河川径流遥感监测研究进展

河川径流参数是用于地表水资源评估、全球变化监测和生态环境保护的基础数据.现有的河川径流监测数据基于水文监测站点获取.近年来,受经济和政治原因的影响,全球水文监测站点在逐渐减少.随着全球变化研究对区域乃至全球水文监测数据需求的增加,监测站点有限及监测数据格式多样等问题逐渐凸显.过去15年,卫星遥感技术在河川径流监测领域的研究和应用实践,使上述问题的解决成为了可能.总结了河川径流遥感监测方法和技术研究进展,包括地基高低频雷达、航空航天雷达和多光谱卫星遥感监测3个方面;介绍了全球大型河川径流与湖泊水体动态监测重大应用成果及未来研究计划.指出在未来具有全天时、全天候,高时空分辨率,以及多水文要素探测能力遥感卫星发射之前,应充分利用遥感野外观测实验,完善河川径流监测技术方法,并综合应用已有高时空分辨率的多光谱和微波遥感数据,开展径流监测应用研究.     

多源信息融合在维西-兰坪矿产勘查中的应用

运用遥感图像处理软件ERDAS中的图像增强方法,分析ETM+遥感数据,提取与金属矿化有关的异常信息,将化探异常图像和遥感信息叠加进行相关异常信息与成矿的关系研究,对本区找矿预测具有较好的指导作用。     

滇东北及毛坪铅锌矿遥感地质与成矿预测

根据遥感构造、含矿岩性地层、岩石蚀变异常等多种遥感地质信息,采用地质异常单元统计预测方法,对毛坪铅锌矿进行多元信息成矿预测,明确了找矿方向。     

汶川震区北川县城泥石流源地特征的遥感动态分析

汶川地震导致山地斜坡积累了大量碎屑物质,在降雨作用下极易成为泥石流源地。震后的2008年9月24日一场暴雨导致北川县境内72条沟同时暴发泥石流。本文选择了汶川地震高烈度区的北川县城8条泥石流沟流域为研究区,基于遥感手段开展了震后和相继暴雨后的泥石流源地变化特征。强震后泥石流流域的重要变化是在沟谷内诱发了大量滑坡。通过开展遥感解译和野外调查,重点分析了研究区泥石流源地的滑坡活动。将512汶川地震后的2008年5月18日获取的航空图像与924暴雨后获取的2008年10月14日SPOT图像相比较,发现泥石流源地的地震滑坡面积由1537104m2增加到暴雨后的1912104m2,即汶川高烈度区一场暴雨过程新增滑坡面积达244%。根据SPOT图像解译,暴雨后泥石流沟床中的松散堆积物增大到97104m2。上述研究结果表明汶川震区在强降雨条件下发生泥石流的敏感性特别高。     

Spatiotemporal Dynamics of a Páramo Ecosystem in the Northern Ecuadorian Andes 1988-2007

Páramo is a term used to describe tropical alpine vegetation between the continuous timberline and the snow line in the Northern Andes. Páramo environments provide important species habitat and ecosystem services. Changes in spatial extent of the páramo ecosystem at Pambamarca in the Central Cordillera of the northern Ecuadorian Andes were analysed using multi-temporal Landsat TM/ETM+ satellite data. The region suffered a loss of 1826.6 ha or 20% of the total area at a rate of 100 ha/annum during 1988-2007 period. It is found that permanent páramo cover decreased from 8350 ha in 1988 to 5864 ha in 2007 at a fairly constant rate(R2=0.94). This loss is attributed to expansion of commercial agriculture and floriculture in the valleys coupled with increased population pressure. Land at higher elevations has been cleared for small scale agriculture. Loss of the páramo ecosystem will exert a number of negative impacts on ecosystem services and livelihoods of the local population at Pambamarca.     

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.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

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.