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基于無人機遙感的玉米水分利用效率與生物量監(jiān)測
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國家自然科學基金項目(51979233)、楊凌示范區(qū)產(chǎn)學研用協(xié)同創(chuàng)新重大項目(2018CXY-23)、國家重點研發(fā)計劃項目(2017YFC0403203)和高等學校學科創(chuàng)新引智計劃項目(B12007)


Maize Water Use Efficiency and Biomass Estimation Based on Unmanned Aerial Vehicle Remote Sensing
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    摘要:

    玉米生物量及水分利用效率是反映作物長勢和作物品質(zhì)的重要指標。為實現(xiàn)農(nóng)業(yè)精準管理,本文以不同水分處理的青貯玉米為研究對象,探討無人機多光譜遙感平臺結(jié)合作物生長模型估測青貯玉米生物量及水分利用效率的可行性。首先,將基于高時空分辨率無人機多光譜圖像估測的關(guān)鍵作物參數(shù)蒸騰系數(shù)kt輸入到簡單的水分效率模型中,來擬合不同水分脅迫處理下玉米水分利用效率WUE和標準化水分利用效率WP*;然后,采用擬合的WUE、WP*估算相同水分和不同水分狀況下的玉米生物量,并進行驗證;基于高時空分辨的無人機多光譜遙感圖像獲取了大田尺度上的WUE、WP*和生物量的空間分布圖。結(jié)果表明,基于無人機多光譜、氣象和土壤水分數(shù)據(jù)計算的實際蒸騰量∑Tc,adj和∑ktkswkst(ksw、kst為環(huán)境脅迫因子)與玉米生物量具有極顯著(P<0.001)的相關(guān)性,不同水分處理下WUE的決定系數(shù)R2均不小于0.92,WP*的R2均不小于0.93。在同一水分脅迫下,使用擬合的WUE和WP*對生物量的估測精度幾乎相同,玉米V-R4生育期估測精度較高,WUE的RMSE為126g/m2,WP*的RMSE為91.7g/m2,一致性指數(shù)d均為0.98,但在R5-R6生育期內(nèi)精度不高。在不同水分脅迫下,使用WUE和WP*估測生物量時,WUE容易受到水分脅迫影響,精度較低(RMSE為306g/m2,d=0.93),而WP*的精度較高(RMSE為195g/m2,d=0.97)。研究表明,將無人機遙感平臺與作物生長模型相結(jié)合能夠很好地估測大田玉米生物量及水分利用效率。

    Abstract:

    Biomass and crop water use efficiency (CWUE) are important indicators to reflect plant growth productivity and quality, and their accurate real-time acquisition is the guarantee to achieve accurate agricultural management. To assess the feasibility of unmanned aerial vehicle (UAV) remote sensing platform combined with water use efficiency growth models to estimate crop biomass and CWUE, the silage maize was employed as the research object. The key crop parameter transpiration coefficient (kt) estimated based on the multispectral image of the high-resolution space-time UAV was firstly inputted into two simple water efficiency models to fit the WUE and WP* of the silage maize under different water stress conditions, and then the biomass of silage maize under the same and different water conditions was estimated by the fitted WUE and WP* values. The results showed that the correlation between the biomass and ∑Tc,adj and ∑ktkswkst based on the multispectral UAV platform combined with meteorological and soil water content data reached extremely significant level (P<0.001). Under the different stress conditions, the lowest determinant coefficients of fitted WUE and WP* were 0.92 and 0.93, respectively. Under the same water stress condition, the accuracy of biomass estimation by using the fitted WUE and WP* values was almost the same, which was shown in the following aspects: in the V-R4 growth period of maize, the accuracy of biomass estimation based on the fitted WUE indicating with RMSE was 126g/m2, d was 0.98, the accuracy of biomass estimation based on the fitted WP* indicating with RMSE was 91.7g/m2, d was 0.98, but the accuracy was not high in the R5-R6 growth period. When WUE and WP* values were used to estimate biomass under different water stress conditions, WUE was susceptible to water stress with low accuracy (RMSE was 306g/m2, d was 0.93), while WP* had higher accuracy (RMSE was 195g/m2,d was 0.97). At the same time, the spatial distribution maps of WUE, WP* and biomass on the field scale were obtained based on the multispectral remote sensing image of UAV. Overall, the combination of UAV remote sensing platform and crop growth model can well estimate the field silage maize biomass and water use efficiency.

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韓文霆,湯建棟,張立元,牛亞曉,王彤華.基于無人機遙感的玉米水分利用效率與生物量監(jiān)測[J].農(nóng)業(yè)機械學報,2021,52(5):129-141. HAN Wenting, TANG Jiandong, ZHANG Liyuan, NIU Yaxiao, WANG Tonghua. Maize Water Use Efficiency and Biomass Estimation Based on Unmanned Aerial Vehicle Remote Sensing[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(5):129-141.

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  • 收稿日期:2020-07-01
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  • 在線發(fā)布日期: 2021-05-10
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