武汉城市群夏季热岛特征及演变

利用2000~2010年共11期MODIS地表温度资料和多源多时相的遥感影像分类结果揭示武汉城市群的夏季热岛效应,反演并计算出10 a间武汉城市群日间和夜间的热岛强度变化、土地覆盖类型和城镇用地面积。在对不同时相的地表温度数据进行热岛指数归一化处理的基础上,分析了武汉城市群热岛的分布特征及年代演变,定量分析了武汉城市群以及中心城市武汉市不同热状况区面积的变化和热场的变迁。结果表明,武汉城市群夏季热岛效应较为明显,其中武汉市是主要热源和热中心;自2000年起,武汉城市群城乡温度差异逐步减小,热中心分布向外扩散,城市热岛区域急速扩张,整体热环境趋于恶化;新兴城区的开发增加了武汉市的热源分布,人工表面的增加以及自然表面的减少导致城市热岛效应不断加剧。     

塔里木河下游区域植被时空变化

为了对比生态输水工程实施前后塔里木河下游植被变化,分析植被对生态输水的时空响应,基于1986-2017年研究区上方无云的22期Landsat NDVI数据,辅以波动分析、趋势分析,探索研究区植被的时空变化特征,并对其驱动因素进行分析。结果表明：（1）空间上,植被的分布与水资源的分布密切相关,主要沿河道和积水区域分布。（2）1986-2000年,NDVI呈现缓慢下降趋势,2000-2017年NDVI总体呈现波动增加趋势;植被对生态输水有一定的滞后性,且与输水量密切相关。（3）研究区NDVI时间序列的方差介于0.0077~0.1957间,存在明显的空间差异,其波动的大小与植被种类密切相关。（4）1986-2000年,植被的NDVI空间趋势以减小为主,并主要发生在英苏和老英苏附近;2000-2017年,植被的NDVI空间趋势以增加为主,且主要发生在沿河道区域和喀尔达依东侧。     

基于多源遥感数据的锡尔河中下游农田土壤水分反演

机器学习结合多源遥感数据反演土壤水分含量（SMC）是目前SMC研究的热点,因较少考虑温度、蒸散等重要SMC影响因子,反演结果存在一定的不确定性。利用Sentinel-1影像、MODIS产品和SRTM数据,提取雷达后向散射系数等32个SMC影响因子,经相关分析选择27个显著的SMC影响因子（P<0.05）作为反演因子,并设计三组因子组合。这三组因子组合分别与随机森林、支持向量回归、BP神经网络三种机器学习方法结合,发现基于随机森林结合所有因子的方案,其SMC反演精度最高,该组合均方根误差RMSE为0.039 m³/m³,将该方案被用于反演2017年生长季锡尔河流域中下游平原区农田SMC。结果表明：从上部至下部SMC总体呈逐渐增加的态势,但存在显著时空差异,春季和秋季SMC较高而夏季较低。SMC差异主要由土壤质地、热量条件和地表植被状况差异引起。春季平原区下部农田SMC要高于上部,SMC的主控因子是土壤质地和地表植被状况;在夏季,土壤水分的主控因子是热量条件,农田灌溉弥补了热量条件差异对土壤水分的影响,导致空间上平原上部和下部土壤SMC空间差异不显著;秋季SMC的主控因子植被状况抵消地表温度和土壤质地差异对SMC的影响,使得秋季SMC空间差异不显著。本文采用的研究方法在一定程度上克服了因考虑SMC影响因子不足而获取更高SMC精度的限制。     

Estimation and inter-comparison of dust aerosols based on MODIS, MISR and AERONET retrievals over Asian desert regions

This study presents detailed analysis of spatiotemporal variations and trend of dust optical properties i.e., Aerosol Optical Depth(AOD) and Angstrom component over Asian desert regions using thirteen years of data(i.e., 2001–2013) retrieved from Aerosol Robotic Network(AERONET), Moderate Resolution Imaging Spectroradiometer(MODIS) and Multi-angle Imaging Spectroradiometer(MISR). These regions include Solar Village, Dunhuang and Dalangzadgad and are considered as origin of desert aerosols in Asia. Mann–Kendall trend test was used to show the trend of AOD. The relationship of AOD with weather parameters and general AOD trend over different wavelengths has also been shown. AOD's trend has been observed significant throughout the year in Solar Village, while in Dunhuang and Dalanzadgad the significant trend has been found only in peak period(March–June).Analysis show high values of AOD and low values of angstrom in Solar Village during peak period. In Chinese desert regions, high values of AOD have been found during peak period and low values in pre-peak period. Significant relationship has been observed between AOD and average temperature in Solar Village and Dalanzadgad whereas rainfall and wind speed showed no significant impact on AOD in all desert regions.     

气候变化和人类活动对东部沿海地区NDVI变化的影响分析

植被是陆地生态系统的重要组成部分,特别是在人类活动密集地区,良好的植被覆盖对于维持区域生态环境稳定、增进居民生活福祉和促进社会经济可持续发展意义重大.基于归一化植被指数(NDVI)、气温、降水和太阳辐射数据,采用趋势分析、偏相关分析和残差分析等方法,探究了1982～2019年中国东部沿海地区NDVI时空变化特征及其与气候因子的关系,评估了气候因素和人类活动等非气候因素对NDVI变化的影响.结果表明：(1)1982～2019年研究区NDVI变化趋势具有明显区域性、阶段性和季节性差异,就区域平均而言,2000年以前(第一阶段)的生长季NDVI比2001年以后(第二阶段)增加更快,而两阶段春季NDVI增加速率均为各季节最快;(2)同一阶段NDVI与各气候因子的关系在不同季节存在差异,而同一季节NDVI的主要气候控制因子在不同阶段也不一致,并且NDVI与气候因子的关系具有很大空间差异.总体上,1982～2019年研究区生长季NDVI的增加与气温的持续上升关系紧密,第二阶段降水和太阳辐射的增加也产生了积极作用;(3)相比于人类活动等非气候因素的影响,气候变化对近38年来研究区生长季NDVI变化的...     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.     

20世纪初以来沂蒙山区森林植被动态及其对气候变化的响应——基于遥感和树轮的研究

遥感能够直接反映植被生长信息,但目前观测时间较短;树轮资料可以弥补遥感手段的不足,但往往缺乏与植被生长状况（如植被生产力）的直接关联。已有研究往往计算不同植被指数指标和树轮指数的相关性,并基于此来重建长时间尺度的植被动态信息。但基于相关性所选取的指标在不同地区存在较大差异,不利于空间对比研究。以沂蒙山区为研究区,选取能够有效表征植被年初级生产力的生长季NDVI累积值指标,利用Bootstrap法建立了其与树轮宽度的关系,重建了20世纪初期以来植被动态时间序列,并分析了变化特征及其与气候变化的关系。结果表明：沂山地区生长季NDVI累积值的多年平均值为7.36,低于蒙山和塔山地区;蒙山地区植被状况呈现好转趋势,特别是20世纪90年代之后植被好转趋势更加明显,而塔山和沂山地区植被无显著变化。小波分析结果表明研究区植被动态存在较显著的2 a、4 a或8 a尺度的周期变化,与生长季帕尔默干旱指数及平均温度的周期变化相一致,但干旱指数与植被动态具有更高的相关性。本研究综合运用树轮与遥感技术发展了长时间尺度植被动态时间序列重建方法,有助于更好地理解植被动态及其对气候变化的响应。     

卫星遥感技术在空气点位布设评估工作中的应用研究

以苏州市为例,利用2013-2014年MODIS高分辨率大气气溶胶卫星遥感产品对国控空气监测点位布设调整方案进行评估论证,通过提取2 km和5km半径范围的PM2.5遥感观测数据,与现有国控布设点位的地面监测数据进行相关性分析后,确定卫星产品用于评估验证是可靠的;通过不同天气场下PM2.5月均值浓度分布的比较,表明调整后空气点位布设具有很好的代表性.     

基于MODIS的乌梁素海“黄苔”监测预警系统

乌梁素海暴发的"黄苔"对其周边地区的生态、经济造成了严重的破坏,对"黄苔"进行监测预警对于改善湖区及周边地区的生态环境以及经济的可持续发展具有重要意义。以物联网的4层设计内涵思想为指导,构建了基于MODIS数据的乌梁素海"黄苔"监测预警系统,实现了"黄苔"监测预警平台的信息化与系统化。经验证,该模型的计算结果合理、可靠,基本达到了业务需要的精度。     

Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products

With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°× 0.25° and a temporal resolution of1 month was established based on the moderate resolution imaging spectroradiometer(MODIS) Thermal Anomalies/Fire Daily Level3 Global Product(MOD/MYD14A1). Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO_2, CO, CH_4,nonmethane volatile organic compounds(NMVOCs), N_2O, NO_x, NH_3, SO_2, fine particles(PM2.5),organic carbon(OC), and black carbon(BC) were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43,1.09, 0.34, and 0.06 Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June(37%).Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N_2O to a high of within ± 169% for NH_3.