI首先用於淬取台灣嘉義市東部子區域內陸-氣之間的熱傳遞訊號。與現有的其他遙測指標相比，NDLI與地表模型能量平衡式（SEBAL）計算出的潛熱通量具有最高的相關性係數( r = 0.75)。 隨後，對NDLI進行檢驗並推估在越南太平省的地表蒸發散 (ET)。 結果表明，在98.1％的稻田中，NDLI推估的ET與SEBAL的推估結果相差不到10％。此外，NDLI推估的ET在逆境水稻區中呈現較低數值，顯示此方法之優越性。結論是，新開發的NDLI能夠量化地表的水可利用量，並且在需要陸-氣界面傳熱信息的各種實際應用中NDLI具有潛在的幫助作用。由於NDLI的方程式簡單易行，透過現有的大量衛星資料，可在其他感興趣的區域進行操作，並有助於多種實際應用
;Surface energy processes have an essential role in the regional weather, climate, and hydrological cycles. Understanding the characteristic of energy exchange processes is vital to improve the efficiency and effectiveness of many applications, such as water resources management, land use planning, forest vulnerability assessment, numerical modeling of hydrological processes, weather forecasting system, etc. Ground-based instrument systems have been long used as a point-wise measurement method for land heat fluxes estimation. However, their use is often restricted to a pre-defined domain and limited with spatial coverage, resulting in difficulty to operate over a regional scale. With the development of satellite-based systems, space science and technology is a key component of the global observation system, which provides a promising data source for the investigations of land-air heat exchange with high spatio-temporal efficiency and economic benefits. Different methods have been proposed and performed with varying degrees of input requirement from remotely sensed data in which the approaches of physical processes in surface energy balance models were widely used to estimate the energy exchange at the land-air interface using the remote sensing data as the primary input. However, these approaches involve the establishment of complex physical processes and still are limited to the areas with existing ground-based measurement system.
Multi-spectral remote sensing has been widely utilized to collect the Earth’s surface properties that basically influence the processes of heat transfer at the land-air interface. The distinction in reflectance makes it possible to understand the earth′s surface features by analyzing its spectral reflectance signatures. In this study, a new multiple-band index, Normalized Difference Latent heat Index, is proposed for latent heat flux extraction from satellite imagery. It utilizes the reflectance observations of three channels, which are primarily used for the optical Earth observation satellites, including green, red, and shortwave-infrared. The NDLI is firstly applied to extract the information of land–air latent heat exchange over a subset region in the eastern part of Chiayi City, Taiwan. The NDLI exhibited superiority in representing the potential latent heat flux by showing the highest consistency coefficient (r = 0.75) with the corresponding predicted results from the Surface Energy Balance Algorithm for Land model (SEBAL) as compared to the other existing satellite indices. Subsequently, the NDLI is adopted to enhance the evapotranspiration estimation over rice paddy areas in the Thai Binh Province, Vietnam. Results indicated that the NDLI-derived ET differs from the derivative of SEBAL by less than 10% over 98.1% of the paddy field. Moreover, the NDLI-derived ET exhibited its superiority in revealing the low amounts of ET in the rice paddy areas under stress. It is concluded that the newly developed NDLI is a good indicator to quantify the surface moisture, evapotranspiration, and latent heat transfer at the land-air interface. The NDLI is potentially helpful for a variety of practical applications since its formula is simple and easily implemented from the abundant existing satellites |
