Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

Beach topography mapping—a comparsion of techniques

A comparison of current techniques for measuring elevations in the beach and near-shore zones is presented. Techniques considered include traditional methods such as ground survey along transects and airborne stereophotogrammetry, and also newer methods based on remote sensing such as airborne scanning laser altimetry (LiDAR). The approach taken was to identify a representative group of users of beach elevation data, elicit their requirements regarding these data, then assess how well the different methods met these requirements on both technical and financial grounds. Potential users of beach height measurements include those concerned with coastal defence, coastal environmental management economic exploitation of the intertidal zone, and coastal flood forecasting. Three test areas in the UK were identified covering a range of such users and also different beach types. A total of 17 basic user requirements were elicited. For each requirement each method was scored according to the degree to which it could meet the requirement. Total scores were calculated and each method ranked. This was undertaken for all the requirements together, for a subset relating to survey of narrow beaches, and for a subset relating to survey of wide beaches. Approximate costs were also established for the top six methods. Airborne stereophotogrammetry proved to be the best method technically, but was also the most expensive. Ground survey provides very good technical performance on narrower beaches at moderate cost. Airborne LiDAR can achieve good technical performance on both narrow and wide beaches at lower cost than ground survey. The satellite-based waterline method was also inexpensive and gave good results on wide beaches. An overall conclusion is that, while the traditional methods of ground survey and airborne stereophotogrammetry remain the best for engineering-related surveys requiring high levels of accuracy, airborne LiDAR in particular looks set to have a significant impact on beach survey for applications for which a vertical accuracy of 20 cm is acceptable, provided that its technology evolves satisfactorily.     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取;提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列;发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性;构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测;在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

面向区域二次污染风险控制的臭氧及其前体物卫星遥感监测

日益突出的臭氧(O_3)污染已成为继PM2. 5之后我国大气污染防治的又一艰巨任务。由于氮氧化物(NO_x)、挥发性有机物(VOCs)这2种前体物的减排难度较大,且与O_3浓度存在复杂的非线性关系,准确获取O_3及NO_x、VOCs的时空分布对制定有效的防控措施至关重要。基于卫星遥感可定量反演O_3及2种前体物的代表性物种——二氧化氮(NO_2)、甲醛(HCHO)及乙二醛(C_2H_2O_2)的时空分布信息。面向区域O_3污染分析和防控应用,综述了卫星遥感对O_3及NO_2、HCHO、C_2H_2O_2的探测能力,以及利用遥感手段分析区域O_3及其前体物的传输。进而从O_3与NO_x、VOCs关系的角度,分析了利用卫星反演的前体物表征O_3生成风险的可行性。最后对卫星在区域O_3及其前体物监测方面的前景趋势提出了思考。     

遥感技术在水生态环境管理的应用与前景

随着遥感数据源的不断丰富,遥感技术不断提高,可以解决越来越多的水环境问题。指出了当前水生态环境管理方面的主要需求,结合目前遥感技术的发展,对国内外的水环境遥感研究进展进行综述。以湖泊富营养化监测与评估、核电站温排水遥感监测及城市黑臭水体遥感监测为案例,具体阐述遥感在水环境管理中的应用方法及成效。未来水生态环境管理发展趋势将以水污染防治为主向水污染防治和水生态修复与保护并重发展。基于此趋势,提出遥感在水生态修复的应用潜力,利于更多地方部门积极有效应用遥感技术,解决水生态环境问题。     

利用卫星遥感数据估算PM2.5浓度的应用研究进展

近年来,PM_(2.5)已成为中国大气污染的首要污染物,危害人体健康。为弥补地基监测站点在空间分布上的局限性,借助卫星遥感技术估算PM_(2.5)浓度已成为研究热点。文章总结了利用卫星估算PM_(2.5)浓度的各种研究方法,探讨了不同方法的优势和不足,指出不同方法对不同应用目的的选择性差异较大。提出,应针对不同应用目的选择相应的方法,从而取得满足各方面需求的研究成果,为未来PM_(2.5)浓度估算应用工作提供参考。     

广东省“十二五”生态环境时空变化趋势及影响因素

基于2011—2015年Landsat7、Landsat8等卫星遥感影像,结合土壤侵蚀面积、水资源量、降雨量、污染物排放量等统计数据,按照《生态环境状况评价技术规范》(HJ 192—2015),研究评价广东省"十二五"期间生态环境状况及其时空变化趋势,并对其影响因素进行综合分析。结果表明,广东省的生态环境状况总体为优,各市生态环境状况均属优、良,粤北生态环境状况整体最好;广东省及各市生态环境状况稳中趋好,但呈现温和地波动变化;主要污染物排放量下降和水资源总量提高是促进生态环境状况改善的主要原因。     

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long‐standing “Digital Divide” in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time‐varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long‐time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed “data rods,” are pre‐generated or generated on‐the‐fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on “data curtains.” The on‐the‐fly generation of data rods uses “data cubes,” NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.     

南方丘陵地区河谷城市用地时空演变与驱动分析——以上饶市城区为例

以揭示中国南方丘陵地区河谷城市的空间演变过程和特征为目的,以上饶市城区为例,在遥感与GIS技术的支持下,对1988~2013年间上饶市城区城市用地的时空演变过程、特征及驱动影响因素进行了研究。结果表明,1988~2013年的25 a间,上饶市城区城市用地呈现出快速增长的态势,城市形态的演变具有明显的时空特征:时间序列上,不论扩展幅度还是扩展速度,2001~2013年间的值均高于1988~2001年间的值,前后两个时段的扩展特征呈现出明显的差异性;空间格局上,上饶市城区以老城区的中心广场为中心向四周扩展,先后经历了放射性扩展、组团式分散扩展两个阶段,同时呈现出明显的方向分异性,西南和西为其主要扩展方向,而其东南方向的扩展速度最为缓慢。自然环境中的地貌对上饶市城区城市用地的扩展起到很大的限制作用,经济社会的发展、政策规划等因素成为城市用地扩张与时空演化的外在驱动因素。     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

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