基于遥感影像的建筑物空间分布方法在地震灾害损失预评估中的应用

房屋建筑数据是地震重点危险区预评估工作的基础,需基于获取到的房屋建筑信息开展人员伤亡、经济损失、救援物资需求等预评估工作。历年地震重点危险区预评估工作能够通过现场调查得到的房屋建筑信息占比极小,仅能进行抽样调查。因此,为批量完成危险区内全部房屋建筑损失估算,需基于遥感影像获取房屋建筑矢量数据,并建立数据库。为实现全国地震重点危险区预评估工作中大批量建筑物矢量化数据的快速获取,本文采用基于遥感影像的建筑物空间分布数据批量获取方法,得到地震重点危险区内建筑物空间矢量数据,结合现场抽样调查得到的建筑物属性信息,建立地震重点危险区建筑物空间分布数据库,进而为地震重点危险区灾害损失预评估工作提供数据基础。本文采用的方法可广泛应用于地震重点危险区房屋建筑信息获取工作中,可提高工作效率,降低工作成本,提升预评估工作的科学性和准确性。     

Remote sensing and hydrological measurement based irrigation performance assessments in the upper Amu Darya Delta,Central Asia

In the Aral Sea Basin, where the Central Asian countries compete for limited water resources, reliable information on the actual water use for eight million ha of irrigated land are rare. In this study, spatially distributed land use data, seasonal actual evapotranspiration, and reference evapotranspiration derived from multitemporal MODIS data were combined with in situ water flow measurements for irrigation performance assessments in the upper Amu Darya Delta. The functioning of the major irrigation and drainage which supplies an agricultural area of 270,000 ha in the Uzbek province Khorezm was analysed using water balancing and adequacy indicators of irrigation water use.An average relative evapotranspiration of 95% indicated fulfilled water demands and partly over-irrigation, whereas values below 75% disclosed inadequate water supply in distant parts of the irrigation system. On the other hand, immense water withdrawals of approximately 24,000 m³ ha⁻¹ recorded at the system boundaries between April and September 2005 clearly exceeded the field water demands for cotton cultivation. Only 46% of the total irrigation amounts were consumed for crop production at field level. Throughout the vegetation period, approximately 58% of the total available water left the region as drainage water. Monthly observations of the depleted fraction and the drainage ratio highlighted drainage problems and rising groundwater levels at regional scale. In the most distant downstream subsystem, a high risk of groundwater and soil salinity during the main irrigation phase was found.A combination of high conveyance losses, hydraulic problems, direct linkages between irrigation and drainage, and low field application efficiencies were identified as major reasons for underperforming irrigation. The findings underlined the necessity of water saving and of reconsidering water distribution in Khorezm. The remote sensing approach was concluded as a reliable data basis for regular performance assessments for all irrigation systems in Central Asia.     

SOFTWARE REVIEWS

AMOS—Analysis of MOment Structures . James Arbuckle CLIMATEDATA–Summary of the Day . (Version 1.10). HYDRODATA–U.S.G.S. Daily Values (Version 2.0). The MAP SETS (includes EUROPEAN MAPSET, US MAPSET and WORLD MAPSET). James Taylor     

Innovation for sustainable energy from a pro-poor perspective

The development and transfer of clean energy technologies to achieve universal energy access is challenging due to the inherent complexities of the energy sector, and the energy governance and financial systems in developing economies. Innovation is an essential part of successfully addressing these difficulties. Duplicating the energy infrastructure models of developed countries will not be sufficient to meet the needs of poor consumers. To the extent that innovation can accelerate energy access, it is important to understand the specific types of innovations that are necessary and how they might be facilitated. The general features of existing international clean energy innovation systems, which are predominantly driven by the markets and emissions reduction mechanisms of developed and rapidly growing emerging economies, are reviewed and the alignment of these systems to the innovation processes required to extend energy access globally is evaluated. Drawing on the innovation policy literature, the attributes of effective international and domestic energy innovation systems that are pro-poor and the associated policy approaches are identified.     

Remotely sensed assessment of water quality levels in the Pearl River Estuary, China

In this paper, a method of assessing water quality from satellite data is introduced. The composite pollution index (CPI) was calculated from measured chemical oxygen demand (COD) and nutrient concentration. The relationships between CPI and 240 band combinations of SeaWiFS water-leaving radiance were analyzed and the optimal band combination for estimating CPI was chosen from the 240 band combinations. An algorithm for retrieval of CPI was developed using the optimal band combination, (L₄₄₃ × L₅₁₀)/(L₄₁₂ + L₄₉₀). The CPI was estimated from atmospherically corrected SeaWiFS data by employing the algorithm. Furthermore, the CPI value range for each water quality level was determined based on data obtained from 850 samples taken in the Pearl River Estuary. The remotely sensed CPIs were then transferred to water quality levels and appropriate maps were derived. The remotely sensed water quality level maps displayed a similar distribution of levels based on in situ investigation issued by the State Ocean Administration, China. This study demonstrates that remote sensing can play an important role in water quality assessment.     

国外农情遥感监测系统现状与启示

大范围的可靠农情信息对粮食市场及相关政策的制定至关重要,是保障区域及全球粮食安全的重要依据,在全球气候变化、人口增长、土地利用/覆盖变化剧烈的背景下,对这一信息的需求也更加迫切.传统农情信息的获取依赖于庞大的调查队伍和大量的调查工作,信息的获取存在成本高、时效性差和结果受主观影响大的缺点.伴随着近30年遥感技术本身及其在农情信息获取领域能力的提升,一些国家与国际组织建设了各自的农情遥感监测系统,并开展了运行化的监测.对美国、欧盟、FAO、加拿大、巴西、阿根廷、俄罗斯、印度等主要的农情遥感监测系统进展进行了详细的介绍,并通过对这些系统的分析得到一些农情监测系统建设的启示.指出作物种植面积估算、单产预测、长势监测、旱情监测是农情遥感监测中最主要的4个主题.在面积估算方面,各个系统在遥感技术不断发展的同时对地面调查的依赖并没有减少,甚至得到了强化,这与遥感降低地面调查的初衷相违背,导致遥感技术在大范围农情监测中的潜力没有得到充分发挥,在单产预测方面,需要发展独立的遥感预测方法.提升遥感的作用是未来一段时间内农情遥感监测系统建设的主要方向.     

Mapping Energy: Cartographies of Energy Into The Twenty‐First Century

“Energy” presents a number of complex and interrelated challenges regarding the environment, economy, and politics. In this paper, we argue that cartography should help clarify our understanding of energy issues, but ask whether this has in fact been the case. In a review of over 100 articles pulled from twenty‐three peer‐reviewed geography journals, we qualitatively assess energy maps published since the early 20^th century, examining trends in topic and cartographic technique. Energy maps in geography journals have focused on North America and Western Europe while relying on proportional symbols, grayscale production, and the analysis of energy phenomena at the national scale—tendencies that in many instances have limited our understanding of the ways in which energy is actually consumed. Simultaneously, cartographers are limited to the energy data available to them, frequently precluding small‐scale consumption analysis or consideration of diurnal and seasonal trends. We argue that the future of energy cartography relies on access to consumption data coupled with greater user interactivity.     

Classifying and mapping the urban transition in Vietnam

The urban transition almost always involves wrenching social adjustment as small agricultural communities are forced to adjust rapidly to industrial ways of life. Large-scale in-migration of young people, usually from poor regions, creates enormous demand and expectations for community and social services. One immediate problem planners face in approaching this challenge is how to define, differentiate, and map what is rural, urban, and transitional (i.e., peri-urban). This project established an urban classification for Vietnam by using national census and remote sensing data to identify and map the smallest administrative units for which data are collected as rural, peri-urban, urban, or urban core. We used both natural and human factors in the quantitative model: income from agriculture, land under agriculture and forests, houses with modern sanitation, and the Normalized Difference Vegetation Index. Model results suggest that in 2006, 71% of Vietnam's 10,891 communes were rural, 18% peri-urban, 3% urban, and 4% urban core. Of the communes our model classified as peri-urban, 61% were classified by the Vietnamese government as rural. More than 7% of Vietnam's land area can be classified as peri-urban and approximately 13% of its population (more than 11 million people) lives in peri-urban areas. We identified and mapped three types of peri-urban places: communes in the periphery of large towns and cities; communes along highways; and communes associated with provincial administration or home to industrial, energy, or natural resources projects (e.g., mining). We validated this classification based on ground observations, analyses of multi-temporal night-time lights data, and an examination of road networks. The model provides a method for rapidly assessing the rural–urban nature of places to assist planners in identifying rural areas undergoing rapid change with accompanying needs for investments in building, sanitation, road infrastructure, and government institutions.     

Perceptions and preferences of commercial fishers for dedicated access privilege framework in a multispecies fishery

The decline of the world's fisheries and the inability of traditional management frameworks to maintain them, has led managers to adopt alternative management frameworks. The use of dedicated access privileges have often been shown to have varying popularity among factions within the commercial fishing industry and managers. Here, we examine commercial fishers' preference for alternative management frameworks in the context of a unique multispecies fisheries of the Florida Keys. By surveying commercial fishers, we find that that the size of operation plays no role in affecting fisher perception regarding dedicated access privileges. Furthermore, fishers who are organized are less likely to support dedicated access privilege frameworks. Overall, we do not find enough support in the fishing industry for the implementation of dedicated access privileges in the Florida Keys. These findings can provide inputs in developing effective management plans in the region.     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.