Diagnosis of regional evaporation by remote sensing to support irrigation performance assessment

The success of water management in large irrigation schemes with composites of soil, crop, wetness and micro-meteorological conditions is difficult to quantify. Performance assessment indicators, being among others a function of evaporation, are useful tools to evaluate the actual functioning of an irrigation system. The inevitable spatial variability of evaporation in large irrigation schemes makes its determination with conventional point measurements almost impossible. A new remote sensing evaporation parameterization algorithm has been tested with high resolution Landsat Thematic Mapper data for the Eastern Nile Delta, Egypt. Although the implementation of such an algorithm requires assumptions to be made, the current case study shows that these assumptions do not hamper the estimation of actual and potential evaporation at regional scale. The actual evaporation has been used to express the uniformity of crop water use which is related to the equity of irrigation water distribution. The coefficient of variance in actual evaporation between 53 differenent irrigation districts is 10% on average. The relative evaporation was considered to determine whether the crop was adequately irrigated. The relative evaporation was more than 75% for 48 out of 53 irrigation districts. It is concluded, that improved information on actual crop growth conditions through remote sensing provides an essential insight into the planning of real-time and seasonal irrigation water deliveries.     

EMC单片机技术在粮仓库门控制系统中的应用

介绍了一种基于EMC单片机的粮仓库门自动控制系统.该系统分为红外遥控和接收两部分,其中红外遥控部分通过EM78P153控制红外无线遥控器发射指令信号,而红外接收部分通过接收模块接收到信号后由EM78P447来控制粮仓库门的开、关、停、限位和夜间自动点灯.系统结构简单,功能齐全,具有低成本、低功耗和可靠性高等特点.     

An entropy approach to spatial disaggregation of agricultural production

While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.     

基于多源数据融合的盐分遥感反演与季节差异性研究

为提高多光谱盐分遥感反演的精度,利用实测高光谱与多光谱进行数据融合,并分析了不同季节盐分遥感的差异性。以河套灌区永济灌域为研究区域,以实测光谱仪测定的土壤高光谱数据和Landsat-8 OLI多光谱数据为基础,通过光谱变换和多元逐步回归方法筛选特征波段和特征光谱指数,构建了春、秋两季土壤盐分多光谱、高光谱反演模型,并利用特征光谱指数的线性回归构建了高-多光谱数据融合反演模型。结果表明:高光谱的反射率总体比多光谱高36. 83%,春季反射率比秋季平均高23. 78%。利用模型中最优变量-特征光谱指数对多光谱模型与高光谱模型进行融合,高-多光谱融合反演模型训练集和验证集R2平均值分别为0. 651和0. 635,RMSE平均值分别为2. 44 g/kg和2. 49 g/kg,精度明显高于对应的多光谱反演模型,其中训练集、验证集的R2平均值分别提高了36. 19%和35. 64%,RMSE平均值分别降低了34. 28%和41. 72%。春季多光谱、高光谱和融合反演模型的精度均高于秋季,其中训练集R2平均值比秋季模型分别提高了6. 03%、6. 05%和4. 40%,验证集R2平均值分别提高了19. 07%、12. 21%和1. 75%。构建的高-多光谱融合模型反演灌域春秋两季平均盐分含量分别为6. 05、5. 97 g/kg,平均相对误差分别为9. 65%和10. 68%,总体上该区域春季土壤主要为重盐化土,秋季土壤主要为中盐化土。     

基于MK—SVR模型的小麦叶面积指数遥感反演

提出了运用多核支持向量回归(MK-SVR)算法构建小麦叶面积指数(LAI)遥感监测模型。以2010—2013年试验样点小麦拔节、孕穗、开花3期的实测LAI数据为基础,同步获取我国自主研发的环境减灾卫星HJ-CCD对该研究区域的影像数据,分析了各生育期小麦LAI与8种植被指数间的相关性。以显著相关的植被指数作为输入参数,使用MK-SVR算法构建了每个生育期的小麦LAI反演模型,即MK-SVR-LAI模型。为了评价模型,每期使用单一核支持向量回归(SK-SVR)、偏最小二乘(PLS)回归算法构建了SK-SVR-LAI、PLS-LAI模型。将模型估算LAI值和田间观测LAI值进行比对,以决定系数(R2)和均方根误差(RMSE)为指标评价并比较了模型。结果表明:3个生育期MK-SVR-LAI模型的RMSE值均低于参比模型,拔节期为0.293 1,孕穗期为0.466 8,开花期为0.548 6,且该模型的R2也都最高,拔节期为0.762 4,孕穗期为0.801 8,开花期为0.668 9。     

喷头综合性能测试实验台的研制及应用

本文研制的喷头综合性能测试设备采用先进的压力、流量、称重等多种参数的传感技术与计算机控制、处理技术,用于测量喷头的压力、流量、喷雾角及雾量分布特性等主要性能参数,以及喷头的组合性能参数;并可实现多参数精密同步测定及处理功能。     

基于遗传算法的遥感数字图像镶嵌研究

遥感数字图像的镶嵌处理是遥感图像处理的基本工作之一，为此介绍了一种基于遗传算法确定图像重叠区和调整图像色度，以辅助完成遥感图像的镶嵌工作的新方法。     

Reflectance-based assessment of spider mite “bio-response” to maize leaves and plant potassium content in different irrigation regimes

It is widely accepted that pest infestations elicit a change in plant physiology, which cause detectable changes in crop leaf reflectance. In this study, we test the hypothesis that crop leaf reflectance may also be used to forecast the risk of pest infestation before they actually occur. We collected reflectance data in 160 spectral bands from 405 to 907 nm from excised leaf pieces from field grown maize plants under 3 irrigation regimes. Leaf material was collected at weekly intervals in two growing seasons. The same leaf pieces were used in choice bioassays with carmine spider mites to assess attractiveness to mites (spider mite “bio-response”) across irrigation regimes. In one growing season, we also obtained nutritional element data (lipid, protein, soluble sugar, starch, lignin, Ca, P, Mg, K, S, and Cl) from whole maize plants. Principal component analysis showed that potassium content (K) was highly negatively correlated with spider mite bio-response. Relative reflectance at 740 nm showed a highly significant and positive trend across spider mite bio-response classes, and that potassium content showed a highly significant and negative trend across the same classes. Thus, we argue that relative reflectance at 740 nm may be used to predict both potassium content and risk of spider mite infestation. Based on extensive reviews, potassium leaf content is known to reduce susceptibility of crops to pests. The results presented provide encouraging support for remotely sensed risk assessment of pest infestations through reflectance-based monitoring of maize leaf attractiveness and highlight that reflectance based monitoring of crop susceptibility may be possible through careful management of macro element crop properties, such as potassium content.     

富阳市湿地资源现状分析与保护对策研究

采用遥感卫片判读和野外人工调查相结合的方法,调查得出富阳市各类湿地的面积数量和空间分布,并进一步分析湿地的成因、水源补给和受威胁状况,提出加强湿地宣传教育、提高全社会的湿地保护意识,完善地方法规、加强湿地综合管理和建立完善的湿地监测体系等相应的保护对策.     

Forest fragmentation in Loudoun County,Virginia, USA evaluated with multitemporal Landsat imagery

In order to study forest fragmentation in the Virginia, USA Piedmont, a series of Landsat images from 1973, 1987, and 1999 covering a rapidly developing area (Loudoun County) was used to classify forest from non-forest. The classified images were analyzed using a geographic information system (GIS) to determine the spatial and temporal patterns of fragmentation, and to relate these patterns to infrared radiance provided by Landsat Enhanced Thematic Mapper Plus (ETM+) band 6. The analysis was concentrated on eleven major watersheds of Loudoun County. The relationship between urbanized area per watershed and mean fragment size showed a strong negative decay form (r ²=0.757, p<0.0001). Analysis of four landscape metrics showed increasing fragmentation of forest cover, particularly from 1987 to 1999, as well as an increase in forest edge and shape complexity. Of the landscape metrics used, the perimeter-to-area (P/A) ratio showed the strongest relationship with mean radiance of forest patches. In addition, there was a negative, linear relationship between distance from major roads and band 6 radiance of forested pixels. Overall, the study shows that landscape metrics can convey meaningful information on biophysical changes associated with forest fragmentation at broad scales. These changes suggest that ambient temperature increases associated with urban sprawl may have important, long-term implications for ecophysiological processes.