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摘 要：为寻求一系列能敏感、清晰地反映生态系统站木特征及生态环境变化趋势的定量遥感参数，构建可业务化的定量生态环境质量监测指标体系，以在时究尺度上对特定区域范围内生态系统和生态系统组合体的类型、结构和功能及其组合要素进行系统地测定，研究围绕生态系统和景观生态学等理念，从区域植被组成状况、植被结构状况和植被功能状况3个方面入手。在多源、多尺度立体监测数据生态环境参数提取研究基础上，重点研究与生产生态环境质量监测与评价的相关参数产品。2014年的主要研究工作为，在基于物候信息和数据拟合算法的支持下，进行了多源遥感数据农作物精细分类、植被遥感决策树分类等方法模型研究；根据NDVI随观测角度的变化规律构造出新型多角度归一化植被指数MNDVI，用以解决LAI反演中过饱和问题，并将实测和估算LAI进行线性回归来进行精度验证。尝试通过结构方程模型建立地表生物量（或LAI）及土壤有机碳与土壤呼吸的关系，实现空间上大面积的土壤有机碳含量估算，并进行土壤呼吸情况的空间分布估计。卫星遥感已被广泛用于大气环境监测与气候变化研究之中，其大范围、动态连续的观测能力对地面观测形成了有益的补充。该研究基于我国大气环境监测的实际需要，基于卫星观测与大气模式、气象数据相结合的思路，初步实现了对流层HCHO柱浓度反演、近地面N02浓度估算，以及基于常规期限观测的气溶胶吸湿增长特性近似等方法的研究，为进一步满足实际的业务监测需要，提高遥感反演精度提供支撑。地基大气痕量气体与气溶胶遥感仪器主要用于获取大气痕量气体柱浓度和垂直分布廓线以及气溶胶光学厚度和消光系数廓线，为星载、机载数据验证提供技术手段。该年度完成了地基大气痕量气体与气溶胶紫外可见光谱遥感探测系统的总体设计、各项关键分系统的设计和加工，包括二维扫描和望远镜单元、光谱探测单元、恒温控制单元等，开展了紫外可见多组分气体浓度反演算法研究等。并进行了实验室测试及实验工作，测试了系统关键部件和验收数据处理算法。
关键词：中文生态环境遥感、大气环境遥感、地基大气遥感、示范应用、系统开发集成
Abstract：This study started from regional vegetation composition status， vegetation structural status and vegetation functional status surrounding ecosystem and landscape ecology concepts. Based on the study of ecological parameter extraction from multi-source， multi-scale and multi-dimension monitoring data， this study focus on parameter productions concerning ecological environment quality monitoring and evaluation. The main work in the year 2014 was， the study of multi-source remote sensing data fine crop classification， decision tree classification of remote sensing of vegetation and other methods and models with the support of phenological information and data fitting algorithm. According to the observed NDVI variation with angle， constructed a new multi-angle normalized difference vegetation index MNDVI， to solve the problem of LAI oversaturated retrieval， and make accuracy verification of measured and estimated LAI. Attempt to establish the relationship between above ground biomass （or LAI） and soil organic carbon by building structural equation model， to estimate soil organic carbon content in a large spatial area， and to estimate spatial distribution of soil respiration. Satellite remote sensing has been widely used in atmospheric environment monitoring and climate change researches. This study developed initial method of estimating ground-level NO2 using satellite observations and atmospheric model simulations. Also， a new approach of approximating hygroscopic growth behaviors of particles based on meteorological measurements， such as VIS and RH， has been established and validated initially.Ground-based trace gases and aerosol telemetry instrument is used to achieve the column density of trace gases and vertical profile， along with the aerosol optical density and extinction coefficient profile. The main progress of this year is mainly focused on the overall design of the ground-based trace gases and aerosol telemetry instrument applied in ultraviolet visible wavelength； design and manufacture of the key subsystem， including two-dimensional scanning telescope， spectrum detection unit， constant temperature control unit； and research of UV visible multi component gas concentration retrieval algorithm. Laboratory test and the experimental work have been carried out， the key parts of the system and data processing algorithm has been tested.
Key Words：Ecological Environment Remote Sensing；Atmospheric Environment Remote Sensing；Ground-based Atmospheric Remote Sensing， Demonstrative Application；System Development and Integration
阅读全文链接（需实名注册）：http：//www.nstrs.cn/xiangxiBG.aspx？id=68346&flag=1
关键词：中文生态环境遥感、大气环境遥感、地基大气遥感、示范应用、系统开发集成
Abstract：This study started from regional vegetation composition status， vegetation structural status and vegetation functional status surrounding ecosystem and landscape ecology concepts. Based on the study of ecological parameter extraction from multi-source， multi-scale and multi-dimension monitoring data， this study focus on parameter productions concerning ecological environment quality monitoring and evaluation. The main work in the year 2014 was， the study of multi-source remote sensing data fine crop classification， decision tree classification of remote sensing of vegetation and other methods and models with the support of phenological information and data fitting algorithm. According to the observed NDVI variation with angle， constructed a new multi-angle normalized difference vegetation index MNDVI， to solve the problem of LAI oversaturated retrieval， and make accuracy verification of measured and estimated LAI. Attempt to establish the relationship between above ground biomass （or LAI） and soil organic carbon by building structural equation model， to estimate soil organic carbon content in a large spatial area， and to estimate spatial distribution of soil respiration. Satellite remote sensing has been widely used in atmospheric environment monitoring and climate change researches. This study developed initial method of estimating ground-level NO2 using satellite observations and atmospheric model simulations. Also， a new approach of approximating hygroscopic growth behaviors of particles based on meteorological measurements， such as VIS and RH， has been established and validated initially.Ground-based trace gases and aerosol telemetry instrument is used to achieve the column density of trace gases and vertical profile， along with the aerosol optical density and extinction coefficient profile. The main progress of this year is mainly focused on the overall design of the ground-based trace gases and aerosol telemetry instrument applied in ultraviolet visible wavelength； design and manufacture of the key subsystem， including two-dimensional scanning telescope， spectrum detection unit， constant temperature control unit； and research of UV visible multi component gas concentration retrieval algorithm. Laboratory test and the experimental work have been carried out， the key parts of the system and data processing algorithm has been tested.
Key Words：Ecological Environment Remote Sensing；Atmospheric Environment Remote Sensing；Ground-based Atmospheric Remote Sensing， Demonstrative Application；System Development and Integration
阅读全文链接（需实名注册）：http：//www.nstrs.cn/xiangxiBG.aspx？id=68346&flag=1