Predicting biomass dynamics at the national extent from digital aerial photogrammetry

The demand for precise mapping and monitoring of forest resources, such as above ground biomass (AGB), has increased rapidly. National accounting and monitoring of AGB requires regularly updated information based on consistent methods. While remote sensing technologies such as airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have been shown to deliver the necessary 3D spatial data for AGB mapping, the capacity of repeat acquisition, remotely sensed, vegetation structure data for AGB monitoring has received less attention. Here, we use vegetation height models (VHMs) derived from repeat acquisition DAP data (with ALS terrain correction) to map and monitor woody AGB dynamics across Switzerland over 35 years (1983-2017 inclusive), using a linear least-squares regression approach. We demonstrate a consistent relationship between canopy height derived from DAP and field-based NFI measures of woody AGB across four inventory periods. Over the environmentally heterogeneous area of Switzerland, our models have a comparable predictive performance (R² = 0.54) to previous work predicting AGB based on ALS metrics. Pearson correlation coefficients between measured and predicted changes in woody AGB over time increased with shorter time gaps (< 2 years) between image capture and field-based measurements, ranging between 0.76 and 0.34. A close temporal match between field surveys and remote sensing data acquisition is thus key to reliable mapping and monitoring of AGB dynamics, especially in areas where forest management and natural disturbances trigger relatively fast canopy dynamics. We show that VHMs derived from repeat DAP capture constitute a cost effective and reliable approach to map and monitor changes in woody AGB at a national extent and can provide an important information source for national carbon accounting and monitoring of ecosystem service provisioning.     

基于易康平台的高分辨率影像在测绘生产中的地物提取

随着遥感技术的发展,遥感数据获取手段有了长足的进步。测绘部门在生产中也展开了基于高分辨率影像提取地表覆盖等信息。本论文以易康软件作为卫星遥感影像地物提取的平台,研究如何利用高分辨率遥感影像生成地表覆盖分类图,以达到测绘部门在生产中的需求。     

河北省卫星遥感海洋应用平台建设研究

随着卫星遥感技术在海洋监测中的作用日益凸显,为了加快地方海洋监测能力建设,构建省级卫星遥感海洋应用平台十分必要。介绍了河北省卫星遥感海洋应用平台的总体设计思路、总体架构、系统建设和应用情况。该平台将国家遥感数据分发单位、地方业务化监测单位、现场观测单位有机联合在一起,形成了自卫星遥感数据与现场观测数据的收集、数据处理、产品生产、数据管理、成果发布至精度评价的全业务闭环流程,实现了海洋环境常规监测业务系统后台全自动化运行,极大程度地提升了河北省海洋遥感监测能力和服务能力,为地方海洋遥感监测平台的建设提供参考。     

How sensitive are estimates of carbon fixation in agricultural models to input data?

Background

Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha^-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.

Results

We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.

Conclusions

High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.     

大气PM2.5遥感制图研究进展

遥感技术具有时空大范围、低成本的独特优势,已经成为定量监测大气PM_(2.5)污染时空分布的重要手段。本文综述了大气PM_(2.5)遥感制图的进展:首先,对大气PM_(2.5)遥感反演方法进行了归纳,以及总结了现有大气PM_(2.5)遥感反演验证方法的适用条件与局限性;其次,对卫星反演大气PM_(2.5)合成产品偏差校正和大气PM_(2.5)无缝制图进行了梳理;最后总结了大气PM_(2.5)遥感制图的前沿研究方向。     

森林地上生物量遥感反演方法综述

森林地上生物量反演对理解和监测生态系统及评估人类生产生活的影响有着重要作用,日益发展的遥感技术使全球及大区域的生物量估算成为可能。近年来,不同的遥感技术和反演方法被广泛用于估算森林生物量。本文首先总结了现有的全球及区域生物量产品及其不确定性,然后综述了3类方法在森林地上生物量遥感反演中的应用,即基于单源数据的参数化方法、基于多源数据的非参数化方法和基于机理模型的反演方法,阐述了各类反演方法的特点、优势及局限性。最后从机理模型研究、多源遥感数据协同、生物量季节变化研究和遥感数据源不断丰富4个方面对今后的生物量遥感反演研究进行了展望。     

珞珈一号01星夜光遥感设计与处理

珞珈一号01星是兼具遥感和导航的一星多用低轨维纳科学试验卫星,本文针对珞珈一号01星夜光遥感设计与处理,详细介绍了卫星平台的有效载荷及平台设计;面向科学的试验目标,制订了科学的夜光成像任务计划,实现了全国夜光一张图任务规划;提出了面向珞珈一号01星的在轨几何辐射定标模型;研制了支持WEB端及移动端访问的数据共享服务系统;针对夜光遥感数据在社会经济应用问题,提出了发展指数和未来发展指数的珞珈一号指数模型,并通过相关实验验证了模型的有效性。珞珈一号01星可为社会经济参数估算、重大事件评估、渔业监测、国家安全等领域提供技术支撑。     

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates.     

基于多源数字遥感影像的“两违”监测服务体系

"两违"综合治理工作因涉及范围广、频率高,亟须采取相应的数字化手段为工作开展提供技术支持。高分辨率遥感技术具有高空间分辨率技术特点,可为"两违"执法工作提供实时详尽的高分辨工作底图,加以遥感处理分析,可以达到对监控区域"两违"变化多时相监测的目的。本文设计了一套以遥感监测为主要手段,集成卫星遥感、航空遥感、无人机航测技术,从多源影像获取、多源数字正射影像工作底图制作、"两违"疑似图斑提取与建库到基于移动互联网技术的"两违"遥感地理信息系统开发的辅助城市规划监测服务体系。     

Current remote sensing approaches to monitoring forest degradation in support of countries measurement,reporting and verification (MRV) systems for REDD+

Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.     

Ontologies to interpret remote sensing images: why do we need them?

The development of new sensors and easier access to remote sensing data are significantly transforming both the theory and practice of remote sensing. Although data-driven approaches based on innovative algorithms and enhanced computing capacities are gaining importance to process big Earth Observation data, the development of knowledge-driven approaches is still considered by the remote sensing community to be one of the most important directions of their research. In this context, the future of remote sensing science should be supported by knowledge representation techniques such as ontologies. However, ontology-based remote sensing applications still have difficulty capturing the attention of remote sensing experts. This is mainly because of the gap between remote sensing experts’ expectations of ontologies and their real possible contribution to remote sensing. This paper provides insights to help reduce this gap. To this end, the conceptual limitations of the knowledge-driven approaches currently used in remote sensing science are clarified first. Then, the different modes of definition of geographic concepts, their duality, vagueness and ambiguity, and the sensory and semantic gaps are discussed in order to explain why ontologies can help address these limitations. In particular, this paper focuses on the capacity of ontologies to represent both symbolic and numeric knowledge, to reason based on cognitive semantics and to share knowledge on the interpretation of remote sensing images. Finally, a few recommendations are provided for remote sensing experts to comprehend the advantages of ontologies in interpreting satellite images.     

无人机低空摄影测量在城市测绘保障中的应用前景

无人机低空摄影测量具有高清晰、大比例尺、小面积、高现势性的优点,是卫星遥感与普通航空摄影不可缺少的补充。可为大比例尺影像地图生产、重点地区正射影像制作、高精度DEM格网和DLG产品提供高分辨率清晰影像数据源,满足城市信息化建设对大比例尺基础地理空间数据的需求,为城市建设提供有效的测绘保障。通过高分辨率测绘产品支持、应急测绘保障、三维数字建模和重点区域动态监测等多个方面对无人机低空摄影测量在城市测绘保障中的应用前景进行论述展望。     

结合树龄信息的遥感森林生态系统生物量制图

森林生态系统是陆地生态系统中的重要组成部分，其中的地上生物量（AGB，Aboveground Biomass）在全球气候变化和碳循环研究中起着重要的作用。本文利用ETM^＋遥感影像，首先建立了实测叶面积指数（LAI，Leaf Area Index）与实测生物量数据的回归关系，基于遥感叶面积指数图像得到初步地上生物量空间分布图；同时在短波植被指数（SWVI，Short Wave Vegetation Index）与实测树龄之间建立了回归关系，在此基础上得到了树龄空间分布图。然后通过将植被指数（VI，Vegetation Index），LAI，树龄等变量针对不同的树种类型进行逐步回归，得到了较好的回归模型，并结合土地利用／土地覆盖估算了贵州省黎平县的地上生物量，绘制了其空间分布图。统计结果显示：总体森林生态系统的AGB与LAI和RSR（Reduced Simple Ratio）之间有一定的相关关系（R^2=0．895）；杉木林的AGB与LAI和归一化植被指数（NDVI，Normalized Difference Vegetation Index）之间有较强的相关性（R^2=0．93）；针叶树种的LAI与年龄是AGB较好的估算因子（R^2=0．937）；阔叶林的AGB与年龄有一定的相关性（R^2=0．792）；混交林的AGB与LAI和SR（Simple Ratio）有较强的相关性（R^2=0．931）。结果表明，将树龄和土地覆盖／土地利用类型的信息加入到地上生物量估算模型的建立中，是一种改善利用多光谱遥感估算精度的较好的方法。结合土地覆盖／土地利用类型的高分辨率的树龄空间分布图，可为森林生态系统的可持续发展和管理提供科学的论据。     

Technical progress of China's national remote sensing mapping:from mapping western China to national dynamic mapping

Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1∶50,000 topographic data of China's land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing map-ping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of colla-boration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic survey-ing and mapping.     

Modelling and representation issues in automated feature extraction from aerial and satellite images

New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.     

新一代智能测绘遥感科学试验卫星珞珈三号01星

光学测绘遥感卫星的性能不断提升,种类日益丰富,已经成为获取全球精准测绘遥感信息的重要支撑。当前光学测绘遥感卫星已具备亚米级的空间分辨能力,但测绘遥感信息服务存在严重的滞后问题,亟须发展智能测绘遥感卫星,向实时智能服务转型升级。本文首先基于光学测绘遥感卫星3种成像体制及其实现方式和应用特点,分析智能测绘遥感卫星的适用体制,进一步面向实时化、智能化和大众化的应用需求,提出通导遥(通信、导航、遥感)一体化智能遥感卫星的设计构想,重点分析智能遥感卫星的服务方式及一体化功能组成;然后,阐述新一代智能测绘遥感科学试验卫星珞珈三号01星的性能与特点;最后,对智能测绘遥感卫星的发展和使命进行总结与展望。珞珈三号01星集遥感与通信功能于一体,探索了从数据获取到应用终端的测绘遥感信息高效智能服务模式,为遥感数据基于天地互联网的在轨处理与实时传输提供了真实的服务验证平台,对我国空间信息网络的建设具有重大意义。     

遥感在沙尘暴监测领域中的应用

沙尘是全球气溶胶系统的主要特征之一,其对地表辐射收支平衡具有显著影响。在过去的几年中,卫星遥感技术已被广泛应用于空气质量监测。本文整理了不同传感器在该领域中的应用,并分析提出了新的理论和方法。文中提供了一份国内外对雾霾监测研究的简要概述,并有针对性地评估了各种方法和经典指数。最后提出一些观点和建议,希望提高遥感在探测全球沙尘暴事件中所起到的作用。     

Predictive Analysis for Vegetation Biomass Assessment in Western Ghat Region (WG) Using Geospatial Techniques

Forests play a critical role in ecological functioning, global warming and climate change through its unique potential to capture and hold carbon (C). Biomass is one of the indicator of the status of forests hence accurate assessment and biomass mapping is important for sustainable forest management. The objectives of this study is to estimate above ground biomass (AGB) from field inventory data and to map AGB combining field inventory data, remote sensing and geo-statistical model. In the present study stratified random sampling were used for estimation of biomass in which 59 plots were laid down in different homogenous strata depending on the NDVI values for the region of Maharashtra Western Ghats. The above ground biomass from field ranged from 0.05 to 271 t-dry wt ha^?1 in which trees added maximum towards total biomass followed by shrubs and herbs. This paper evaluates the best vegetation indices to estimate biomass. This study was carried out by using Landsat TM satellite data and field inventory data in the Ratnagiri district of Maharashtra, India. A significant correlation was observed between biomass and vegetation indices. The best fit regression equation developed from field above ground biomass and NDVI with R² value of 0.61 was used for spectral modeling to estimate the geospatial distribution of AGB in the entire region. The results of spatial predictions Geostatistical technique and remotely sensed data as auxiliary variables were compared using statistical error methods. This study employed Mean error, Root-Mean-Square error, Average Standard error and Root-Mean Square Standardized error. The ME, RMSE, Average Standard error and Root-Mean Square Standardized error was 0.078, 8.032, 7.982 and 0.967 respectively. The results showed that cokriging technique is one of the geostatistical method for spatial predictions of biomass in the studied region. The present study revealed that remote sensing technique combined with field sampling provides quick and reliable estimates of above ground biomass and carbon pool and can be used as baseline information for further temporal studies of biomass status of the region and in planning of forest and natural resources management.     

卫星遥感应急监测信息服务框架设计与应用——以四川木里森林火灾为例

构建及时、有效的卫星遥感应急监测信息服务框架，是开展自然灾害应急救援能力建设的重要内容。本文以数据统筹管理、多源数据处理、应灾信息分析及信息服务快速发布等关键技术为核心，依托高效互联机制和高速数据通道，构建了卫星遥感应急监测信息服务框架。通过在四川木里森林火灾应急遥感监测中的具体应用，实现了对灾前灾后数据的实时推送，以及灾区遥感解译图、三维地形、救援通达性及火灾变化等综合信息服务的及时发布，为四川省火灾一线救援工作提供了科学指导，为新时期国家应急能力建设提供了探索性技术途径。     

遥感技术在“一张图”实施监督系统中的应用

结合国土空间规划“一张图”实施监督信息系统的开发,详细阐述了卫星遥感技术在规划实施评估、国土空间开发适宜性评价和规划监测预警这几个模块中的应用案例,对应用的内容、方法及效果进行了总结和探讨。分析表明,遥感技术能为国土空间规划“一张图”提供众多的基础数据,对于评估城市发展动态、合理规划城市用地具有非常重要的作用。