Field studies were conducted at Bushland, Texas, USA, in 2004 to examine usefulness of canopy temperature depression （CTD）, the difference of air-canopy temperature, in screening wheat （Triticum aestivum L.） genot...Field studies were conducted at Bushland, Texas, USA, in 2004 to examine usefulness of canopy temperature depression （CTD）, the difference of air-canopy temperature, in screening wheat （Triticum aestivum L.） genotypes for yield under dryland and irrigated. Forty winter wheat genotypes were grown under irrigation and dryland. CTDs were recorded after heading between 1 330 and 1 530 h on 6 clear days for dryland and 9 days for irrigation. Drought susceptible index （DSI） for each genotype was calculated using mean yield under dryland and irrigated conditions. Genotypes exhibited great differences in CTD under each environment. The dryland CTDs averaged 1.33℃ ranging from -0.67 to 2.57℃, and the average irrigation CTD were 4.59℃ ranging from 3.21 to 5.62℃. A low yield reduction was observed under dryland conditions relative to irrigated conditions for high-CTD genotypes. CTD values were highly negatively correlated with DSI under dryland, and genotypes of CTDs = 1.3℃ in dryland condition were identified as drought resistant. For 21 genotypes classified as drought resistant by DSI, their CTDs were 1.68℃ for dryland and 4.35℃ for irrigation on average; for 19 genotypes classified as drought susceptible by DSI, average CTD was 0.94℃ in dryland and 4.85℃ in irrigation. The high-yield genotypes consistently had high CTD values, and the low-yield ones had low CTD values for all measurements in dryland. After heading, genotypes maintained consistent ranking for CTD. Regression results for CTD and yield suggested that the best time for taking CTD measurement was 3-4 weeks after heading in irrigation but any time before senescence in dryland. Crop water stress index （CWSI） calculated from CTD data was highly correlated with CWSI calculated from yield, which suggesting traditional costly CWSI measurement may be improved by using portable infrared thermometers. Most importantly, grain yield was highly correlated with CTD under dryland （R^2 = 0.79-0.86） and irrigation （R^2 = 0.46-0.58） c展开更多
基于冠层温度的作物水分胁迫指标CWSI(Crop Water Stress Index)广泛用于指导作物灌水时间,利用自动气象站的观测资料分别计算了不同供水处理条件下冬小麦中午12:00的作物水分胁迫指数,并将作物水分胁迫指数和对应的土壤含水量进行相关...基于冠层温度的作物水分胁迫指标CWSI(Crop Water Stress Index)广泛用于指导作物灌水时间,利用自动气象站的观测资料分别计算了不同供水处理条件下冬小麦中午12:00的作物水分胁迫指数,并将作物水分胁迫指数和对应的土壤含水量进行相关分析,以探讨用作物水分胁迫指数确定灌水量的可行性。结果表明,二者是一定相关性,但相关关系不密切,复相关系数为0.54,作物水分胁迫指数随土壤含水量的降低呈明显的增大趋势;作物水分胁迫指数随气象因子的波动表现出明显的波动性,且在作物遭受较严重水分胁迫下波动性更强,这预示着利用作物水分胁迫指数直接定量标识作物土壤水分状况的可靠性不强。展开更多
针对当前无人机热红外遥感提取冠层温度不准确、监测作物水分胁迫状况精度不高的问题,该研究以不同水分处理的拔节期夏玉米为研究对象,利用无人机获取试验区域热红外和可见光图像资料,分别采用Otsu算法、EXG-Kmeans算法和Otsu-EXG-Kmean...针对当前无人机热红外遥感提取冠层温度不准确、监测作物水分胁迫状况精度不高的问题,该研究以不同水分处理的拔节期夏玉米为研究对象,利用无人机获取试验区域热红外和可见光图像资料,分别采用Otsu算法、EXG-Kmeans算法和Otsu-EXG-Kmeans算法获取冠层区域图像,并对提取结果进行精度评价,而后采用最优算法求得对应作物水分胁迫指数(Crop Water Stress Index,CWSI),通过分析CWSI同土壤含水率相关关系以及CWSI日平均变化趋势来监测玉米水分亏缺状况。结果表明:1)相比于其他方法,Otsu-EXG-Kmeans算法对冠层温度提取精度更高(用户精度为95.9%),提取的冠层温度更接近实测温度(r=0.788),可以准确获取图像冠层温度。2)相比于冠层温度,CWSI与土壤含水率的相关性更高(r=-0.738),CWSI日平均变化趋势更符合实际情况,可更加精确地监测玉米缺水状况。该研究为无人机遥感精准监测作物水分胁迫状况提供参考。展开更多
为了减少土壤背景带来的干扰,更加准确、高效的获取无人机热红外图像中的玉米冠层温度,进而快速反演玉米地土壤含水率,以4种水分梯度处理的拔节期玉米为研究对象,借助无人机可见光和热红外图像,采用RGRI指数法、Otsu阈值法和不剔除土壤...为了减少土壤背景带来的干扰,更加准确、高效的获取无人机热红外图像中的玉米冠层温度,进而快速反演玉米地土壤含水率,以4种水分梯度处理的拔节期玉米为研究对象,借助无人机可见光和热红外图像,采用RGRI指数法、Otsu阈值法和不剔除土壤背景3种处理方法提取热红外图像中玉米冠层温度信息,计算作物水分胁迫指数(Crop water stress index,CWSI)并用于反演不同水分梯度处理下玉米地不同深度的土壤含水率,基于3种方法获得的CWSI分别记为CWSIRGRI、CWSIOtsu、CWSIsc。结果表明:(1)基于RGRI指数法获取的玉米冠层温度与实测冠层温度的相关性最高(R2均大于0.8;RMSE均小于1℃),Otsu方法次之,不剔除土壤背景方法效果最差。(2)在整个拔节期,CWSIRGRI反演土壤含水率效果最好(R2均大于0.5,P<0.01;效果显著),CWSIOtsu次之、CWSIsc反演效果最差。(3)选取CWSIRGRI为最优CWSI指标,其在玉米拔节期5个土壤深度内的R2呈现先上升后下降的趋势且都在0~30 cm深度内达到最大值。因此,基于RGRI指数法建立的CWSIRGRI可以作为反演玉米地土壤含水率的有效指标。展开更多
为使热红外遥感诊断土壤含水率更加准确、高效,以不同水分处理的大田玉米为研究对象,借助无人机可见光图像,对热红外图像进行植土分离,并提取玉米冠层温度和地表土壤温度。通过剔除温度直方图两端1%的温度像元对温度信息进行优化,进而...为使热红外遥感诊断土壤含水率更加准确、高效,以不同水分处理的大田玉米为研究对象,借助无人机可见光图像,对热红外图像进行植土分离,并提取玉米冠层温度和地表土壤温度。通过剔除温度直方图两端1%的温度像元对温度信息进行优化,进而计算作物水分胁迫指数(Crop water stress index,CWSI)、冠层相对温差(Canopy relative temperature difference,CRTD)、地表相对温差(Surface relative temperature difference,SRTD),利用三者之和求得水分温度综合指数(Water-temperature composite index,WTCI),并用于诊断不同深度的土壤含水率。结果表明,剔除温度直方图两端1%温度像元的玉米冠层温度与实测冠层温度的相关性更高(4次试验的R2由0.823、0.886、0.899、0.876提高至0.906、0.938、0.944、0.922),剔除温度直方图前端1%温度像元的地表土壤温度与实测地表温度的相关性也更高(2次试验的R2由0.841、0.875提高至0.908、0.925),即通过直方图法优化的温度更接近实测温度;在拔节前期,CWSI、WTCI诊断0~20 cm土壤含水率效果较优,而拔节后期、抽雄吐丝期、乳熟期诊断0~40 cm土壤含水率效果较优;在半覆盖条件下,包含冠层温度信息(CWSI、CRTD)和土壤温度信息(SRTD)的WTCI1与土壤含水率的相关性更高(0~40cm:决定系数为0.500、0.821,高于0.463、0.748);在全覆盖状态下,包含冠层相对温差(CRTD)的WTCI2与土壤含水率的相关性更高(0~40 cm:决定系数为0.809、0.729,高于0.721、0.656),表明WTCI是诊断土壤含水率效果较优的指标。展开更多
基金This study was financially supported by the China National 863 Program(2002AA2Z4011)the China National R&D Program(2004BA508B09)Texas wheat breed and physiology program.These assistances are gratefully acknowledged.We also thank Gail Petersion and Melanie Allred for their assistance when the study was going on.
文摘Field studies were conducted at Bushland, Texas, USA, in 2004 to examine usefulness of canopy temperature depression （CTD）, the difference of air-canopy temperature, in screening wheat （Triticum aestivum L.） genotypes for yield under dryland and irrigated. Forty winter wheat genotypes were grown under irrigation and dryland. CTDs were recorded after heading between 1 330 and 1 530 h on 6 clear days for dryland and 9 days for irrigation. Drought susceptible index （DSI） for each genotype was calculated using mean yield under dryland and irrigated conditions. Genotypes exhibited great differences in CTD under each environment. The dryland CTDs averaged 1.33℃ ranging from -0.67 to 2.57℃, and the average irrigation CTD were 4.59℃ ranging from 3.21 to 5.62℃. A low yield reduction was observed under dryland conditions relative to irrigated conditions for high-CTD genotypes. CTD values were highly negatively correlated with DSI under dryland, and genotypes of CTDs = 1.3℃ in dryland condition were identified as drought resistant. For 21 genotypes classified as drought resistant by DSI, their CTDs were 1.68℃ for dryland and 4.35℃ for irrigation on average; for 19 genotypes classified as drought susceptible by DSI, average CTD was 0.94℃ in dryland and 4.85℃ in irrigation. The high-yield genotypes consistently had high CTD values, and the low-yield ones had low CTD values for all measurements in dryland. After heading, genotypes maintained consistent ranking for CTD. Regression results for CTD and yield suggested that the best time for taking CTD measurement was 3-4 weeks after heading in irrigation but any time before senescence in dryland. Crop water stress index （CWSI） calculated from CTD data was highly correlated with CWSI calculated from yield, which suggesting traditional costly CWSI measurement may be improved by using portable infrared thermometers. Most importantly, grain yield was highly correlated with CTD under dryland （R^2 = 0.79-0.86） and irrigation （R^2 = 0.46-0.58） c
文摘剔除无人机热红外影像中的土壤背景是提高作物水分诊断精度的有效途径,但也是热红外图像处理的难点问题。本文以不同水分处理的花铃期棉花为研究对象,分别在09:00、13:00和17:00等3个时刻,连续5 d采集无人机高分辨率热红外影像,并采用二值化Ostu算法和Canny边缘检测算法对热红外图像进行掩膜处理,实现对土壤背景的剔除,然后分别计算二值化Ostu算法、Canny边缘检测算法和包含土壤背景下的3种棉花水分胁迫指数(Crop water stress index,CWSI),最后建立不同时刻下3种CWSI与棉花叶片气孔导度Gs的关系模型。研究结果表明,应用Canny边缘检测算法可有效剔除热红外影像中的土壤背景,剔除土壤背景后的温度直方图呈单峰的偏态分布;3种处理方法获得的作物水分胁迫指数CWSI中,Canny边缘检测算法的CWSI最小,二值化Ostu算法的CWSI较高,包含土壤背景的CWSI最大;采用Canny边缘检测算法剔除土壤背景后的CWSI与棉花叶片气孔导度Gs的决定系数R2达到0.84,Ostu算法的结果次之,包含土壤背景的最差。本研究可为无人机热红外遥感监测作物水分状况提供参考。
文摘基于冠层温度的作物水分胁迫指标CWSI(Crop Water Stress Index)广泛用于指导作物灌水时间,利用自动气象站的观测资料分别计算了不同供水处理条件下冬小麦中午12:00的作物水分胁迫指数,并将作物水分胁迫指数和对应的土壤含水量进行相关分析,以探讨用作物水分胁迫指数确定灌水量的可行性。结果表明,二者是一定相关性,但相关关系不密切,复相关系数为0.54,作物水分胁迫指数随土壤含水量的降低呈明显的增大趋势;作物水分胁迫指数随气象因子的波动表现出明显的波动性,且在作物遭受较严重水分胁迫下波动性更强,这预示着利用作物水分胁迫指数直接定量标识作物土壤水分状况的可靠性不强。
文摘针对当前无人机热红外遥感提取冠层温度不准确、监测作物水分胁迫状况精度不高的问题,该研究以不同水分处理的拔节期夏玉米为研究对象,利用无人机获取试验区域热红外和可见光图像资料,分别采用Otsu算法、EXG-Kmeans算法和Otsu-EXG-Kmeans算法获取冠层区域图像,并对提取结果进行精度评价,而后采用最优算法求得对应作物水分胁迫指数(Crop Water Stress Index,CWSI),通过分析CWSI同土壤含水率相关关系以及CWSI日平均变化趋势来监测玉米水分亏缺状况。结果表明:1)相比于其他方法,Otsu-EXG-Kmeans算法对冠层温度提取精度更高(用户精度为95.9%),提取的冠层温度更接近实测温度(r=0.788),可以准确获取图像冠层温度。2)相比于冠层温度,CWSI与土壤含水率的相关性更高(r=-0.738),CWSI日平均变化趋势更符合实际情况,可更加精确地监测玉米缺水状况。该研究为无人机遥感精准监测作物水分胁迫状况提供参考。
文摘为了减少土壤背景带来的干扰,更加准确、高效的获取无人机热红外图像中的玉米冠层温度,进而快速反演玉米地土壤含水率,以4种水分梯度处理的拔节期玉米为研究对象,借助无人机可见光和热红外图像,采用RGRI指数法、Otsu阈值法和不剔除土壤背景3种处理方法提取热红外图像中玉米冠层温度信息,计算作物水分胁迫指数(Crop water stress index,CWSI)并用于反演不同水分梯度处理下玉米地不同深度的土壤含水率,基于3种方法获得的CWSI分别记为CWSIRGRI、CWSIOtsu、CWSIsc。结果表明:(1)基于RGRI指数法获取的玉米冠层温度与实测冠层温度的相关性最高(R2均大于0.8;RMSE均小于1℃),Otsu方法次之,不剔除土壤背景方法效果最差。(2)在整个拔节期,CWSIRGRI反演土壤含水率效果最好(R2均大于0.5,P<0.01;效果显著),CWSIOtsu次之、CWSIsc反演效果最差。(3)选取CWSIRGRI为最优CWSI指标,其在玉米拔节期5个土壤深度内的R2呈现先上升后下降的趋势且都在0~30 cm深度内达到最大值。因此,基于RGRI指数法建立的CWSIRGRI可以作为反演玉米地土壤含水率的有效指标。
文摘为使热红外遥感诊断土壤含水率更加准确、高效,以不同水分处理的大田玉米为研究对象,借助无人机可见光图像,对热红外图像进行植土分离,并提取玉米冠层温度和地表土壤温度。通过剔除温度直方图两端1%的温度像元对温度信息进行优化,进而计算作物水分胁迫指数(Crop water stress index,CWSI)、冠层相对温差(Canopy relative temperature difference,CRTD)、地表相对温差(Surface relative temperature difference,SRTD),利用三者之和求得水分温度综合指数(Water-temperature composite index,WTCI),并用于诊断不同深度的土壤含水率。结果表明,剔除温度直方图两端1%温度像元的玉米冠层温度与实测冠层温度的相关性更高(4次试验的R2由0.823、0.886、0.899、0.876提高至0.906、0.938、0.944、0.922),剔除温度直方图前端1%温度像元的地表土壤温度与实测地表温度的相关性也更高(2次试验的R2由0.841、0.875提高至0.908、0.925),即通过直方图法优化的温度更接近实测温度;在拔节前期,CWSI、WTCI诊断0~20 cm土壤含水率效果较优,而拔节后期、抽雄吐丝期、乳熟期诊断0~40 cm土壤含水率效果较优;在半覆盖条件下,包含冠层温度信息(CWSI、CRTD)和土壤温度信息(SRTD)的WTCI1与土壤含水率的相关性更高(0~40cm:决定系数为0.500、0.821,高于0.463、0.748);在全覆盖状态下,包含冠层相对温差(CRTD)的WTCI2与土壤含水率的相关性更高(0~40 cm:决定系数为0.809、0.729,高于0.721、0.656),表明WTCI是诊断土壤含水率效果较优的指标。
