Characterizing 3D vegetation structure from space: Mission requirements

Human and natural forces are rapidly modifying the global distribution and structure of terrestrial ecosystems on which all of life depends, altering the global carbon cycle, affecting our climate now and for the foreseeable future, causing steep reductions in species diversity, and endangering Earth's sustainability.To understand changes and trends in terrestrial ecosystems and their functioning as carbon sources and sinks, and to characterize the impact of their changes on climate, habitat and biodiversity, new space assets are urgently needed to produce high spatial resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass above ground, the carbon stored within and the implications for atmospheric green house gas concentrations and climate. These needs were articulated in a 2007 National Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives of this paper are to articulate the importance of these new, multi-year, 3D vegetation structure and biomass measurements, to briefly review the feasibility of radar and lidar remote sensing technology to meet these requirements, to define the data products and measurement requirements, and to consider implications of mission durations. The paper addresses these objectives by synthesizing research results and other input from a broad community of terrestrial ecology, carbon cycle, and remote sensing scientists and working groups. We conclude that:

(1)

Current global biomass and 3-D vegetation structure information is unsuitable for both science and management and policy. The only existing global datasets of biomass are approximations based on combining land cover type and representative carbon values, instead of measurements of actual biomass. Current measurement attempts based on radar and multispectral data have low explanatory power outside low biomass areas. There is no current capability for repeatable disturbance and regrowth estimates.

(2)

The science and policy needs for information on vegetation 3D structure can be successfully addressed by a mission capable of producing (i) a first global inventory of forest biomass with a spatial resolution 1 km or finer and unprecedented accuracy (ii) annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass accumulation rates at resolutions of 1 km or finer, and (iii) transects of vertical and horizontal forest structure with 30 m along-transect measurements globally at 25 m spatial resolution, essential for habitat characterization.

We also show from the literature that lidar profile samples together with wall-to-wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together to satisfy these vegetation 3D structure and biomass measurement requirements. Finally we argue that the technology readiness levels of combined pol-SAR and lidar instruments are adequate for space flight. Remaining to be worked out, are the particulars of a lidar/pol-SAR mission design that is feasible and at a minimum satisfies the information and measurement requirement articulated herein.     

Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry

The Congo Basin is the world's third largest in size (~ 3.7 million km²), and second only to the Amazon River in discharge (~ 40,200 m³ s^− 1 annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3° × 3° regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 km³, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.     

A fast and robust bulk-loading algorithm for indexing very large digital elevation datasets: I. Algorithm

Digital elevation models (DEMs) constitute a valuable source of data for a number of geoscience-related applications. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public the world's largest DEM (composed of billions of points) until that date. The SRTM DEM is stored on the NASA repository as a well-organized collection of flat files. The retrieval of this stored topographic information about a region of interest involves one selection of a proper list of files, their downloading, data filtering in the desired region, and their processing according to user needs. With the aim to provide an easier and faster access to this data by improving its further analysis and processing, we have indexed the SRTM DEM by means of a spatial indexing based on the kd-tree data structure, called the Q-tree. This paper is the first in a two-part series that describes the method followed to build an index on such huge amounts of data, minimizing the number of insert operations. We demonstrate that our method can build a very efficient space-partitioning index, with good performance in both point and range queries on the spatial data. To the best of our knowledge, this is the only successful spatial indexing proposal in the literature that deals with such a huge volume of data.     

高性能SAR成像程序的并行粒度选择技术

高性能并行仿真程序必须采用针对性的并行优化技术以获得高效的性能加速。而根据程序特性,确定适合的并行粒度是设计并行优化技术的基础。因此,以典型合成孔径雷达(SAR)成像程序--距离-多普勒(RD)程序为代表,研究了高性能SAR成像程序的并行粒度选择技术,重点针对并行粒度的基本准则和RD算法的并行粒度选择方法进行了研究。实验结果证明,经过并行粒度优化选择的SAR成像程序能够获得显著的性能提升,并且具有良好的可扩展性。     

基于ZigBee的生产线监控系统的设计与实现

根据生产线的实际需要,设计并实现了用于生产线的无线信息传输网络节点,研究了系统结构,完成了系统的软硬件设计,详细分析了ZigBee组网通信、应答机制建立等关键技术。测试结果表明,系统传输距离远、可靠性高,能够满足实际应用需要。     

三聚氰胺装置中液位计的选用

通过对V-3131助滤剂槽上使用的吹气式液位计LT-36113的测量原理及使用情况分析,证明吹气式液位计在使用中的缺陷,从而说明使用雷达液位计的必要性,并表明雷达液位计将被广泛应用。     

实时高性能CORBA的体系框架研究

CommonObjectRequestBrokerArchitecture（CORBA）标准是分布对象管理系统的一个重要标准,但现有的CORBA标准不支持实时应用系统开发,实时应用对CORBA的发展提出了新的需求。文章立足于现有的CORBA标准做了进一步分析,讨论了传统的CORBA标准对实时应用支持的不足之处,并提出实时务性能CORBA应该具有的特征及其对传统CORBA标准的改进之处。     

基于DHCP的终端设备分类方法

为了有效的管理终端设备,通过分析DHCP（Dynamic Host Configuration Protocol）的动态配置过程和报文内容,提出了一个DHCP环境下对终端设备按照类别标识进行分类的方法。实验证明,该方法是有效的。     

电能量信息采集系统规约插件管理器的架构分析

首先说明了当前江苏省电力系统中各厂家终端产品所采用的通讯规约不完全相同现状。接着分析了规约插件的设计规范和需要满足的设计需求,最后设计出解决通讯规约兼容问题的规约插件管理器。该管理器实现对所有规约插件的管理．同时实现和市场中各种电力终端设备数据通讯。     

地质雷达在水电站坝基工程中的应用研究

岩溶地区水电站工程建设中对坝基岩体完整程度要求较高,为了探明坝基岩体中是否存在溶洞、溶隙和破碎带等不良地质体,应用地质雷达较准确地判断出了坝基下不良地质体的走向和规模,取得了良好的效果,为处理岩溶地质问题和工程安全施工提供了依据.