运用ENVI实现SPOT-5卫星影像的RVI提取

运用ENVI软件处理长沙地区的SPOT-5影像,将全色影像和多波段影像进行融合,分析融合后的影像,再选择感兴趣区域进行影像裁剪;采用ENVI的波段运算(Band3/Band2)提取该地区比值植被指数并进行分析。结果表明:比值植被指数对植被覆盖率较高的区域有非常高的敏感度;在植被覆盖率小于50%的时候,其敏感度明显降低,在绿色植被覆盖区域的比值植被指数远大于1,在裸露地表、建筑物、水体等没有植被覆盖区域的比值植被指数则在1附近,而比值植被指数大于2的则出现在高覆盖健康绿色植被上。     

相干变化指数法在震害快速评估中的应用

合成孔径雷达(SAR)具有全天候全天时的特点,为快速展开地震救援,评估震害损失提供了重要的数据支持。本文基于汶川震中东南平原地区的ENVISATASAR影像,利用相位干涉方法处理得到相干变化指数图像,对6个评估区域的像元相干变化指数进行统计分析,以相干变化指数平均值作为区分建筑物基本完好与损毁的阈值,并与实地调查结果相比,精度基本达到70%。验证干涉相干变化指数法对震害快速评估有效的同时,也为震区提供震害救援的依据。     

齐齐哈尔市地理国情分析与表达

以齐齐哈尔市为例,利用地理国情普查数据与统计年鉴数据,构建自然地表指数、地理区位指数、生态覆被指数,对齐齐哈尔市各县、区的地理国情进行综合分析和地图表达。结果表明,齐齐哈尔市的总体条件较好,但区域差异较大,自然地表条件与地理区位条件均以中部的齐齐哈尔市辖区为优,而生态覆被条件则以北部和西部地区为优。     

雅安芦山4.20震后县级单元生态系统风险评价

区域生态风险评价是对各种生态风险及环境问题进行评价和管理的重要手段。针对雅安地震灾区特殊的自然地理及生态环境特征,选取芦山县为研究对象,采用遥感、GIS及SPSS统计分析的方法,通过风险源、风险受体、暴露和易损性分析,建立生态风险综合评价模型,划分生态风险区类型,进而提出生态风险管理对策。结果表明:1)微度和低度生态风险区集中分布在高海拔的森林及草地生态系统,该区生物多样性丰富,抗干扰能力较强,地质灾害及人类活动影响较小;2)中度和高度生态风险区具有沿农田及建设用地生态系统集聚分布的特征,该区地质灾害频繁,地壳活动性较强,生态系统抵抗灾害的能力较差。研究结果可为地震灾区防御、规避风险及安全选址提供科学依据。     

Re-conceptualizing the Anthropocene: A call for collaboration

Since it was first proposed in 2000, the concept of the Anthropocene has evolved in breadth and diversely. The concept encapsulates the new and unprecedented planetary-scale changes resulting from societal transformations and has brought to the fore the social drivers of global change. The concept has revealed tensions between generalized interpretations of humanity’s contribution to global change, and interpretations that are historically, politically and culturally situated. It motivates deep ethical questions about the politics and economics of global change, including diverse interpretations of past causes and future possibilities. As such, more than other concepts, the Anthropocene concept has brought front-and-center epistemological divides between and within the natural and social sciences, and the humanities. It has also brought new opportunities for collaboration. Here we explore the potential and challenges of the concept to encourage integrative understandings of global change and sustainability. Based on bibliometric analysis and literature review, we discuss the now wide acceptance of the term, its interpretive flexibility, the emerging narratives as well as the debates the concept has inspired. We argue that without truly collaborative and integrative research, many of the critical exchanges around the concept are likely to perpetuate fragmented research agendas and to reinforce disciplinary boundaries. This means appreciating the strengths and limitations of different knowledge domains, approaches and perspectives, with the concept of the Anthropocene serving as a bridge, which we encourage researchers and others to cross. This calls for institutional arrangements that facilitate collaborative research, training, and action, yet also depends on more robust and sustained funding for such activities. To illustrate, we briefly discuss three overarching global change problems where novel types of collaborative research could make a difference: (1) Emergent properties of socioecological systems; (2) Urbanization and resource nexus; and (3) Systemic risks and tipping points. Creative tensions around the Anthropocene concept can help the research community to move toward new conceptual syntheses and integrative action-oriented approaches that are needed to producing useful knowledge commensurable with the challenges of global change and sustainability.     

5—6月东北冷涡持续活动及强度特征

利用1960—2012年5—6月NCEP/NCAR逐日再分析资料,基于冷涡经典定义,采取客观识别方法检索东北冷涡活动过程,根据东北冷涡活动时空变化特征给出东北冷涡持续活动过程标准, 通过冷涡强度指数进行定量化分析,该指数对冷涡持续活动过程具有较好表征意义。冷涡活动强对应5月乌拉尔山阻塞高压、贝加尔湖阻塞高压和6月鄂霍次克海阻塞高压活动频繁。通过强弱指数年合成,得到6月强指数年冷涡系统较深厚,集中于对流层中高层,冷心结构明显,具有一定大气斜压特征; 高层存在冷中心,低层有冷空气活动,中高层西风带呈明显的上游分流和下游汇合特征,分汇流之间呈东北高、西南低的偶极子阻塞形势;弱指数年冷涡系统较浅薄,主要集中在对流层中低层,冷心结构不明显,不存在阻塞形势。     

内蒙古河套灌区春玉米作物系数试验研究

作物系数曲线是估算作物生长季耗水量变化的重要参数。基于2013年4—9月内蒙古巴彦淖尔市临河区田间水分试验和1994—2013年气象站观测资料,利用水量平衡法反求春玉米作物系数,分析生长季内的变化规律, 建立动态模拟方程,并与联合国粮农组织 (FAO) 分段直线法结果进行比较, 提出胁迫条件下作物系数的叶面积修正方法。结果表明:玉米作物系数随发育进程可用三项式曲线描述,变化趋势与产量水平无关, 但随产量增高而变幅增大;以出苗后相对积温为时间变量建立模拟方程效果较好,决定系数 (R2) 均在0.92以上;模拟计算出各站点最大 (1.30~1.48) 和平均 (0.831~0.919) 作物系数,与FAO分段直线法计算的典型值和区间值基本一致,生长中期平均相对误差为3.4%~7.2%;提出利用相对叶面积指数修正作物系数的计算方法;通过2014年实例检验,土壤水分模拟值与实测值的平均相对误差为6.3%,相对误差小于15%的占95.8%。     

风云卫星数据服务评价指标的验证分析

简述了目前我国风云卫星数据服务以及气象服务效益评估业务的现状,利用层次分析法提出风云卫星数据服务评价的6个1级指标和19个2级指标。设计了风云卫星数据服务评测量表,并采用分半信度、因子分析等方法对量表作信度和效度分析,结果表明所设计的评测量表具有良好的信度和效度,确定了包括服务平台易用性、服务流程规范性、服务响应及时性、服务内容完整性、服务工作主动性、服务宣传广泛性等6个方面的风云卫星数据服务评价指标。     

Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data

A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAI_L) alone (R² = 0.77 and RMSE = 231 g m⁻²). Assimilation of GLAI derived from the fusion dataset (GLAI_F) resulted in a R² of 0.71 and RMSE of 193 g m⁻² while assimilating the combination of GLAI_L and GLAI_F led to further improvements (R² = 0.76 and RMSE = 176 g m⁻²). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution remote sensing data acquisitions is limited.     

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R² = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.