Agricultural irrigation is a primary user for freshwater withdrawal. Irrigation plays an important role in crop production, as it provides the benefit of reducing the effects of prolonged dryness and erratic precipita...Agricultural irrigation is a primary user for freshwater withdrawal. Irrigation plays an important role in crop production, as it provides the benefit of reducing the effects of prolonged dryness and erratic precipitation. Center pivot irrigation system is the most common irrigation system in agriculture. As the center pivot irrigation system ages, the system could develop a leaking joint, clogged sprinklers, and physical damage. This can cause areas of non-uniformity that can lead to under- or over-irrigated in some areas of the land, resulting in excess energy use and cost, wasting resources, and environmental impacts. Thus, it is important to evaluate the performance of a center pivot irrigation system regularly to maximize return on investments and minimize wasting resources. This study focuses on evaluating the impacts and benefits of improved center pivot irrigation distribution uniformity by performing distribution uniformity evaluations pre- and post-retrofit. This study also focused on demonstrating an unmanned aerial vehicle (UAV) to assess the performance of the center pivot irrigation system in two irrigated farmlands. The Coefficient of Uniformity (CU), Distribution Uniformity (DU), and Scheduling Coefficient (SC) were calculated based on the catch can test data. The values were utilized to evaluate water and energy savings from the improved coefficients. The team has found that replacing sprinkler packages increased the CU from 78 to 89 and the DU from 77 to 82, and reduced the SC from 1.3 to 1.2 in Field A. In Field B, replacing sprinkler packages increased the CU from 73 to 91 and the DU from 62 to 84 and reduced the SC from 1.6 to 1.2. The estimated water savings in Field A due to the reduced scheduling coefficient was approximately 151,000 liters/hectare/year, with consideration of the corn and soybean rotation field in Michigan. The estimated water savings in Field B was 608,000 liters/hectare/year. The data from this demonstration study showed the value of distribution uniformity evaluation and retrofit of irrigation systems. This information will encourage farmers and agricultural industries to consider performing more distribution uniformity evaluations, ultimately improving irrigation water use efficiency and supporting sustainable water management in agriculture.展开更多
设计图像块特征表示是计算机视觉领域内的基本研究内容,优秀的图像块特征表示能够有效地提高图像分类、对象识别等相关算法的性能.SIFT(scale-invariant feature transform)和HOG(histogram of oriented gradient)是人为设计图像块特征...设计图像块特征表示是计算机视觉领域内的基本研究内容,优秀的图像块特征表示能够有效地提高图像分类、对象识别等相关算法的性能.SIFT(scale-invariant feature transform)和HOG(histogram of oriented gradient)是人为设计图像块特征表示的优秀代表,然而,人为设计图像块特征间的差异往往不能足够理想地反映图像块间的相似性.核描述子(kernel descriptor,简称KD)方法提供了一种新的方式生成图像块特征,在图像块间匹配核函数基础上,应用核主成分分析(kernel principal component analysis,简称KPCA)方法进行特征表示,且在图像分类应用上获得不错的性能.但是,该方法需要利用所有联合基向量去生成核描述子特征,导致算法时间复杂度较高.为了解决这个问题,提出了一种算法生成图像块特征表示,称为有效图像块描述子(efficient patch-level descriptor,简称EPLd).算法建立在不完整Cholesky分解基础上,自动选择少量的标志性图像块以提高算法效率,且利用MMD(maximum mean discrepancy)距离计算图像间的相似性.实验结果表明,该算法在图像/场景分类应用中获得了优秀的性能.展开更多
文摘Agricultural irrigation is a primary user for freshwater withdrawal. Irrigation plays an important role in crop production, as it provides the benefit of reducing the effects of prolonged dryness and erratic precipitation. Center pivot irrigation system is the most common irrigation system in agriculture. As the center pivot irrigation system ages, the system could develop a leaking joint, clogged sprinklers, and physical damage. This can cause areas of non-uniformity that can lead to under- or over-irrigated in some areas of the land, resulting in excess energy use and cost, wasting resources, and environmental impacts. Thus, it is important to evaluate the performance of a center pivot irrigation system regularly to maximize return on investments and minimize wasting resources. This study focuses on evaluating the impacts and benefits of improved center pivot irrigation distribution uniformity by performing distribution uniformity evaluations pre- and post-retrofit. This study also focused on demonstrating an unmanned aerial vehicle (UAV) to assess the performance of the center pivot irrigation system in two irrigated farmlands. The Coefficient of Uniformity (CU), Distribution Uniformity (DU), and Scheduling Coefficient (SC) were calculated based on the catch can test data. The values were utilized to evaluate water and energy savings from the improved coefficients. The team has found that replacing sprinkler packages increased the CU from 78 to 89 and the DU from 77 to 82, and reduced the SC from 1.3 to 1.2 in Field A. In Field B, replacing sprinkler packages increased the CU from 73 to 91 and the DU from 62 to 84 and reduced the SC from 1.6 to 1.2. The estimated water savings in Field A due to the reduced scheduling coefficient was approximately 151,000 liters/hectare/year, with consideration of the corn and soybean rotation field in Michigan. The estimated water savings in Field B was 608,000 liters/hectare/year. The data from this demonstration study showed the value of distribution uniformity evaluation and retrofit of irrigation systems. This information will encourage farmers and agricultural industries to consider performing more distribution uniformity evaluations, ultimately improving irrigation water use efficiency and supporting sustainable water management in agriculture.
文摘设计图像块特征表示是计算机视觉领域内的基本研究内容,优秀的图像块特征表示能够有效地提高图像分类、对象识别等相关算法的性能.SIFT(scale-invariant feature transform)和HOG(histogram of oriented gradient)是人为设计图像块特征表示的优秀代表,然而,人为设计图像块特征间的差异往往不能足够理想地反映图像块间的相似性.核描述子(kernel descriptor,简称KD)方法提供了一种新的方式生成图像块特征,在图像块间匹配核函数基础上,应用核主成分分析(kernel principal component analysis,简称KPCA)方法进行特征表示,且在图像分类应用上获得不错的性能.但是,该方法需要利用所有联合基向量去生成核描述子特征,导致算法时间复杂度较高.为了解决这个问题,提出了一种算法生成图像块特征表示,称为有效图像块描述子(efficient patch-level descriptor,简称EPLd).算法建立在不完整Cholesky分解基础上,自动选择少量的标志性图像块以提高算法效率,且利用MMD(maximum mean discrepancy)距离计算图像间的相似性.实验结果表明,该算法在图像/场景分类应用中获得了优秀的性能.
