应用MODIS数据估算草地生物量

利用新一代EOS/MODIS卫星遥感数据,针对MODIS的应用特点,借鉴国内外基于遥感手段监测植被的方法以及植被指数的研究进展.以天山北坡乌鲁木齐南郊的草地为研究区,通过野外实地采样得到与MODIS影像资料时相一致的草地地上生物量数据.并利用ENVI软件,提取典型区各样点的植被指数,分析遥感植被指数与植被生物量的相关关系,从而建立植被指数在不同季节草甸和草原的生物量估测模型.     

Use of airborne multispectral imagery to discriminate and map weed infestations in a citrus orchard

Reliable information on weed abundance and distribution within fields is essential for weed management in agricultural systems. Such information is necessary to adopt localized and variable rates of herbicide spraying, thus reducing chemical waste, crop damage, and environmental pollution. This paper examined the potential of airborne multispectral imagery to discriminate and map weed infestations in an experimental citrus orchard in Japan. Using an airborne digital sensor, multispectral imagery was acquired over the study site on 10 April 2003. The obtained reflectance imagery was analyzed using an image object-based approach in eCognition. After creating image objects on the image, the spectral information for weeds and citrus, represented by corresponding selected sample image objects, was extracted. Significant differences in the spectral characteristics between weeds and citrus were observed in each of the red, green, and blue wavebands. The simple average values of these wavebands were used to classify image objects with the nearest neighbor algorithm. Maps were generated with different classes or levels of class groups. A subsequent accuracy assessment demonstrated that the weeds were successfully discriminated from other image objects with a classification accuracy of 99.07%. Therefore, maps generated based on the classification result could provide valuable information for developing a site-specific weed management program for the study orchard.     

A method for mapping the distribution of willow at a catchment scale using bi-seasonal SPOT5 imagery

This study showed that seasonal imagery acquired at specific stages of phenology can be used to improve the mapping accuracy of invasive willow at a catchment scale. SPOT5 XI (10 m) satellite imagery was acquired for early autumn and winter to represent the phenological stages of leaf cover and leaf fall respectively. Four classification regimes were evaluated using single‐ and bi‐seasonal composite imagery to determine the most accurate method. Significant spectral noise was found in willow populations, especially in the winter image, due to the effects of undergrowth exposure, shadowing, topography and boundary‐mixed pixels. Two noise reduction techniques were applied to the bi‐seasonal composite image to improve the classification results. The noise‐reduced bi‐seasonal composite image was classified using the spectral angle mapper (SAM) algorithm before importation into a geographical information system. Aerial photography was used to reduce the errors of commission associated with misclassification of pastures. The class accuracy achieved for willow using the method described in this study was 77.5% (Kappa =0.87). The high cost of eradicating willow means that managers must establish priorities for control; this technique can provide a powerful tool for prioritizing control programmes and for monitoring results at a catchment scale.     

准噶尔盆地西南缘人工绿洲演变初探

本文以1989年和2000年TM影像为基础,结合部分统计资料,分析了准噶尔盆地西南缘沙湾-石河子-玛纳斯人工绿洲近20年的变化特点。分析结果表明:该研究区人工绿洲面积增加显著,由1989的6077.62km2增至2000年的6995.02km2,且主要增长期为1995年以后,1998-2002年增长尤为明显;绿洲内部存在一定程度的弃荒现象,1989-2000年间有365.29km2农用地被荒弃;绿洲的增长以外延式增长为主,开发原有绿洲内部空地为辅;同时,北部莫索湾绿洲土地盐碱化现象明显。     

Using remote sensing to predict outbreaks of Oestrus ovis in Namibia

The Directorate of Veterinary Services of the Ministry of Agriculture, Water and Rural Development of Namibia issues warnings to farmers in the south of the country about the likelihood of infestation of small-stock by the nasal bot fly, Oestrus ovis. Farmers can then treat their stock at the most appropriate time. The O. ovis puparia develop at shallow depths in the soil and the timing of emergence is directly dependent on climatic conditions, specifically the number of degree-days above a particular threshold soil temperature. Based on temperature measurements from only a few stations scattered throughout the country, the veterinary department warnings lack precision in space and time. This paper presents an attempt to support the programme of warnings with accumulated temperature information from Meteosat satellite images, in order to strengthen predictions of the time of emergence in specific places, and to improve the precision and reliability of warnings given to farmers.     

基于landsat卫星影像的水库水体总磷质量浓度反演研究

以清河水库为研究区域,利用Landsat8卫星OLI数据及实地观测数据,建立了适于清河水库水体总磷质量浓度的最小二乘支持向量机(LS-SVM)遥感反演模型,并对清河水库总磷量进行了反演分析。结果表明,LS-SVM模型的平均相对误差为6.06%,相比于单波段线性回归反演模型及波段组合线性回归模型,平均误差分别降低了20.77%、12.53%,显著提高了清河水库水体总磷质量浓度反演的模型精度,达到遥感反演预测精度要求;利用LSSVM反演模型对清河水库总磷量反演显示,水体中总磷质量浓度主要集中在0.04~0.08 mg/L,水库水体总磷质量浓度总体偏高。     

变量筛选方法对郁闭度遥感估测模型的影响比较

比较基于偏最小二乘回归的Bootstrap方法与传统的平均残差平方和(RMSq)准则所选变量建立模型的精度差别.结果表明:Bootstrap方法是一种更优秀的变量筛选方法,比RMSq方法精度提高约5%;而且它不受变量多带来的运算困难的限制,更便于实际应用.     

Combined use of optical and radar satellite data for the detection of tillage and irrigation operations: Case study in Central Morocco

The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season.The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations.The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.     

负载敏感技术在甘蔗联合收割机上的应用

甘蔗联合收割机由于执行元件的复杂性及液压系统负载的多变性,在作业过程中造成了大量的液压能损失现象.为改善收割机的节能性,在对负载敏感系统的工作原理进行分析的基础上首次提出了将负载敏感技术应用于甘蔗联合收割机的节能观点,并为其负载敏感系统匹配了相关参数.基于AMESim平台的静、动态仿真结果表明,在系统压力达到调压阀设定压力之前,系统的流量仅取决于流量阀的开口而与负载无关,负载敏感阀将根据流量阀的开口自动调节变量泵的排量.在系统压力达到调压阀设定压力之后,系统压力仅取决于调压阀的设定值,而与负载无关,此时负载敏感阀将自动调节变量泵的排量使其恰好与负载的需要相适应,控制过程的压力损失小于1 MPa,从而大大减小了甘蔗联合收割机的液压能损失.     

基于EnKF-3DVar模型的海淀区地表温度模拟

以城市化程度较深的北京市海淀区为研究区,基于2005年、2010年和2015年的遥感影像数据,利用基于影像(IB)的算法反演城市地表温度空间分布。将数据同化算法EnKF-3DVar与CA/Markov模型集成,将海淀区的多年平均臭氧浓度空间分布数据同化进行城市地表温度的模拟预测。结果表明海淀区的城市地表温度10年间呈现先下降后上升的趋势,但总体呈现下降趋势,其中2015年的平均温度为31.139 3℃。引入EnKF-3DVar的预测模型能够显著提升模型的模拟精度,所预测的2015年的数据结果 Kappa系数达到0.821 6。在有城市公园绿地的模式下,地表温度高值区呈现缓解趋势,在无城市绿地公园的模式下,城市地表温度高值区呈现出明显的扩张趋势,最高温度达到了56.142 3℃,城市生态绿地对于城市地表温度的空间分布影响巨大,合理布局城市绿地公园意义重大。