2005年-2008年亚洲东部沙尘暴的定期数字记录监测

地处亚洲东部的中国长春,蒙古乌兰巴托和日本鹿儿岛,作为亚洲沙尘暴的地面监测站点,用数码相机全自动定时拍摄记录天空的数字照片,通过分析数字照片数据上像素点的信息和建筑的能见度,来判断沙尘暴事件的发生及强度。对比分析了2005年-2008年冬春季节数字监测数据与NOAA,MT-SAT和Terra,Aqua/MOD IS的卫星遥感图片以及其他相关沙尘天气的报道。在监测的图片数据上,持续1-2天的强沙尘暴天气能够被清楚的识别,轻度的沙尘天气与云量较多的天气较难区别。     

污泥裂解过程的形貌学特征参数研究

污泥裂解过程对应的特殊形貌学特征能够反映污泥裂解进行程度,通过全程拍摄处于400％下的污泥裂解反应进程,得到反应不同阶段的图像序列,对该图像序列借助Image Pro Plus v6．3软件进行数字化处理,可以得到描述图像特征的量化值。通过对比各种形貌特征值后发现,污泥裂解过程中,被关注的区域主体面积（用像素表示）和光密度值呈现规律性变化。随污泥裂解进行,关注的区域主体面积从最初的52000像素降至最终的35000像素,污泥图像的基本色红绿蓝（RGB）三通道光密度值从最初的160～180降至最终的70,两者的变化规律与污泥的裂解过程密切相关,并且光密度值能够更加准确地表征污泥裂解进程。通过实验数据拟合,验证了平均光密度和裂解失重率呈线性关系,并且在特定条件下和反应时间的关系满足DoseResp函数,为实现污泥裂解自动化控制提供基础。     

Monitoring Plant Phenology Using Digital Repeat Photography

Repeated observations of plant phenology have been shown to be important indicators of global change. However, capturing the exact date of key events requires daily observations during the growing season, making phenologic observations relatively labor intensive and costly to collect. One alternative to daily observations for capturing the dates of key phenologic events is repeat photography. In this study, we explored the utility of repeat digital photography for monitoring phenologic events in plants. We provide an illustration of this approach and its utility by placing observations made using repeat digital imagery in context with local meteorologic and edaphic variables. We found that repeat photography provides a reliable, consistent measurement of phenophase. In addition, digital photography offers advantages in that it can be mathematically manipulated to detect and enhance patterns; it can classify objects; and digital photographs can be archived for future analysis. In this study, an estimate of greenness and counts of individual flowers were extracted by way of mathematic algorithms from the photo time series. These metrics were interpreted using meteorologic measurements collected at the study site. We conclude that repeat photography, coupled with site-specific meteorologic measurements, could greatly enhance our understanding environmental triggers of phenologic events. In addition, the methods described could easily be adopted by citizen scientists and the general public as well as professionals in the field.     

基于灰度的生物炭pH值与N和K离子吸附研究

通过固定床石英管热解装置将稻壳、木薯秸秆及玉米秸秆在350、450、500、550、600℃进行充分热解制备生物炭,利用图像识别技术获得生物炭的RGB值（红、绿、蓝三个通道的颜色）及相应的灰度值,研究了生物炭灰度值与其水溶液中的pH值及阳离子（NH₄⁺-N及K⁺-K）吸附性能的关系.结果表明：3种生物炭的pH值随着灰度值的增加呈现“S”型增长趋势,并符合DoseResp模型,回归方程的决定系数（R²）分别为0.9766、0.9592和0.9219,残差平方和（RSS）均小于0.01;除玉米秸秆炭的K⁺-K吸附量与灰度值的关系为线性负相关外,3种生物炭的NH₄⁺-N和K⁺-K吸附量与灰度值之间满足一元高次非线性模型,R²范围在0.8595~0.9999.本研究为快速预测生物炭在水溶液中的pH值和阳离子吸附性能提供了理论基础.