Classifying environmentally significant urban land uses with satellite imagery

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.     

Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management

The Lower Rio Grande Valley (LRGV) of south Texas is an agriculturally rich area supporting intensive production of vegetables, fruits, grain sorghum, and cotton. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yields. Intensive agricultural activities in past decades might have caused potential contamination of soil, surface water, and groundwater due to leaching of pesticides in the vadose zone. In an effort to promote precision farming in citrus production, this paper aims at developing an airborne multispectral technique for identifying tree health problems in a citrus grove that can be combined with variable rate technology (VRT) for required pesticide application and environmental modeling for assessment of pollution prevention. An unsupervised linear unmixing method was applied to classify the image for the grove and quantify the symptom severity for appropriate infection control. The PRZM-3 model was used to estimate environmental impacts that contribute to nonpoint source pollution with and without the use of multispectral remote sensing and VRT. Research findings using site-specific environmental assessment clearly indicate that combination of remote sensing and VRT may result in benefit to the environment by reducing the nonpoint source pollution by 92.15%. Overall, this study demonstrates the potential of precision farming for citrus production in the nexus of industrial ecology and agricultural sustainability.     

Estimating the Variability and Confidence of Land Use and Imperviousness Relationships at a Regional Scale1

Abstract: Impervious cover is a commonly used metric to help explain or predict anthropogenic impacts on aquatic resources; often it is used as a surrogate for intensity of human impacts when evaluating effects on aquatic resources. The most common way to estimate imperviousness is based on relationships with land use. Few studies have evaluated how the relationship between impervious surface and land use varies among geographies with different levels of development and between types of imagery used to assign land use type. In this study, we assess variability in estimates of imperviousness based on two locally available land use datasets: one based on aerial imagery (2‐m resolution) and another based on satellite imagery (30‐m resolution). The ranges and variability in imperviousness within land use categories were assessed at several spatial scales, including within counties, between counties, and between watersheds. Results indicate that there was considerable variability for all developed land use types. Estimated impervious cover often varied over a range of 20‐40% points within a land use category. Furthermore, there were clear spatial patterns both between and within counties, with impervious cover for a given land use type being higher near the urban centers and lower at the margins of development. Estimates of imperviousness for 12 study watersheds indicated that variability increased with increasing watershed development, making it difficult to confidently set management or regulatory targets based on impervious cover. This study suggests that locally derived, high resolution satellite or aerial imagery should be used to estimate imperviousness when a high level of accuracy and precision is required for regulatory or management decisions. Furthermore, the error associated with impervious land use relationships should be accounted for when using impervious cover in runoff or water quality models, or when making management decisions regarding stream health.     

环境试验信息远程传输系统研究

通过对环境试验外站的环境试验数据研究和多次远程传输实验得出现阶段环境试验外站同环试中心的远程传输连接方式应该以电话线为传输载体,采用FTP协议进行远程传输和管理,同时使用加密机和防火墙来保障数据传输的安全.     

Gaseous elemental mercury concentration in atmosphere at urban and remote sites in China

An investigation of gaseous elemental mercury concentration in atmosphere was conducted at Beijing and Guangzhou urban, Yangtze Delta regional sites and China Global Atmosphere Watch Baseline Observatory (CGAWBO) in Mt. Waliguan of remote continental area of China. High temporal resolved data were obtained using automated mercury analyzer RA-915 . Results showed that the overall hourly mean Hg0 concentrations in Mt. Waliguan were 1.7± 1.1 ng/m3 in summer and 0.6±0.08 ng/m3 in winter. The concentration in Yangtze Delta regional site was 5.4±4.1 ng/m3, which was much higher than those in Waliguan continental background area and also higher than that found in North America and Europe rural areas. In Beijing urban area the overall hourly mean Hg0 concentrations were 8.3±3.6 ng/m3 in winter, 6.5±5.2 ng/m3 in spring, 4.9±3.3 ng/m3 in summer, and 6.7±3.5 ng/m3 in autumn, respectively, and the concentration was 13.5±7.1 ng/m3 in Guangzhou site. The mean concentration reached the lowest value at 14:00 and the highest at 02:00 or 20:00 in all monitoring campaigns in Beijing and Guangzhou urban areas, which contrasted with the results measured in Yangtze Delta regional site and Mt. Waliguan. The features of concentration and diurnal variation of Hg0 in Beijing and Guangzhou implied the importance of local anthropogenic sources in contributing to the high Hg0 concentration in urban areas of China. Contrary seasonal variation patterns of Hg0 concentration were found between urban and remote sites. In Beijing the highest Hg0concentration was in winter and the lowest in summer, while in Mt. Waliguan the Hg0 concentration in summer was higher than that in winter. These indicated that different processes and factors controlled Hg0 concentration in urban, regional and remote areas.     

湖南永吉高速公路建设的景观格局影响评价

利用遥感（RS）、全球定位系统（GPS）与地理信息系统技术（GIS）,对湖南省永吉高速公路沿线建设前后的景观进行分类和制图,结合景观结构分析软件Fragstats33和景观生态学方法,从斑块和景观两个层次上研究高速公路建设前后景观格局的变化。结果表明：（1）斑块层次指数中,沿线除公路用地外各景观类型的面积均有所减少,257%的土地转换为公路用地,其中旱地面积减少最多,但是公路建设前后没有改变该区域的优势斑块类型;（2）景观层次指数中,斑块数目和斑块密度的增加与最大斑块指数的减少,都表明景观异质性增加;（3）不同缓冲区分析结果表明：高速公路建设对景观格局的干扰突出表现在距公路较近的500 m缓冲区内。本研究方法在未来路网规划与环境影响评价中具有一定应用前景     

基于中低分辨率遥感影像的分类方法对比研究——以鄱阳湖水鸟栖息地遥感分类为例

选取中国鄱阳湖南矶山湿地为研究范围,通过分析候鸟在越冬期的栖息特征,构建适宜于提取候鸟栖息地的湿地分类系统。以Landsat8卫星OLI遥感影像为数据源,采用面向对象分类方法,通过多尺度分割、特征提取和决策树建立等关键步骤,实现湿地信息的快速提取;通过与传统像元法的分类结果对比,系统分析了面向对象方法在基于中低分辨率遥感影像的湿地信息提取中的有效性。研究表明:在面向对象湿地信息提取中,构建不同等级的分割尺度,在多个尺度上提取同一地物,可以更好识别复杂的湿地景观类型;相比仅依据像元光谱特征进行分类的传统像元方法,面向对象方法综合利用光谱、空间、形状和纹理等多种特征,因此可以获得更高的精度(总体分类精度达到87.64%,Kappa系数为 0.855 2);基于中低分辨率遥感影像,采用面向对象分类方法,能够获得较高精度的湿地景观分布,是一种成本较低且行之有效的技术手段。     

基于遥感的上海市湿地资源与生态服务价值研究

基于遥感开展城市湿地资源与生态服务价值研究是当前生态环境研究的热点问题之一。利用1987年、2000年和2007年的Landsat遥感影像,利用遥感和地理空间分析方法,结合野外调查及研究区相关资料,监测了1987~2007年上海市湿地资源的变动情况,并借助生态系统服务价值理论,估算研究区1987~2007年湿地资源的生态服务价值变化。结果表明:(1)1987~2007年间上海市湿地资源呈现不断退化的趋势,特别是2000年后退化趋势明显,主要表现在稻田、河流、库塘、滩涂等湿地面积的显著减少;(2)1987~2007年上海市湿地生态服务总价值呈下降趋势,其中河流、库塘、稻田的生态服务价值减少,滩涂、湖泊的生态服务价值增加。上海湿地资源与生态服务价值的变化主要是城市化快速发展导致的。以上研究结果,可为政府城市发展中对湿地资源的保护、开发和利用提供依据。     

川西高原积雪稳定性分布格局及其驱动因子分析

在气候变暖的背景下,川西高原积雪出现剧烈变化,对地区水循环过程、生态系统以及社会经济带来严重影响。基于MODIS积雪遥感数据以及环境因子数据,通过构建稳定度指标及最大熵模型探讨川西高原不同稳定性积雪的空间分布格局及其驱动因子,并对不同稳定性积雪的适宜分布区进行分析,结果表明：（1）川西高原大多数地区的积雪属于高度不稳定性积雪,其他稳定性积雪在川西高原分布面积较小;（2）川西高原积雪在海拔越高的地方稳定性越好;（3）不同稳定性积雪分布格局的影响因素存在差异,海拔和降水是影响稳定性积雪分布格局的主要因素。     

Comparing wildlife habitat suitability models based on expert opinion with camera trap detections

Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.