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覆蓋度對無人機熱紅外遙感反演玉米土壤含水率的影響
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國家重點研發(fā)計劃項目(2017YFC0403203、2017YFC0403302)


Influence of Coverage on Soil Moisture Content of Field Corn Inversed from Thermal Infrared Remote Sensing of UAV
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    摘要:

    為提高基于冠層溫度信息反演土壤含水率的精度,以不同水分處理的拔節(jié)期大田玉米為研究對象,采用無人機熱紅外和可見光相機獲取試驗區(qū)遙感圖像,,通過不同圖像分類方法剔除土壤背景,提取玉米植被覆蓋度(Corn vegetation coverage, Vc)及冠層溫度(Canopy temperature, Tc),,并計算冠-氣溫差(Tca)和冠-氣溫差與覆蓋度的比值,,分析這兩種指數(shù)與土壤含水率(Soil moisture content, Smc)之間的關(guān)系,。結(jié)果表明,,不同分類方法提取的玉米覆蓋度以及冠層溫度均存在差異,,由灰度分割法,、RGRI指數(shù)法、GBRI指數(shù)法3種分類方法剔除土壤背景后計算的冠-〖JP〗氣溫差,、冠-氣溫差與覆蓋度之比與土壤含水率均呈線性關(guān)系,,并且冠-氣溫差、冠-氣溫差與覆蓋度之比兩種指數(shù)反演0~30cm玉米根域深度的土壤含水率效果較好,;其中,,未剔除土壤背景的冠-氣溫差反演土壤含水率效果較差,GBRI指數(shù)分類法剔除土壤背景的冠-氣溫差反演土壤含水率效果有所提高(0~10cm,、10~20cm,、20~30cm深度的R2由0255、0360,、0131提高至0.425,、0.538、0.258),;而冠-氣溫差與覆蓋度的比值反演土壤含水率相比于冠-氣溫差精度明顯提高,0~10cm,、10~20cm,、20~30cm深度建模集R2高達(dá)0.488、0.600,、0.290,,P<0.001,驗證集R2達(dá)0.714,、0.773,、0.446,表明冠-氣溫差與覆蓋度之比是反演玉米根域深度土壤含水率效果更優(yōu)的指標(biāo),。

    Abstract:

    In order to improve the accuracy of retrieving soil moisture content based on canopy temperature information, taking the different moisture treatment of the jointing field corn as the research object, and the UAV thermal infrared and visible light camera were used to obtain the remote sensing images of the experimental area. Different image classification methods were applied to remove the soil background and extract corn coverage and canopy temperature, then the indices such as crowntemperature difference and the ratio of crowntemperature to coverage were calculated, and the relationship between the two indices and soil moisture content was analyzed subsequently. The results showed that there were differences in corn coverage extracted by different classification methods, and there were also differences in corn canopy temperature extracted by different classification methods. The crowntemperature difference, crowntemperature difference to coverage ratio calculated by three classification methods (Grayscale segmentation, RGRI index, GBRI index) had a linear relationship with soil moisture content, and it was better to invert the soil moisture content of 0~30cm corn root depth by the two indices; the crowntemperature difference without removing the soil background held the worst effect on soil moisture content, while removing soil background by GBRI index classification enjoyed the better effect on the soil moisture content(R2 was improved from 0.255,,0.360 and 0.131 to 0.425,0.538 and 0.258 at depth of 0~10cm,,10~20cm and 20~30cm); the ratio of crowntemperature difference to coverage inversion of soil moisture content performed much better than that of crowntemperature difference. At the depth of 0~10cm,,10~20cm and 20~30cm, R2 was 0.488,0.600 and 0.290 in the model set, P<0.001, and R2 was 0.714,,0.773 and 0.446 in the verification set, indicating that the ratio of crowntemperature difference to coverage was a new indicator for reversing the effect of deep soil moisture in the corn root zone. This study provided a new method for inversion of the soil moisture content of corn in the field by thermal infrared remote sensing.

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張智韜,許崇豪,譚丞軒,邊江,韓文霆.覆蓋度對無人機熱紅外遙感反演玉米土壤含水率的影響[J].農(nóng)業(yè)機械學(xué)報,2019,50(8):213-225. ZHANG Zhitao, XU Chonghao, TAN Chengxuan, BIAN Jiang, HAN Wenting. Influence of Coverage on Soil Moisture Content of Field Corn Inversed from Thermal Infrared Remote Sensing of UAV[J]. Transactions of the Chinese Society for Agricultural Machinery,2019,50(8):213-225.

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  • 收稿日期:2019-04-16
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  • 在線發(fā)布日期: 2019-08-10
  • 出版日期: 2019-08-10
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