南京市地表参数变化与热岛效应时空分析

利用南京市1989年TM和2001年、2010年ETM+卫星遥感数据,提取了3个时期的归一化植被指数(normalized difference vegetation index,NDVI)、改进的归一化水体指数(modified normalized difference water index,MNDWI)、归一化建筑指数(normalized difference build-up index,NDBI)和归一化不透水面指数(normalized difference impervious surface index,NDISI)等地表参数;利用热红外波段遥感数据反演地表温度,并从时间维对比分析了3个时期各个参数的变化和产生的原因;利用回归分析方法探讨了上述地表参数变化与城市地表温度之间的关系,即地表温度与NDISI和NDBI呈正相关,与NDVI呈负相关。进一步分析表明,南京市最近20 a来不透水面和建筑面积大幅增大,植被覆盖范围减少,城市热岛效应加剧,不透水面、建筑指数与地表温度的变化趋势和城市扩张趋势一致。该研究成果对于揭示南京市热岛效应、优化土地配置和推进生态城市建设具有一定的参考意义。     

基于CASI数据的黑河绿洲区叶面积指数反演

叶面积指数(leaf area index,LAI)作为植被冠层的重要参数,对作物长势监测及产量估算具有重要意义。本研究以黑河流域张掖绿洲试验区为例,基于机载航空高光谱遥感影像(compact airborne spectrographic imager,CASI)数据,利用物理模型与统计模型对研究区的LAI进行估测反演。首先,利用归一化植被指数(normalized difference vegetation index,NDVI)与相应实测LAI数据建立最佳线性回归模型;然后,基于混合像元分解模型和多次散射植被冠层模型构建物理模型;最后,以线性回归模型为参比修正多次散射植被冠层模型,构建半经验LAI反演模型,并比较上述模型拟合效果。研究结果表明,半经验模型为绿洲区LAI反演最优模型,模型估算精度R2达到0.89,精度提高较显著。研究对提升作物LAI的估算精度有一定意义,并将进一步推动精细农业定量遥感理论的研究与应用。     

基于生态参数的岩溶峰丛区石灰岩基岩表面溶蚀率遥感反演

为了探索岩溶峰丛区生态参数与石灰岩基岩表面溶蚀率的相关性,用相关生态参数反演土层下石灰岩基岩表面的溶蚀率,从而间接估算其变形。选择桂林丫吉村岩溶峰丛区为研究区,以Landsat5 TM多光谱数据为信息源,提取归一化差值植被指数(normalized difference vegetation index,NDVI)、地面温度及土壤湿度等遥感参数;运用SPSS统计软件对这3种参数分别与石灰岩溶蚀率进行了相关分析,确定其相关系数分别为-0.91,0.85及0.93;在此基础上,通过逐步回归分析,建立了运用NDVI估算植被覆盖下石灰岩表面溶蚀率的遥感反演模型。结果表明:NDVI与石灰岩溶蚀率相关性最大,所以植被信息是石灰岩表层基岩溶蚀的主要间接标志;溶蚀率与NDVI指数存在线性关系,因此只要已知研究区其他地区的NDVI指数,即可估算出该地区的石灰岩基岩表面溶蚀率。     

基于物候信息的山东省冬小麦长势遥感监测

作物长势监测是农情监测的核心内容之一,处在不同生育期的作物长势存在显著差异。为了提高大范围作物长势遥感监测的精度,利用2001―2015年间获取的MOD09A1数据,以山东省冬小麦为研究对象,在逐年提取冬小麦抽穗期基础上,探讨研究区近15 a间冬小麦抽穗期长势时空格局。研究表明,与归一化差值植被指数(normalized difference vegetation index,NDVI)相比,基于增强型植被指数(enhanced vegetation index,EVI)提取的冬小麦抽穗期与地面观测数据有更好的一致性。研究区冬小麦抽穗期主要集中在4月中、下旬,并从南向北、自西向东逐渐推迟;与NDVI,EVI和归一化差值红外指数(normalized difference infrared index,NDII)相比,产品改进–NDVI(product improve–NDVI,PI_NDVI)更能反映冬小麦的实际长势。基于该指数监测冬小麦长势,2001―2015年间山东省冬小麦抽穗期长势整体呈上升趋势;但年际间波动较大,相同年份不同区域的冬小麦长势存在明显差异;而大部分区域长势状况比较一致,与多年平均状况持平。研究结果与已有的相关研究较为一致,基于遥感进行大范围和长时间作物长势监测的思路可以为以后研究提供一定的参考。     

林火烈度遥感评估指数适应性分析

科学合理地定量评估林火烈度,对揭示林火干扰下森林生态系统的变化,以及植被的恢复与管理具有重要意义。以美国科罗拉多大峡谷国家公园北缘的Poplar Fire为实验区,利用Landsat5 TM影像,结合实地调查的综合火烧指数(composite burn index,CBI),分析评价了归一化差值植被指数(normalized difference vegetation index,NDVI),归一化火烧指数(normalized burn ration,NBR),差分归一化植被指数(differenced normalized difference vegetation index,ΔNDVI)和差分归一化火烧指数(differenced normalized burn ration,ΔNBR)4种遥感指数对林火烈度评估的适应性。结果表明,4种遥感指数对识别不同等级林火烈度存在一定的差异。在未过火区和轻度火灾区,单一遥感指数的精度略高于差分遥感指数,其中NBR的提取精度最高,分别达到了66.7%和80%;在中度火灾区和重度火灾区,差分遥感指数的精度高于单一遥感指数,ΔNBR的提取精度最高,分别达到了100%和90%。总体上,基于差分遥感指数的林火烈度制图精度总体高于单一遥感指数,其中ΔNBR的总体制图精度最高,达到了86.2%。因此,ΔNBR是林火烈度分析与评估的适宜遥感指数。     

基于决策树方法的Landsat8 OLI影像红树林信息自动提取

基于广西山口国家红树林生态自然保护区的Landsat 8 OLI影像数据,选用广泛应用于植被液态水含量反演的归一化差值湿度指数(normalized difference moisture index,NDMI)和修正的归一化差值池塘指数(modified normalized difference pond index,MNDPI)作为分类特征,运用决策树方法进行红树林信息的自动提取。研究结果表明:红树林独特的滨海湿地生境特点,使其光谱同时包含植被和湿地信息;MNDPI和NDMI可分别反映可见光-近红外波段反射率同短波红外波段反射光谱的反差,可成功应用于湿地植被信息的提取,能有效地将红树林同其他地物相区分;采用Landsat8 OLI遥感数据,并结合NDMI和MNDPI分类特征构建的决策树模型可有效地提取红树林信息,其错分率和漏分率都较低,分别为5.34%和1.69%。     

GPS反射信号信噪比与NDVI相关性研究

归一化植被指数（normalized difference vegetation index,NDVI）作为重要的植被生长状况植被指数,对其进行有效实时监测具有重要科学意义。选择4个大陆板块边界观测网（plate boundary observatory,PBO）观测站的GPS信噪比观测值,提取反射信号信噪比并计算归一化振幅,通过与MODIS（moderate resolution imaging spectroradiometer）NDVI产品时序频谱特征的相关性分析,建立GPS反射信号植被指数线性反演模型和BP神经网络反演模型。分析发现:GPS反射信号信噪比归一化振幅与NDVI指数存在显著年周期性和季候特性,NDVI线性反演模型相关系数均约为0.7,均方根误差处于0.05~0.09之间,BP神经网络反演模型相关系数提高了约5%。利用GPS反射信号反演NDVI变化趋势具有可行性,为获取高时间分辨率、低成本的NDVI指数提供了一种新思路。     

基于地形调节植被指数估算长汀县植被覆盖度

植被覆盖度遥感估算最常用的方法是基于植被指数构建模型,但大部分的植被指数没有考虑地形的影响。以福建省长汀县作为研究区,引入能消除地形影响的地形调节植被指数(topography adjusted vegetation index,TAVI),利用像元二分模型估算植被覆盖度,旨在研究TAVI对植被覆盖度估算结果的影响,并与基于归一化差值植被指数(normalized difference vegetation index,NDVI)估算的结果进行比较。根据目视效果和统计指标的分析表明:基于TAVI估算的植被覆盖度精度高于基于NDVI的估算结果,并能有效降低阴坡阳坡间的差异,提高阴坡区域植被覆盖度的估算精度。     

基于MODIS的城市大气颗粒物污染指数研究

遥感特征指数法是一种简单、高效的信息提取方法。根据气溶胶散射或吸收引起的卫星不同波段间表观反射率变化,构建了基于MODIS的城市大气颗粒物污染指数,结合石家庄市各环境空气质量站实测颗粒物浓度数据,分析差值植被指数(difference vegetation index,DVI)、归一化灰霾指数(normalized difference haze index,NDHI)、归一化建筑指数(normalized difference built-up index,NDBI)和差值建筑指数(difference built-up index,DBI)与PM10之间的相关关系。结果表明,除NDHI外,DVI,NDBI和DBI与大气颗粒物质量浓度均呈现负相关关系,DBI与PM10之间线性相关关系较为明显,综合多种大气颗粒物污染指数构建的大气颗粒物质量浓度估算模型,可以用来简便、快速地指示城市大气颗粒物污染状况。     

兰西城市群热环境格局多尺度研究

从不同空间尺度研究城市热环境的变化格局,可为城市人居环境建设提供科学参考。采用MODIS和Landsat TM/OLI/TIRS遥感影像反演地表温度(land surface temperature,LST),分别从宏观和微观尺度探索了兰西城市群热场的空间格局特征,分析了城市热岛效应在昼夜、季节和年份等不同时间尺度上的分布格局及变化特征。研究结果表明,大尺度下兰西城市群未存在明显的城市热岛效应,但中心城区内热岛效应的空间格局发生了较大变化,热场的空间格局及演变与城市空间扩展布局相一致;兰州中心城区热岛比例指数呈现先增加后减小的变化趋势,西宁—海东中心城区热岛比例指数则呈现持续增长的态势;河谷地段的LST低于周围黄土丘陵,主要受植被覆盖、太阳辐射时间和接收量的影响;LST与归一化差值植被指数(normalized difference vegetation index,NDVI)呈负相关关系,与归一化差值建筑用地指数(normalized difference building index,NDBI)呈正相关关系。     

Spectra and vegetation index variations in moss soil crust in different seasons,and in wet and dry conditions

Similar to vascular plants, non-vascular plant mosses have different periods of seasonal growth. There has been little research on the spectral variations of moss soil crust (MSC) over different growth periods. Few studies have paid attention to the difference in spectral characteristics between wet MSC that is photosynthesizing and dry MSC in suspended metabolism. The dissimilarity of MSC spectra in wet and dry conditions during different seasons needs further investigation. In this study, the spectral reflectance of wet MSC, dry MSC and the dominant vascular plant (Artemisia) were characterized in situ during the summer (July) and autumn (September). The variations in the normalized difference vegetation index (NDVI), biological soil crust index (BSCI) and CI (crust index) in different seasons and under different soil moisture conditions were also analyzed. It was found that (1) the spectral characteristics of both wet and dry MSCs varied seasonally; (2) the spectral features of wet MSC appear similar to those of the vascular plant, Artemisia, whether in summer or autumn; (3) both in summer and in autumn, much higher NDVI values were acquired for wet than for dry MSC (0.6 ∼ 0.7 vs. 0.3 ∼ 0.4 units), which may lead to misinterpretation of vegetation dynamics in the presence of MSC and with the variations in rainfall occurring in arid and semi-arid zones; and (4) the BSCI and CI values of wet MSC were close to that of Artemisia in both summer and autumn, indicating that BSCI and CI could barely differentiate between the wet MSC and Artemisia.     

RNDSI: A ratio normalized difference soil index for remote sensing of urban/suburban environments

Understanding land use land cover change (LULCC) is a prerequisite for urban planning and environment management. For LULCC studies in urban/suburban environments, the abundance and spatial distributions of bare soil are essential due to its biophysically different properties when compared to anthropologic materials. Soil, however, is very difficult to be identified using remote sensing technologies majorly due to its complex physical and chemical compositions, as well as the lack of a direct relationship between soil abundance and its spectral signatures. This paper presents an empirical approach to enhance soil information through developing the ratio normalized difference soil index (RNDSI). The first step involves the generation of random samples of three major land cover types, namely soil, impervious surface areas (ISAs), and vegetation. With spectral signatures of these samples, a normalized difference soil index (NDSI) was proposed using the combination of bands 7 and 2 of Landsat Thematic Mapper Image. Finally, a ratio index was developed to further highlight soil covers through dividing the NDSI by the first component of tasseled cap transformation (TC1). Qualitative (e.g., frequency histogram and box charts) and quantitative analyses (e.g., spectral discrimination index and classification accuracy) were adopted to examine the performance of the developed RNDSI. Analyses of results and comparative analyses with two other relevant indices, biophysical composition index (BCI) and enhanced built-up and bareness Index (EBBI), indicate that RNDSI is promising in separating soil from ISAs and vegetation, and can serve as an input to LULCC models.     

基于TM图像的“增强的指数型建筑用地指数”研究

以Landsat TM/ETM+图像为数据源,研究城镇和农村建筑用地信息的提取方法.首先利用TM7,4,2波段创建归一化差值裸地与建筑用地指数(normalized difference bareness and built- up index,NDBBI);然后根据裸地在裸土指数(bare doil index,BSI)图像上的亮度值最高、在改进型归一化差值水体指数(modified normalized difference water index,MNDWI)图像的亮度值最低的特征,提出了增强型裸土指数(enhanced baresoilindex,EBSI);最后选用NDBBI,EBSI,MNDWI和SAVI( soil adjustment vegetation index,SAVI)4个指数,构建一种新型的建筑用地指数,称为“增强的指数型建筑用地指数”( enhanced index - based built - up index,EIBI),可快速地提取建筑用地信息.实验结果表明,用EIBI提取的建筑用地信息客观,人为干预少,可信度高,提取精度可达90％以上,适合于同时提取城市和农村建筑用地信息.     

基于TM数据的植被覆盖度反演

本文首先对TM影像进行了几何纠正、辐射校正、大气校正;然后根据混合像元的结构特征,利用TM数据从植被指数(NDVI)中采用“等密度模型”和“非密度模型”提取了宜昌南部地区的植被覆盖度。在用“非密度模型”反演植被覆盖度的过程中,叶面积指数(LAI)是一个必要的参数,本文提出了一种改进的借助可见光波段和近红外波段反射值来提取叶面积指数(LAI)的方法。通过和MODIS数据反演结果比较表明:“非密度模型”的估算精度要高于“等密度模型”;利用“等密度模型”和“非密度模型”反演植被覆盖度是可行。     

城市地表典型遥感参数与热岛效应时空分析研究——以桂林市为例

利用桂林市1991年和2013年的卫星遥感影像数据,分别提取两个时期的归一化建筑指数(NDBI)、归一化植被指数(NDVI)和改进的归一化差异水体指数(MNDWI)3个地表典型参数,并利用回归分析方法,分析了3个地表典型参数与利用Landsat卫星(热红外波段)反演的地表温度(LST)的相关关系。研究结果表明:桂林市中、高、极高温区3个温度类别的变化趋势与桂林市城市扩张趋势基本一致;NDBI与LST成显著的正相关关系,而NDVI、MNDWI则与LST成负相关关系,且各参数对地表温度响应的程度各有差异。该研究成果对于揭示桂林市热岛效应现状、缓解热岛效应及推进桂林市生态城市建设具有一定的参考意义。     

Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area.     

利用多时相的高光谱航空图像监测冬小麦条锈病

冬小麦发生锈病 ,叶绿素被大量破坏 ,水分蒸滕量大大增加 ,叶片细胞大小、形态、叶片结构发生了改变 ,从而改变了叶片和冠层的光学特性 ,使得遥感探测与评价成为可能。利用多时相的高光谱航空飞行图像数据 ,了解、分析和发现条锈病病害对作物光谱的影响及其光谱特征 ;设计了病害光谱指数 ,成功地监测了冬小麦条锈病病害程度与范围。对比 3个生育期的条锈病与正常生长冬小麦的PHI图像光谱及光谱特征 ,发现 :5 6 0— 6 70nm黄边、红谷波段 ,条锈病病害冬小麦的冠层反射率高于正常生长的冬小麦光谱反射率 ;近红外波段 ,条锈病病害的冠层反射率低于正常生长的冬小麦光谱反射率 ;条锈病冬小麦冠层光谱红谷吸收深度和绿峰的反射峰高度都会减小     

Seasonal trend analysis (STA) of MODIS vegetation index time series for the mangrove canopy of the Teacapan-Agua Brava lagoon system,Mexico

Monthly time series, from 2001 to 2016, of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from MOD13Q1 products were analyzed with Seasonal Trend Analysis (STA), assessing seasonal and long-term changes in the mangrove canopy of the Teacapan-Agua Brava lagoon system, the largest mangrove ecosystem in the Mexican Pacific coast. Profiles from both vegetation indices described similar phenological trends, but the EVI was more sensitive in detecting intra-annual changes. We identified a seasonal cycle dominated by Laguncularia racemosa and Rhizophora mangle mixed patches, with the more closed canopy occurring in the early autumn, and the maximum opening in the dry season. Mangrove patches dominated by Avicennia germinans displayed seasonal peaks in the winter. Curves fitted for the seasonal vegetation indices were better correlated with accumulated precipitation and solar radiation among the assessed climate variables (Pearson’s correlation coefficients, estimated for most of the variables, were r ≥ 0.58 p < 0.0001), driving seasonality for tidal basins with mangroves dominated by L. racemosa and R. mangle. For tidal basins dominated by A. germinans, the maximum and minimum temperatures and monthly precipitation fit better seasonally with the vegetation indices (r ≥ 0.58, p < 0.0001). Significant mangrove canopy reductions were identified in all the analyzed tidal basins (z values for the Mann-Kendall test ≤ ?1.96), but positive change trends were recorded in four of the basins, while most of the mangrove canopy (approximately 87%) displayed only seasonal canopy changes or canopy recovery (z > ?1.96). The most resilient mangrove forests were distributed in tidal basins dominated by L. racemosa and R. mangle (Mann-Kendal Tau t ≥ 0.4, p ≤ 0.03), while basins dominated by A. germinans showed the most evidence of disturbance.     

Retrieval of Brown Carbon based on the aerosol complex refractive indices in the winter of Wuhan

Abstract

The impact of Brown Carbon (BrC) to aerosol light absorption has been paid more attention recently and there are a large number of studies showing that the influence of BrC on radiative forcing should not be ignored. BrC also acts as an important component of haze pollution which is occurring frequently in Wuhan, China. Therefore, it is essential to estimate their optical properties, composition, and mass concentration. Considering most haze pollution happens during the coldest time, we retrieved BrC columnar content during winter in Wuhan for the first time. Our method bases on the fact that BrC showed the strong spectral dependence on UV-light absorption. Using this method, we found that BrC makes up the small proportions of total aerosol volume (less than 10%). In the winter of 2011, we retrieved the daily-averaged columnar-integrated mass concentration of BrC on clear day is 4.353 mg/m² while that of haze day is 12.750 mg/m². According to the sensitivity study, we found that the results highly relied on the assumed aerosol refractive index. To reduce the uncertainty of this approach, we need to gain a better understanding of the temporal variability of the radiation absorbing components of these aerosols in the future.