京津冀地区一次污染过程的星载地基激光雷达联合观测分析

针对2018年3月9—15日京津冀地区的一次空气重污染过程,进行了基于地基颗粒物激光雷达组网的星载-地基联合观测分析。颗粒物激光雷达观测到污染前期为局地污染累积过程,中期有明显的污染物区域传输过程,北京受太行山沿线城市污染输送影响较大。风廓线激光雷达观测结果表明:此次污染过程近地面主要为偏南风且风力较弱,冷空气到来时风向转为较强东北风,导致污染消散。微波辐射计观测到保定在污染过程中出现持续6 d的逆温层,同时在污染过程中近地面相对湿度较高,逆温层被打破后污染开始消散。在污染过程的各个阶段中,污染团的空间分布与变化特征均被很好地反映出来,可见地天联合观测对污染物的累积与输送研究有较大的意义,能对京津冀及周边地区的大气污染联防联控提供有力支持。     

卫星遥感洞庭湖主汛期水体时空变化特征及影响因子分析

基于1989~2011年的长时间序列卫星遥感数据,利用综合水体信息提取方法提取了洞庭湖区6~9月主汛期的水体信息,通过较高分辨率卫星遥感数据验证,水体面积提取精度达到90%以上。洞庭湖年平均径流入湖量、NCEP再分析资料计算的湖体上空和流域累计月平均降水量分别与水体面积变化的关系进行分析,结果表明: 1989~2011年间洞庭湖水体面积最大值主要分布在7和8月,这两个月也是洞庭湖区域发生洪涝灾情的高风险期;洞庭湖水体面积与年平均径流入湖水量的相关系数为0.67(置信度为95%);2003年以前,洞庭湖主汛期间水体面积波动比较大,2003年三峡水库运行后,洞庭湖的面积波动有所减少;洞庭湖上空累计月平均降水量对于水体面积存在正相关性,相关系数为0.68(置信度为99%);2003年以前,洞庭湖流域累计月平均降水量和水体面积相关系数为0.50(置信度为90%),2003年三峡水库运行后,两者相关性有所减弱。     

Landscape trajectory of natural boreal forest loss as an impediment to green infrastructure

Loss of natural forests by forest clearcutting has been identified as a critical conservation challenge worldwide. This study addressed forest fragmentation and loss in the context of the establishment of a functional green infrastructure as a spatiotemporally connected landscape-scale network of habitats enhancing biodiversity, favorable conservation status, and ecosystem services. Through retrospective analysis of satellite images, we assessed a 50- to 60-year spatiotemporal clearcutting impact trajectory on natural and near-natural boreal forests across a sizable and representative region from the Gulf of Bothnia to the Scandinavian Mountain Range in northern Fennoscandia. This period broadly covers the whole forest clearcutting period; thus, our approach and results can be applied to comprehensive impact assessment of industrial forest management. The entire study region covers close to 46,000 km² of forest-dominated landscape in a late phase of transition from a natural or near-natural to a land-use modified state. We found a substantial loss of intact forest, in particular of large, contiguous areas, a spatial polarization of remaining forest on regional scale where the inland has been more severely affected than the mountain and coastal zones, and a pronounced impact on interior forest core areas. Salient results were a decrease in area of the largest intact forest patch from 225,853 to 68,714 ha in the mountain zone and from 257,715 to 38,668 ha in the foothills zone, a decrease from 75% to 38% intact forest in the inland zones, a decrease in largest patch core area (assessed by considering 100-m patch edge disturbance) from 6114 to 351 ha in the coastal zone, and a geographic imbalance in protected forest with an evident predominance in the mountain zone. These results demonstrate profound disturbance of configuration of the natural forest landscape and disrupted connectivity, which challenges the establishment of functional green infrastructure. Our approach supports the identification of forests for expanded protection and conservation-oriented forest landscape restoration.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Effectiveness of Africa's tropical protected areas for maintaining forest cover

The effectiveness of parks for forest conservation is widely debated in Africa, where increasing human pressure, insufficient funding, and lack of management capacity frequently place significant demands on forests. Tropical forests house a substantial portion of the world's remaining biodiversity and are heavily affected by anthropogenic activity. We analyzed park effectiveness at the individual (224 parks) and national (23 countries) level across Africa by comparing the extent of forest loss (as a proxy for deforestation) inside parks to matched unprotected control sites. Although significant geographical variation existed among parks, the majority of African parks had significantly less forest loss within their boundaries (e.g., Mahale Park had 34 times less forest loss within its boundary) than control sites. Accessibility was a significant driver of forest loss. Relatively inaccessible areas had a higher probability (odds ratio >1, p < 0.001) of forest loss but only in ineffective parks, and relatively accessible areas had a higher probability of forest loss but only in effective parks. Smaller parks less effectively prevented forest loss inside park boundaries than larger parks (T = ?2.32, p < 0.05), and older parks less effectively prevented forest loss inside park boundaries than younger parks (F_2,154 = ?4.11, p < 0.001). Our analyses, the first individual and national assessment of park effectiveness across Africa, demonstrated the complexity of factors (such as geographical variation, accessibility, and park size and age) influencing the ability of a park to curb forest loss within its boundaries.     

Applications of Very High‐Resolution Imagery in the Study and Conservation of Large Predators in the Southern Ocean

The Southern Ocean is one of the most rapidly changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically important krill and fish. Because sea ice loss is expected to be accompanied by declines in krill and fish predators, decoupling the effects of climate and anthropogenic changes on these predator populations is crucial for ecosystem‐based management of the Southern Ocean. We reviewed research published from 2007 to 2014 that incorporated very high‐resolution satellite imagery to assess distribution, abundance, and effects of climate and other anthropogenic changes on populations of predators in polar regions. Very high‐resolution imagery has been used to study 7 species of polar animals in 13 papers, many of which provide methods through which further research can be conducted. Use of very high‐resolution imagery in the Southern Ocean can provide a broader understanding of climate and anthropogenic forces on populations and inform management and conservation recommendations. We recommend that conservation biologists continue to integrate high‐resolution remote sensing into broad‐scale biodiversity and population studies in remote areas, where it can provide much needed detail. Aplicaciones de Imágenes de Muy Alta Resolución en el Estudio y Conservación de Grandes Depredadores en el Océano Antártico     

Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin1

Gebremichael, Mekonnen, Emmanouil N. Anagnostou, and Menberu M. Bitew, 2010. Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin. Journal of the American Water Resources Association (JAWRA) 46(2):361-366. DOI: 10.1111/j.1752-1688.2010.00428.x. Abstract: Given the increasingly higher resolution and data accessibility, satellite precipitation products could be useful for hydrological application in the Nile River Basin, which is characterized by lack of reasonably dense hydrological in situ sensors and lack of access to the existing dataset. However, in the absence of both extreme caution and research results for the Nile basin, the satellite rainfall (SR) products may not be used, or may even be used erroneously. We identify two steps that are critical to enhance the value of SR products for hydrological applications in the Nile basin. The first step is to establish representative validation sites in the Nile basin. The validation site will help to quantify the errors in the different kinds of SR products, which will be used to select the best products for the Nile basin, include the errors in decision making, and design strategies to minimize the errors. Using rainfall measurements collected from the unprecedented high-density rain gauge network over a small region within the Nile basin, we indicate that SR estimates could be subject to significant errors, and quantification of estimation errors by way of establishing validation sites is critically important in order to use the SR products. The second step is to identify the degree of hydrologic model complexity required to obtain more accurate hydrologic simulation results for the Nile basin when using SR products as input. The level of model complexity may depend on basin size and SR algorithm, and further research is needed to spell out this dependence for the Nile basin.     

基于环境一号卫星多光谱影像数据的三湖一库富营养化状态评价

环境一号卫星是我国2008年自主发射的环境与灾害监测小卫星,其2d的时间分辨率使其成为环境变化监测的重要数据源.根据实测的太湖、巢湖、滇池和三峡水库的水面光谱信息以及水质参数,构建基于环境一号卫星多光谱数据的富营养化评价模型,对太湖、巢湖、滇池和三峡水库2009年水体营养状况进行了评价分析.研究结果表明:利用环境一号卫...     

基于机器学习和卫星遥感的PM2.5/10 空间连续分布反演方法研究

在过去的几十年里,快速的经济发展以及工业化、城镇化进程加速使得中国的资源环境承担的压力不断加大。作为影响空气质量的首要污染物,PM_2.5和PM₁₀（记为PM_2.5/10）直接影响着广大人民群众的身体健康。因此,针对PM_2.5/10浓度进行遥感反演研究,对环境监测和控制改善全国空气环境质量具有重要的意义。近些年来,随着对近地面PM_2.5/10浓度研究的不断深入,基于遥感影像数据进行PM_2.5/10浓度的反演方法也日益增多。本文利用Google Earth engine（GEE）平台获取了海量的Landsat 8 OLI遥感影像数据,并结合气象信息、空间特征等参数,采用机器学习中常用的多层映射反向传播神经网络构建了波段反射率与PM_2.5/10浓度之间的反演模型,以获得PM_2.5/10在研究区域的连续分布。为了提高基础PM_2.5/10反演模型的反演精度,还从影响因素和前溯时间两个维度出发,探寻了模型的最优化输入参数组合,并最终实现了对PM_2.5/10浓度的精准反演。以北京市地区为例,模型的PM_2.5和PM₁₀的反演精度R²分别达到0.814和0.796,均方根误差RMSE分别为19.21 μg?m^?3和28.31 μg?m^?3。鉴于该反演结果具有较高的准确性和可靠性,本文所建立的方法模型为研究PM_2.5/10在空间上的连续分布特征提供了新的思路和方法,具有较为重要的科研意义与广泛的应用价值。     

基于卫星遥感气溶胶产品评估体系的气溶胶时空分布及变化趋势表征

卫星遥感气溶胶虽然空间覆盖度高,但不同产品数据在准确性和适用性上存在显著差异.为了能够科学定量的衡量各个产品的优劣,选择最合适的气溶胶产品,该研究以数学统计为基础,提出了一种卫星遥感气溶胶产品评估体系,并依此确定了全球6个人口密集地区的最优卫星数据集,在此基础上开展了近10年的（2009—2018）气溶胶时空变化分析.结果表明暗像元算法在植被覆盖度高的地区表现最好,深蓝算法在亮地表的沙漠干旱地区更占优势,而暗像元-深蓝融合算法在土地类型复杂且气溶胶来源多变时得以突出.人口密集的6个区域中,除了区域A和区域B,其它地区的大气污染水平整体偏高.其中,A、B、E的气溶胶负荷呈下降变化,区域F基本不变,其余区域上升变化.评估体系的建立为气溶胶遥感产品的选取提供了新的衡量方法,且该文关于气溶胶时空分布及变化的分析可以为区域性气溶胶研究提供一定的参考价值.