亚洲沙尘暴的遥感监测方法研究 --以中国-日本合作研究区为例

介绍了亚洲沙尘暴遥感监测的一些新方法,并对监测结果与数据进行了综合分析,这些结果能够为GCM全球尺度沙尘模型提供参数和验证数据。本次研究结果为亚洲沙尘暴的中长期预测/预警系统提供了新的遥感技术方法。     

Geographically weighted regression‐based determinants of malaria incidences in northern China

Geographically weighted regression (GWR) is an important local method to explore spatial non‐stationarity in data relationships. It has been repeatedly used to examine spatially varying relationships between epidemic diseases and predictors. Malaria, a serious parasitic disease around the world, shows spatial clustering in areas at risk. In this article, we used GWR to explore the local determinants of malaria incidences over a 7‐year period in northern China, a typical mid‐latitude, high‐risk malaria area. Normalized difference vegetation index (NDVI), land surface temperature (LST), temperature difference, elevation, water density index (WDI) and gross domestic product (GDP) were selected as predictors. Results showed that both positively and negatively local effects on malaria incidences appeared for all predictors except for WDI and GDP. The GWR model calibrations successfully depicted spatial variations in the effect sizes and levels of parameters, and also showed substantially improvements in terms of goodness of fits in contrast to the corresponding non‐spatial ordinary least squares (OLS) model fits. For example, the diagnostic information of the OLS fit for the 7‐year average case is R² = 0.243 and AICc = 837.99, while significant improvement has been made by the GWR calibration with R² = 0.800 and AICc = 618.54.     

利用MODIS遥感影像获取近地层气温的方法研究

由于冠层叶片群体效应,在1km的空间尺度上遥感获取浓密植被陆面温度与气温近似相等。根据这个原理对利用遥感手段获取气温进行了尝试,提出利用NDVI-Ts空间获取气温的方法,计算气温空间分布模式,同时对Prihodko和Goward提出的气温遥感获取模型(简称P-G模型)进行试验并与NDVI-Ts空间法进行了对比。根据Parton和Logan提出的气温尺度转换模型,利用气象站观测最高气温和最低气温获取Terra卫星过境时刻气温作为“测定值”,对遥感获取的气温进行检验,得到以下结论:P-G模型计算气温与观测结果相比偏高,而NDVI-Ts法计算结果偏低,但是其总体误差范围相当,大约为 4℃;与P-G模型相比,尽管NDVI-Ts空间法获得的气温在精度上对P-G模型没有多大的改善,但这种方法能够更加充分利用遥感获取的信息,而且在计算机运算效率上也有很大的改进,NDVI-Ts空间法相对于P-G模型具有一定优势。     

改进型遥感生态指数与RSEI的对比分析

为了更好对城市生态质量进行监测和评价,构建一个更精确的城市遥感生态指数十分必要。本文结合绿度、湿度、干度、热度和空气质量指标采用主成分分析PCA（Principal Component Analysis） 构建改进型遥感生态指数MRSEI（Modified Remote Sensing Ecological Index）;利用熵权法计算压力—状态—响应模型PSR （Pressure State Response Model）中各指标的权重,通过加权法获得生态环境指数EI（Eco-environmental Index）与MRSEI和RSEI进行比较。同时,综合绿度、热度、湿度、干度指标利用核主成分分析KPCA（Kernel Principal Component Analysis）构建非线性遥感生态指数NRSEI（Nonlinear Remote Sensing Ecological Index）;最后将MRSEI、NRSEI分别与常用的遥感生态指数RSEI（Remote Sensing Ecological Index）进行对比和分析。结果表明,MRSEI可体现空气质量空间分布对城市生态质量的影响,2014年和2017年MRSEI与EI的相关系数分别是0.829和0.857（P<0.01）,比RSEI与EI的相关系数分别提高0.035和0.055。在主城区MRSEI和RSEI与EI比较结果表明,MRSEI的平均绝对误差、均方根误差和平均相对误差均小于RSEI,表明MRSEI更适用于城市生态质量评价,空气质量指标对北京市生态环境监测、评价是非常重要的。同时,在实验区KPCA第一主成分贡献率比PCA提高了11.94%—21.45%;各个指标与NRSEI相关系数比与RSEI提高了0.128—0.198;NRSEI可体现生态等级间的过渡,RSEI对生态环境差的区域有时低估,对生态环境优的区域有时高估,NRSEI与遥感影像定性反映的生态状况更加相符。在监测空气质量严峻的北京市生态质量方面,MRSEI优于RSEI;顾及各指标间的弱线性或非线性问题的NRSEI监测生态环境质量效果优于利用线性变换的RSEI。     

中国北方沙尘灾害特点及其下垫面状况的遥感监测

2000年春季,中国北方地区多次受到沙尘灾害的影响,对生产、生活活动造成了多方面的不利影响。采用遥感和GIS技术进行沙尘灾害的过程监测、空间特点分析和下垫面状况分析是一个有效的技术方法,通过对沙尘灾害发生、发展的环境条件的了解,可以减轻沙尘天气的危害、防治等一系列决策措施的制定、实施提供客观、及时的空间信息,有助于制定和实施区域生态环境保护措施,以便减少沙尘天气的次数和减轻灾害性天气的危害程度。     

中国北方沙尘灾害特点及其下垫面状况的遥感监测

2000年春季,中国北方地区多次受到沙尘灾害的影响,对生产、生活活动造成了多方面的不利影响。采用遥感和GIS技术进行沙尘灾害的过程监测、空间特点分析和下垫面状况分析是一个有效的技术方法,通过对沙尘灾害发生、发展的环境条件的了解,可以减轻沙尘天气的危害、防治等一系列决策措施的制定、实施提供客观、及时的空间信息,有助于制定和实施区域生态环境保护措施,以便减少沙尘天气的次数和减轻灾害性天气的危害程度。     

顾及地面传感器观测数据的遥感影像地面温度反演算法

针对遥感数据对地面温度反演精度低及地面温度传感器数据为点数据的特点,构建了融合地面温度传感器实时监测数据与遥感反演地面温度数据的协同反演方法体系。以HJ-1遥感影像的地表温度反演为例,提出了四种融合策略,通过分析比较得到四种结果。四种方案的融合结果的均方根误差分别从0.8848℃下降为0.6562℃、0.4288℃、0.4535℃、0.4261℃;相关系数分别从初始的0.6195提高到0.6343、0.8629、0.8507、0.8648。其中,方案④在增加地面点间隔的情况下,均方根误差能够保持在0.45℃以下,相关系数在0.85以上,并采用不同影像和实测数据进行相对验证。最后探讨了不同方案的特点,得出最优的融合方案,以达到对地表温度进行实时动态监测的目的。     

Atmospheric pollution assessment near potential source of natural aerosols in the South Gobi Desert region,China

ABSTRACT

Rapid economic growth, a high degree of urbanization and the proximity of a large number of desert and semidesert landscapes can have a significant impact on the atmosphere of adjacent territories, leading to high levels of atmospheric pollution. Therefore, identifying possible sources of atmospheric pollution is one of the main tasks. In this study, we carried out an analysis of spatial and temporal characteristics of five main atmospheric pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and CO) near potential source of natural aerosols, affecting seven cities (Wuhai, Alashan, Wuzhong, Zhongwei, Wuwei, Jinchang, Zhangye), located in immediate proximity to the South Gobi deserts. The results, obtained for the period from 1 January 2016 to 31 December 2018, demonstrate total concentrations of PM_2.5 and PM₁₀ are 38.2 ± 19.5 and 101 ± 80.7 μg/m³ exceeding the same established by the Chinese National Ambient Air Quality Standard (CNAAQS), being 35 and 70 μg/m³, respectively. Based on the data from Moderate Resolution Imaging Spectroradiometer (MODIS) for the whole period, Clean Сontinental (71.49%) and Mixed (22.29%) types of aerosols prevail in the region. In the spring and winter seasons maximum concentrations of pollutants and high values of Aerosol Optical Depth (AOD) in the region atmosphere are observed. PM_2.5 and PM₁₀ ratio shows the presence of coarse aerosols in the total content with value 0.43. The highest concentrations of pollutants were in the period of dust storms activity, when PM_2.5 and PM₁₀ content exceeded 200 and 1000 µg/m³, and AOD value exceeded 1. UV Aerosol Index (UVAI), Aerosol Absorbing Optical Depth (AAOD), and Single Scattering Albedo (SSA), obtained from Ozone Monitoring Instrument (OMI), demonstrate the high content of dust aerosols in the period of sandstorms. Analysis of backward trajectories shows that dust air masses moved from North to Northwest China, affecting large deserts such as Taklamakan, Gurbantunggut, Badain Jaran, Tengger, and Ulan Buh deserts.     

Understanding spatial variations of malaria in Vietnam using remotely sensed data integrated into GIS and machine learning classifiers

Abstract

This study examines the potentials of remotely sensed data, GIS and some machine learning classifiers and ensemble techniques in the investigation of the non-linear relationship between malaria occurrences and socio-physical conditions in the Dak Nong province of Viet Nam. Accuracy assessment was determined with Receiver Operating Characteristic (ROC) curve and pair t-test. The results showed that the area under ROC of Random Subspace ensemble model performed better than the other models based on statistical indicators. Comparing pair t-test with Area Under Curve values showed a slight difference of about 1%. Therefore ensemble techniques had significantly improved the performance of the base classifier. However, the performances might vary according to geographic locations. It is concluded that the machine learning classifiers combined with remotely sensed data and GIS is promising for malaria vulnerability mapping, and the derived maps can be used as a fundamental basis for programmes on spatial disease control.     

北京市污染气溶胶散射特征实验及其数值模拟

用地基遥感方法对北京市主要大气污染类型的气溶胶散射进行多角度观测实验，对比分析不同污染类型，及在不同观测角度下污染气溶胶的散射特征；并建立对各类型污染气溶胶散射率进行了数值模拟的数学模型。在此基础上求出观测时污染气溶胶的混浊度。为污染气溶胶的卫星遥感打下基础。     

北京市污染气溶胶散射特征实验及其数值模拟

用地基遥感方法对北京市主要大气污染类型的气溶胶散射进行多角度观测实验，对比分析不同污染类型，及在不同观测角度下污染气溶胶的散射特征；并建立对各类型污染气溶胶散射率进行了数值模拟的数学模型。在此基础上求出观测时污染气溶胶的混浊度。为污染气溶胶的卫星遥感打下基础。     

Malaria incidence in Nairobi,Kenya and dekadal trends in NDVI and climatic variables

The primary objective of this research was to determine if the remotely-sensed metric, Normalised Difference Vegetation Index (NDVI) and ground-collected dekadal climatological variables were useful predictors of future malaria outbreaks in an epidemic-prone area of Nairobi, Kenya. Data collected consisted of 36 dekadal (10-day) periods for the variables rainfall, temperature and NDVI along with yearly documented malaria admissions in 2003 for Nairobi, Kenya. Linear regression models were built for malaria cases reported in Nairobi, Kenya, as the dependent variable and various time-based groupings of temperature, rainfall and NDVI data from the dekads in both the current and the previous month as the independent variables. Data from 2003 show that malaria incidence in any given month is best predicted (R²  = 0.881, p < 0.001) by the average NDVI for the 30 days including the final two dekads of the previous month and first dekad of the current month, and by the average rainfall for the 30 days including the three dekads of rainfall data from the prior month. Forecasting an outbreak in an epidemic zone would allow public health entities to plan for and disseminate resources to the general public such as antimalarials and insecticide impregnated bed nets. In addition, vector control measures could be implemented to slow the rate of transmission in the impacted population.     

近海岸悬浮泥沙遥感反演模型的分析探讨

简要介绍了国内外近海岸悬浮泥沙定量化遥感反演的研究进展及悬浮泥沙遥感反演模型的建立方法,通过对国内外近年研究的部分悬浮泥沙遥感反演模型进行简单分类、对比分析得出其优缺点,并针对部分悬浮泥沙遥感反演模型的不足和目前遥感技术在悬浮泥沙定量反演中的应用提出了一些肤浅见解。     

航空遥感地表温度时间归一化

航空热红外遥感影像的航带宽度一般较为有限,通常需要进行连续飞行获得多个航带才能覆盖一个较大的研究区;由于地表温度随时间变化迅速,不同航带间地表温度存在差异。因此,进行不同航带影像拼接之前,需要对不同航带的地表温度进行时间归一化。本文基于温度日变化模型,构建了航空遥感地表温度时间归一化方法;结合Hi WATER试验区高密度的气象观测数据,分析了天气晴朗条件下,风速的大小和波动剧烈程度对地表温度日变化模型的影响,在此基础上发展了一种考虑风速影响的改进温度日变化模型。验证结果表明:两种模型均能够减小观测时间不同导致的地表温度瞬时波动差异;考虑风速影响的改进模型比未改进模型的精度提高0.3—0.6 K,且其提供的地表温度在时间尺度变化上更加符合实际情况。本研究建立的相关模型对于卫星遥感地表温度的时间归一化也具有借鉴意义。     

城市目标方向亮温观测的视场效应分析

基于简化的城市目标三维结构模型,利用计算机图形学中辐射度方法,对城市目标的热辐射方向性规律进行模拟。在传感器分别位于近地面和卫星轨道时,研究了城市目标各组分在视场内的权重随观测天顶角、方位角和观测距离改变的变化规律。结果表明:城市目标方向亮温地面辐射测量存在显著视场效应。当传感器位于近地面时,在垂直太阳主平面附近,视场效应达到最大。方向亮温随观测距离的改变有明显变化。随着观测距离的增加,视场效应急剧减小。将近地面测量得到的方向亮温与卫星影像计算所得的方向亮温对比时,视场效应是一个必须考虑的因素。     

稀疏植被净初级生产力时空变化及气象因素关系分析

本文探讨了2001-2018年古尔班通古特沙漠植被NPP时空格局,基于改进的CASA模型,采用空间分析、相关性分析及地理探测器模型等方法,揭示了研究区NPP气候驱动因子及其影响。结果表明:①古尔班通古特沙漠近18年植被NPP变化总体呈现波动增加趋势,增速为0.56 gC· a^-1,NPP均值为46.90 gC· m^-2· a^-1;②2001-2018年,年均NPP整体呈西低东高、北低南高的空间分布格局,但从动态上而言,基本呈现沙漠腹地较稳定、四周较活跃的格局;③古尔班通古特沙漠植被NPP主要受降水因子的影响,与降水、气温因子均呈正相关关系,从各因子驱动力分析而言,降水因子(0.614 4)为限制荒漠植被生长的主导因素。     

高分辨率遥感测绘嵩山实验场的设计与实现——兼论航空航天遥感定位精度与可靠性的基地化验证方法

以高精度地面基准为参照对遥感定位各种可能的影响要素进行整体性、定量化的验证、分析与评估,显然是一种合理、有效、可信、可行的方式。这里针对实际应用需求,重点介绍嵩山高精度遥感测绘综合实验场的设计思路与实现情况,并对遥感定位精度与可靠性实验场验证的基地化方法进行了探讨与分析。     

云下地表温度与辐射变化关系的定量分析

云下对地表温度一直是热红外遥感研究的难点,云下地表温度的变化不仅受到到达地表的辐射强度的影响,还与地表覆盖类型的热力学性质有关,本文通过开展野外观测实验,并利用地表能量平衡模型模拟地表温度在不同辐射条件的变化情况,以期获得不同地表类型的地表温度与辐射变化的定量关系,结果表明,在云覆盖情况下,到达地表面的辐射值减小,地表温度也随之减小,当云覆盖前地表温度越高,云覆盖后地表温度的变化幅度就越大,不同地表类型的云下地表温度在单位时间(min)内发生的温度值的单位变化量所需辐射值的变化量与云覆盖前温度高低呈线性关系。在长时间云覆盖情况下,地表温度的下降速度随着云覆盖时间的增加而不断放缓,当云层覆盖一定时间(10—20 min)后,地表温度会达到一个相对稳定的状态。     

天然草地牧草产量遥感综合监测预测模型研究

利用天然草地牧草光谱观测资料、牧草产量资料、气象资料和NOAA／AVHRR资料，建立了天然草地牧草产量光谱植被指数和卫星遥感监测模型、气监测模型，提供及时准确地掌握牧草产量变化的科学手段。建立了天然草地牧草产量遥感预测模型及气象预测模型，可以根据需要提供不同时效的卫星遥感预测结果和气象模型预测结果。气象模型精度较高，但气象站点有限，往往以点代面；遥感技术宏观性强，空间信息丰富，可以弥补气象模型的不足；两者既可以互相验证，又可以取长补短。1995年以后服务表明，这些模型达到牧业气象业务服务的要求。