Identification and mapping of submerged plants in a shallow lake using Quickbird satellite data

Turkey is a country rich in lakes and wetlands--monitoring of all these will require advances in technology such as remote sensing. In this study, the aquatic plants of the large and shallow Lake Mogan, located in Central Anatolia were identified and mapped using high spatial resolution Quickbird imagery. As Lake Mogan is an important bird area the assessment of submerged plant species is of great value for ecosystem conservation and management. Quickbird multispectral image acquired on August 6, 2005 was geometrically corrected and a water mask was used based on strong absorption of Near Infrared (NIR) wavelengths by calm, clear and deep water. The water mask was applied using band reflectance values for a specific pixel satisfying the conditions of band decreasing property (Green>Red>NIR) and NIR相似文献   

Application of Ecological Classification and Predictive Vegetation Modeling to Broad-Level Assessments of Ecosystem Health

The Little Missouri National Grasslands (LMNG) of western North Dakota support the largest permitted cattle grazing use within all lands administered by the USDA, Forest Service, as well as critical habitat for many wildlife species. This fact, coupled with the need to revise current planning direction for range allotments of the LMNG, necessitated that a broad-level characterization of ecosystem integrity and resource conditions be conducted across all lands within the study area (approximately 800,000 hectares) in a rapid and cost-effective manner. The approach taken in this study was based on ecological classifications, which effectively utilized existing field plot data collected for a variety of previous inventory objectives, and their continuous spatial projection across the LMNG by maps of both existing and potential vegetation. These two map themes represent current and reference conditions (existing vs. potential vegetation); their intersection allowed us to assign various ecological status ratings (i.e., ecosystem integrity and resource condition) based on the degree of departure between current and reference conditions. In this paper, we present a brief review of methodologies used in the development of ecological classifications, and also illustrate their application to assessments of rangeland health through selected maps of ecological status ratings for the LMNG.     

Classification and mapping forest sites using geographic information system (GIS): a case study in Artvin Province

The productivity of forest sites has been indirectly determined with solo wood production objective in forest management. Forest site productivity should, however, be determined directly in order to implement ecosystem based multipurpose forest management philosophy. This article tackles the problem in distinguishing and mapping forest sites using both direct method and indirect method in Genya Mountain located in central of Artvin State Forest Enterprise. About 112 sample plots were designed and distributed over the area. In each sample plot, soil samples were collected and the classical timber inventory measurements were taken. According to direct method, Soil Moisture Regime (SMR) method is preferred due to a water deficiency in the study area. Water holding capacity was used as an essential criterion for the classification of the forest site. Forest site classifications were assigned regarding the physiographic factors such as landform, aspect, and slope. Five different forest sites classes; dry, moderate fresh, fresh, humid and hygric were determined. According to direct method, the guiding curve was used to generate anamorphic site index (SI) equations and three site index classes; good (SI=I–II), medium (SI=III) and low (SI=IV–V) were determined. Some important differences between the methods were realized. The forest sites determined with site index estimation method indicate that site index I and II is 505.99 ha, III 1095.79 ha and IV and V 992.95 ha, whereas forest sites determined with direct method related to dry site of 937.58 ha, moderate fresh site of 931.90 ha, fresh site of 1,797.71 ha, humid site of 80.48 ha and hygric site of 356.55 ha. The forest site maps of both methods were created using GIS functions. The forest sites of open and degraded areas should be determined according to direct method.     

鞍山市化学事故辅助决策系统的开发

以科学实用为出发点,对鞍山市化学事故辅助决策系统的建立和开发进行了研究。分析讨论了建立该辅助决策系统软件的背景及意义;根据GB6944—2005《危险货物品名表》,应用Access2003数据库和VB6.0语言进行编程,构建危险化学品资料查询数据库,实现模糊查询和精确查询功能;通过分析、比较扩散模型中应用较广泛的高斯模型、SLAB模型、ADMS模型,结合鞍山市当地的实际气象数据,确定ADMS模型为该软件所用扩散模型,并根据ADMS模型和毒负荷法建立危险区域划分标准;根据鞍山市的实际情况,在灵图2006和消防水源电子地图的共同支持下,实现救援车辆电子地图导航和现场实时水源显示功能。     

基于统计和信度理论的火灾保险费率分级方法

通过对建筑火灾保险费率厘定的调查、研究,确定了关于建筑物火灾保险费率的主要影响因素;详细介绍基于统计理论和信度理论的火灾保险费率分级方法,并以美国马萨诸塞州东海岸地区为例,给出其实际的应用算例;结合实际中的问题,分析了基于统计理论和信度理论的火灾保险费率分级方法的优缺点,为我国建筑火灾保险费率厘定的研究提供了依据和参考。     

Modeling Residential Lawn Fertilization Practices: Integrating High Resolution Remote Sensing with Socioeconomic Data

This article investigates how remotely sensed lawn characteristics, such as parcel lawn area and parcel lawn greenness, combined with household characteristics, can be used to predict household lawn fertilization practices on private residential lands. This study involves two watersheds, Glyndon and Baisman’s Run, in Baltimore County, Maryland, USA. Parcel lawn area and lawn greenness were derived from high-resolution aerial imagery using an object-oriented classification approach. Four indicators of household characteristics, including lot size, square footage of the house, housing value, and housing age were obtained from a property database. Residential lawn care survey data combined with remotely sensed parcel lawn area and greenness data were used to estimate two measures of household lawn fertilization practices, household annual fertilizer nitrogen application amount (N_yr) and household annual fertilizer nitrogen application rate (N_ha_yr). Using multiple regression with multi-model inferential procedures, we found that a combination of parcel lawn area and parcel lawn greenness best predicts N_yr, whereas a combination of parcel lawn greenness and lot size best predicts variation in N_ha_yr. Our analyses show that household fertilization practices can be effectively predicted by remotely sensed lawn indices and household characteristics. This has significant implications for urban watershed managers and modelers.     

When Has an Abandoned Field Become a Semi-Natural Grassland or Heathland?

This study presents a meta-analysis of a collective dataset describing the succession from abandoned fields to semi-natural grassland and heathland vegetation over the past century. The study objectives were to develop a method for statistical discrimination between abandoned fields and semi-natural habitats and to analyze the probability that an abandoned field had developed into a semi-natural habitat. A statistical classification model was developed, based on lists of vascular plants from 2059 plots from Danish semi-natural grasslands and heathlands, and abandoned fields of varying age. This model was shown to discriminate effectively between abandoned fields and semi-natural habitats, and it was found to be potentially useful for the detection of abandoned fields approaching semi-natural vegetation. We suggest that the model may help clarify restoration targets and assess biological condition in formerly cultivated areas. Statistical modeling revealed that succession age, period of abandonment and succession trajectory had significant effects on the probability that abandoned fields reached the semi-natural phase. Our study indicates that restoration projects targeting grassland and heathland should take local species pools and soil fertility into account. Nomenclature: Species names follow Flora Europaea (Tutin and others 1964–1993).     

生态文明对图书管理的影响及对策措施

生态文明是社会主义文明的组成部分之一,是社会文明发展的新阶段.生态文明使有关图书的重要性更加突出,数量激增,涉及的范围更加广泛,类型更加复杂多样.因此,图书管理应以生态文明为指导,为生态文明建设服务,采取高度重视,调整、增加分类,开设专柜、专室,及时向读者提供有关信息等措施.     

A Gis‐Based Approach to Watershed Classification for Nebraska Reservoirs1

Abstract: The U.S. Environmental Protection Agency is charged with establishing standards and criteria for assessing lake water quality. It is, however, increasingly evident that a single set of national water quality standards that do not take into account regional hydrogeologic and ecological differences will not be viable as lakes clearly have different inherent capacities to meet such standards. We demonstrate a GIS‐based watershed classification strategy for identifying groups of Nebraska reservoirs that have similar potential capacity to attain a certain level of water quality standard. A preliminary cluster analysis of 78 reservoirs was performed to determine the potential number of Nebraska reservoir groups. Subsequently, a Classification Trees method was used to refine number of classes, describe the structure of reservoir watershed classes, and to develop a predictive model that relates watershed conditions to reservoir classes. Results suggest that Nebraska reservoirs can be represented by nine classes and that soil organic matter content in the watershed is the most important single variable for segregating the reservoirs. The cross‐validation prediction error rate of the Classification Tree model was 26.3%. Because all geospatial data used in this work are available nationally, the method could be adopted throughout the U.S. Hence, this GIS‐based watershed classification approach could provide water resources managers an effective decision‐support tool in managing reservoir water quality.     

Adequacy of Visually Classified Particle Count Statistics From Regional Stream Habitat Surveys1

Abstract: Streamlined sampling procedures must be used to achieve a sufficient sample size with limited resources in studies undertaken to evaluate habitat status and potential management‐related habitat degradation at a regional scale. At the same time, these sampling procedures must achieve sufficient precision to answer science and policy‐relevant questions with an acceptable and statistically quantifiable level of uncertainty. In this paper, we examine precision and sources of error in streambed substrate characterization using data from the Environmental Monitoring and Assessment Program (EMAP) of the U.S. Environmental Protection Agency, which uses a modified “pebble count” method in which particle sizes are visually estimated rather than measured. While the coarse (2?) size classes used in EMAP have little effect on the precision of estimated geometric mean (D_gm) or median (D₅₀) particle diameter, variable classification bias among observers can contribute as much as 0.3?, or about 15‐20%, to the root‐mean‐square error (RMSE) of D_gm or D₅₀ estimates. D_gm and D₅₀ estimates based on EMAP data are nearly equal when fine sediments (<2 mm) are excluded, but otherwise can differ by up to a factor of 2 or more, with D_gm < D₅₀ for gravel‐bed streams. The RMSE of reach‐scale particle size estimates based on visually classified particle count data from EMAP surveys, including variability associated with reoccupying unmarked sample reaches during revisits, is up to five to seven times higher than that reported for traditional measured pebble counts by multiple observers at a plot scale. Nonetheless, a variance partitioning analysis shows that the ratio of among site to revisit variance for several EMAP substrate metrics exceeds 8 for many potential regions of interest, suggesting that the data have adequate precision to be useful in regional assessments of channel morphology, habitat quality, or ecological condition.