Improved Methods for Monitoring Vegetation Structure and Change for Input to Landscape-Scale Ecosystem Process Models

监测植被结构和景观尺度生态系统过程模型输入变化的改进方法

• 批准号: 8908941
• 负责人: Janet Franklin
• 金额: $ 4.09万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-07-01 至 1990-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8908941&HistoricalAwards=false
• 关键词: Improved; Methods; Monitoring; Vegetation; Structure

Growing awareness of the accelerating pace of global environmental change has heightened the need for effective means to monitor and analyze changes in natural conditions throughout the world. Satellite imagery and other forms of remote sensing have greatly increased the amount of raw data available for tracing changes in natural conditions, but techniques for converting that data in useful information necessary to evaluate changes in natural patterns and processes have been slower to develop. This project will improve and refine methods for measuring changes in many of the attributes of vegetation in arid and semiarid regions. By evaluating the reflectance properties and locational patterns of different types of vegetation, the investigator should be able to develop standard rules that will enable remotely sensed images across larger areas to be used to more accurately map vegetational patterns. By analyzing images of the same area taken over time, changes in vegetational patterns can be mapped and more direct analyses of the processes of vegetational change can be undertaken. This project will be undertaken by the collaborator in collaboration with ecologists at the Jornada Long-Term Ecological Reserve in New Mexico. This research will be beneficial from both methodological and substantive standpoints. The analysis of properties that more reliably identify vegetation will be of value to all scholars studying vegetational patterns. By using this information to improve and test models of ecosystem change, this research also will benefit those seeking to increase understandings of the roles of a wide range of factors in ecological change.

人们日益认识到全球环境变化的步伐正在加快，因此更加需要有效的手段来监测和分析世界各地自然条件的变化。卫星图像和其他形式的遥感大大增加了可用于追踪自然条件变化的原始数据量，但将这些数据转换为评估自然模式和过程变化所需的有用信息的技术开发较慢。该项目将改进和改进衡量干旱和半干旱地区植被许多属性变化的方法。通过评估不同类型植被的反射特性和位置模式，调查者应该能够制定标准规则，使更大范围的遥感图像能够用于更准确地绘制植被模式图。通过分析同一地区随时间拍摄的图像，可以绘制植被模式变化的地图，并可以对植被变化过程进行更直接的分析。该项目将由合作者与新墨西哥州乔尔纳达长期生态保护区的生态学家合作进行。这项研究将从方法论和实质性的角度都是有益的。对更可靠地识别植被的属性的分析将对所有研究植被格局的学者都有价值。通过利用这些信息来改进和测试生态系统变化的模型，这项研究也将有利于那些寻求增加对各种因素在生态变化中的作用的理解的人。