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1.
Developing techniques are required to generate agricultural land cover maps to monitor agricultural fields. Landsat 8 Operational Land Imager (OLI) offers reflectance data over the visible to shortwave-infrared range. OLI offers several advantages, such as adequate spatial and spectral resolution, and 16 day repeat coverage, furthermore, spectral indices derived from Landsat 8 OLI possess great potential for evaluating the status of vegetation. Additionally, classification algorithms are essential for generating accurate maps. Recently, multi-Grained Cascade Forest, which is also called deep forest, was proposed, and it was shown to give highly competitive performance for classification. However, the ability of this algorithm to generate crop maps with satellite data had not yet been evaluated. In this study, the reflectance at 7 bands and 57 spectral indices calculated from Landsat 8 OLI data were evaluated for its potential for crop type identification.  相似文献   

2.
北京地区Landsat 8 OLI高空间分辨率气溶胶光学厚度反演   总被引：3，自引：0，他引：3  
卫星气溶胶光学厚度(AOD)反演中,传统暗目标方法在反射率较低的水体、浓密植被覆盖区域取得了较好效果,在反射率较高且结构复杂的高反射地表上空目前多采用深蓝算法,但存在空间分辨率较低,对细节分布描述性较差等问题。为解决这一问题,本文首先以5年(2008年—2012年)长时间序列MODIS地表反射率产品为基础,采用最小值合成法建立500 m分辨率逐月地表反射率产品数据集,然后利用地物波谱库中典型地物波谱数据,分析建立MODIS与Landsat 8 OLI传感器蓝光波段反射率转换模型,最后北京地区AERONET地基观测数据确定了气溶胶光学物理参数,并反演获取了北京地区上空500 m分辨率的AOD分布。为验证反演算法的精度,分别将反演结果同AERONET及MODIS/Terra气溶胶产品(MOD04)进行交叉对比,同时利用相关系数R,均方根误差RMSE,平均绝对误差MAE以及MODIS AOD产品预期误差EE共4个指标进行衡量。结果表明:算法反演获取的AOD与AERONET观测值具有较高的一致性,各指标分别为R=0.963,RMSE=0.156,MAE=0.097,EE=85.3%,稍优于MOD04产品(R=0.962,RMSE=0.158,MAE=0.101,EE=75.8%),并且有效的对比点数也高于MOD04。通过与地基观测相比,卫星遥感获取的高分辨率城市地区AOD精度可作为定量评估城市空气质量的有效依据。  相似文献   

3.
Sentinel-2A与Landsat 8O LI逐像元辐射归一化方法研究   总被引：1，自引：0，他引：1  
考虑不同传感器光谱响应函数差异及不同地物类型反射率光谱的差异,提出了一种逐像元辐射归一化方法,并以2017年7月17日内蒙古达里诺尔湖地区准同步过境的Sentinel-2A及Landsat 8数据为例,对两类数据可见-近红外波段（VNIR）地表反射率结果进行归一化。首先采用Sen2cor方法及NASA官方提供大气校正算法,分别对Sentinel-2A及Landsat 8 OLI影像进行大气校正并重采样到同一空间分辨率;然后基于光谱库计算匹配因子并构建图像与光谱库之间的匹配转换模型,实现像元尺度上从Sentinel-2影像到Landsat 8影像地表反射率相似波段之间的转换。结果表明,经逐像元归一化的影像相比原始影像及经HLS光谱归一化的影像,与Landsat 8 VNIR波段的相关性明显提高,辐射一致性增强。该转换模型为多源中高分辨率遥感图像高精度辐射归一化提供了新思路。  相似文献   

4.
黄河口水体光谱特性及悬沙浓度遥感估测   总被引：10，自引：1，他引：10  
通过黄河口含沙水体野外遥感光谱反射率的观测实验，探讨了黄河口水体表观光谱特性，分析了悬浮体中有机颗粒含量和悬沙粒度对光谱特性的影响。针对Landsat TM／ETM^＋影像波段特性，对黄河口含沙水体在其可见光至近红外4个波段的光谱特性进行了模拟分析，并结合表观光谱观测数据建立了经验回归函数，以估测不同时相黄河口水体表层悬沙的浓度。  相似文献   

5.
Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross–Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.  相似文献   

6.
The operational land imager (OLI) is the latest instrument in the Landsat series of satellite imagery, which officially began normal operations on 30 May 2013. The OLI includes two bands that are not on the thematic mapper series of sensors aboard Landsat-5 and 7; a cirrus band and a coastal/aerosol band. This paper compares the classification and regression tree and the kernel-based extreme learning machine (KELM) for mapping crops in Hokkaido, Japan, using OLI data, except the cirrus band and the pan band. The OLI data acquired on 8 July 2013 was used for crop classification of beans, beets, grassland, maize, potatoes and winter wheat. The KELM algorithm performed better in this study and achieved overall accuracies of 90.1%. According to the Jeffries–Matusita (J–M) distances, the short wavelength infrared band provides the greater contribution (the highest value was observed for band 6 in OLI data).  相似文献   

7.
A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data.  相似文献   

8.
高分一号卫星(GF-1)WFV相机是中国新型高分辨率传感器,为了更好地进行定量应用,需完成高精度大气校正,但需要解决数量大,辅助数据不足等关键问题。针对WFV相机构建了快速大气校正模型,(1)采用交叉定标方法借助Landsat 8数据完成辐射定标;(2)从WFV相机的辅助数据出发,计算得到太阳天顶角、观测天顶角等辅助信息;(3)考虑不同海拔大气分子散射的不同,完成基于海拔数据的分子散射校正;(4)采用深蓝算法,从第一波段(蓝光)反演得到气溶胶信息;(5)计算每个像元的大气校正参数,进而获取地表反射率,完成大气校正。在此基础上,利用IDL语言建立相应的大气校正模块,以过境华北地区的3景WFV数据为例进行大气校正实验。结果表明,模型能够快速完成大气校正,并能较好的去除大气分子与气溶胶影响,较好地还原植被、裸土等典型地表类型的光谱反射曲线,校正后的NDVI更好地反映了各地物的特征。  相似文献   

9.
云遮挡对高光谱影像的应用造成了不可忽视的影响。现有云去除方法通常利用时域近邻的同源影像提供辅助信息。然而,高光谱影像(如GF-5和EO-1高光谱影像)较低的时间分辨率导致同源辅助影像中可能存在较大的地物覆盖变化。时间分辨率更高的多光谱影像(如Landsat 8 OLI影像)能提供时间上更接近于高光谱云影像的辅助信息,从而减少地物覆被变化带来的影响。为应对高光谱和多光谱波段之间差异较大的问题,本文基于空谱随机森林(spatial-spectral-based random forest,SSRF)方法,提出一种利用多光谱影像(Landsat 8 OLI影像)对高光谱影像进行厚云去除的方法,将其简记为SSRF_M。SSRF_M较强的非线性拟合能力使其能够综合利用多光谱影像所有波段的有效数据对各个高光谱波段进行重建。本文使用GF-5和EO-1高光谱影像进行模拟云去除试验,视觉和定量评价结果均表明,与利用时间间隔更长的同源辅助影像的方法相比,本文方法能获得更高精度的云下信息重建结果。  相似文献   

10.
Landsat系列卫星对地观测40年回顾及LDCM前瞻   总被引：7，自引：0，他引：7  
姜高珍  韩冰  高应波  杨崇俊 《遥感学报》2013,17(5):1033-1048
Landsat系列卫星数据凭借其长期连续、全球覆盖、适中的时间空间分辨率和科学的数据存档与分发策略等优势,逐渐成为地表特征和地球系统科学研究中最有效的遥感数据之一,并广泛应用于生态环境、农林地矿、能源资源、教育科研和政府管理等领域。而第8代陆地卫星--陆地卫星数据连续任务卫星(LDCM)于2013年2月发射升空,该卫星携带了运行性陆地成像仪(OLI)和热红外传感器(TIRS)两种传感器。与Landsat 7/ETM+相比,OLI/TIRS在波段设置、辐射分辨性能和扫描方式上都得到很大改进,其中OLI共包括9个波段,新增海岸带(coastal)监测和卷云(cirrus)识别波段,TIRS则设置了两个热红外波段。如果LDCM能够成功升空运行,它将继续承担起长期连续对地观测的使命。  相似文献   

11.
The successful launch of Landsat 8 provides a new data source for monitoring land cover, which has the potential to significantly improve the characterization of the earth’s surface. To assess data performance, Landsat 8 Operational Land Imager (OLI) data were first compared with Landsat 7 ETM + data using texture features as the indicators. Furthermore, the OLI data were investigated for land cover classification using the maximum likelihood and support vector machine classifiers in Beijing. The results indicated that (1) the OLI data quality was slightly better than the ETM + data quality in the visible bands, especially the near-infrared band of OLI the data, which had a clear improvement; clear improvement was not founded in the shortwave-infrared bands. Moreover, (2) OLI data had a satisfactory performance in terms of land cover classification. In summary, OLI data were a reliable data source for monitoring land cover and provided the continuity in the Landsat earth observation.  相似文献   

12.
The overarching aim of this study was to derive simple and accurate algorithms for the retrieval of water quality parameters for the Wular Lake using Landsat 8 OLI satellite data. The water quality parameters include pH, COD, DO, alkalinity, hardness, chloride, TDS, total suspended solids (TSS), turbidity, electric conductivity and phosphate. Regression analysis was performed using atmospherically corrected true reflectance values of original OLI bands, images after applying enhancement techniques (NDVI, principal components) and the values of the water quality parameters at different sample locations to obtain the empirical relationship. Most of the parameters were well correlated with single OLI bands with R2 greater than 0.5, whereas phosphate showed a good correlation with NDVI image. The parameters like pH and DO showed a good relation with the principal component I and IV, respectively. The high concentration of pH, COD, turbidity and TSS and low concentration of DO infers the anthropogenic impact on lake.  相似文献   

13.
Remote sensing has been proven promising in wetland mapping. However, conventional methods in a complex and heterogeneous urban landscape usually use mono temporal Landsat TM/ETM + images, which have great uncertainty due to the spectral similarity of different land covers, and pixel-based classifications may not meet the accuracy requirement. This paper proposes an approach that combines spatiotemporal fusion and object-based image analysis, using the spatial and temporal adaptive reflectance fusion model to generate a time series of Landsat 8 OLI images on critical dates of sedge swamp and paddy rice, and the time series of MODIS NDVI to calculate phenological parameters for identifying wetlands with an object-based method. The results of a case study indicate that different types of wetlands can be successfully identified, with 92.38%. The overall accuracy and 0.85 Kappa coefficient, and 85% and 90% for the user’s accuracies of sedge swamp and paddy respectively.  相似文献   

14.
The present work evaluates the applicability of operational land imager (OLI) and thermal infrared sensor (TIRS) on-board Landsat 8 satellite. We demonstrate an algorithm for automated mapping of glacier facies and supraglacial debris using data collected in blue, near infrared (NIR), short wave infrared (SWIR) and thermal infrared (TIR) bands. The reflectance properties in visible and NIR regions of OLI for various glacier facies are in contrast with those in SWIR region. Based on the premise that different surface types (snow, ice and debris) of a glacier should show distinct thermal regimes, the ‘at-satellite brightness temperature’ obtained using TIRS was used as a base layer for developing the algorithm. This base layer was enhanced and modified using contrasting reflectance properties of OLI bands. In addition to facies and debris cover characterization, another interesting outcome of this algorithm was extraction of crevasses on the glacier surface which were distinctly visible in output and classified images. The validity of this algorithm was checked using field data along a transect of the glacier acquired during the satellite pass over the study area. With slight scene-dependent threshold adjustments, this work can be replicated for mapping glacier facies and supraglacial debris in any alpine valley glacier.  相似文献   

15.
Soil salinity is one of the most important problems affecting Egyptian soils. It is caused by: (1) a rising water table, or (2) the misuse of the irrigation water. Two Landsat images acquired in 1987 and 1999 were used to detect and monitor soil salinity over the Siwa Oasis, Western Desert, Egypt. DN values of these images were converted to percent reflectance. Inspection of Landsat images revealed that saline soils had an overall higher spectral reflectance in all spectral bands except the two MIR bands. The reflectance curves of saline soils show a strong relationship between the existence of salts in the soil and the difference between bands 4 and 5. A salinity index (SI) was calculated for both images. The majority of pixels in the 1987 image have salinity index values ranging between 0 and 0.2, whereas the values in the 1999 image histogram ranged between 0 and 0.4. These values indicate that soil salinity has increased twofold during the 12 years spanning the imagery. These values show a strong correlation with vegetation index images, in which the 1999 vegetation index image reveals the appearance of surface water lakes formed due to a rising water table. This study presents a model for the identification of soil salinity using remote sensing measurements in conjunction with piezometer readings taken during the time of image acquisition.  相似文献   

16.
The visible and near infrared bands of Landsat have limitations for detecting ships in turbid water. The potential of TM middle infrared bands for ship detection has so far not been investigated. This study analyzed the performance of the six Landsat TM visible and infrared bands for detecting dredging ships in the turbid waters of the Poyang Lake, China. A colour composite of principal components analysis (PCA) components 3, 2 and 1 of a TM image was used to randomly select 81 dredging ships. The reflectance contrast between ships and adjacent water was calculated for each ship. A z-score and related p-value were used to assess the ship detection performance of the six Landsat TM bands. The reflectance contrast was related to water turbidity to analyze how water turbidity affected the capability of ship identification. The results revealed that the TM middle infrared bands 5 and 7 better discriminated vessels from surrounding waters than the visible and near infrared bands 1–4. A significant relation between reflectance contrast and water turbidity in bands 1–4 could explain the limitations of bands 1–4; while water turbidity has no a significant relation to the reflectance contrast of bands 5 and 7. This explains why bands 5 and 7 detect ships better than bands 1–4.  相似文献   

17.
Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = −10.8242, p < 0.01} between the classification accuracies derived based on Landsat OLI 8 and those derived using WorldView-2 sensor. Although there were significant differences between Landsat and WorldView-2 accuracies, the magnitude of variation (9%) between the two sensors was within an acceptable range. Therefore, the findings of this study demonstrated that the recently launched Landsat 8 OLI multispectral sensor provides valuable information that could aid in the long term continuous monitoring and formulation of effective bracken fern management with acceptable accuracies that are comparable to those obtained from the high resolution WorldView-2 commercial sensor.  相似文献   

18.
江苏近海岸水深遥感研究   总被引：8，自引：0，他引：8  
以江苏近海辐射沙脊群海域为典型研究区,通过实测水深数据和水体光谱测量与分析,发现对应TM3和TM4波段的水体光谱反射率对水深信息敏感,线性相关系数分别达到-0.561和-0.694。结合多光谱遥感信息传输方程所推导出的水深信息对数反演模式,针对本研究区TM4和TM3波段数据所建立的水深预测模式的复相关系数R2为0.4793,对0-15m水深,预测水深和实测水深之间拟合较好。利用TM5波段反射率、出露沙洲反射率以及海水反射率的差异,通过建立掩膜图像,可较有效地对TM遥感图像进行水陆分离,提取TM图像中海水部分,进一步可通过常用的图像处理软件绘制每隔5m的TM水深遥感制图、等深线图。随着高空间、高光谱、高辐射分辨率遥感技术的发展,对浅海水域的水深和水下地形进行遥感探测的技术方法和应用将会不断地深入开展。  相似文献   

19.
For three agricultural crop types, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), we estimated biophysical parameters including fresh and dry biomass, leaf area index (LAI), and vegetation water content, for which we found the equivalent water thickness (EWT), fuel moisture content per fresh weight (FMCFW), and fuel moisture content per dry weight (FMCDW). We performed these estimations using data from the newly launched Landsat 8 Operational Land Imager (OLI) sensor, as well as its predecessor the Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Progress in the design of the new sensor (i.e., Landsat 8), including narrower near-infrared (NIR) wavebands, higher signal-to-noise ratio (SNR), and greater radiometric resolution highlights the necessity to investigate the biophysical parameters of agricultural crops, especially compared to data from its predecessor. This study aims to evaluate vegetation indices (VIs) derived from the Landsat 8 OLI and the Landsat 7 ETM+. Both the Landsat 8 OLI and Landsat 7 ETM+ VIs agreed well with in-situ data measurements. However, the Landsat 8 OLI-derived VIs were generally more consistent with in situ data than the Landsat 7 ETM+ VIs. We also note that the Landsat 8 OLI is better able to capture the small variability of the VIs because of its higher SNR and wider radiometric range; in addition, the saturation phenomenon occurred earlier for the Landsat 7 ETM+ than for the Landsat 8 OLI. This indicates that the new sensor is better able to estimate the biophysical parameters of crops.  相似文献   

20.
Reduced availability of plant nutrients such as nitrogen (N) and phosphorous (P) has detrimental effects on plant growth. Plant N:P ratio, calculated as the quotient of N and P concentrations, is an ecological indicator of relative N and P limitation. Remote sensing has already been widely used to detect plant traits in foliage, particularly canopy N and P concentrations and could be used to detect canopy N:P faster and at lower cost than traditional destructive methods. Despite the potential opportunity of applying remote sensing techniques to detect canopy N:P, studies investigating canopy N:P remote detection are scarce. In this study, we examined if vegetation indices developed for canopy N or P detection can also be used for canopy N:P detection. Using in situ spectrometry, we measured the reflectance of a common grass species, Yorkshire fog (Holcus lanatus L.), grown under different nutrient ratios and levels. We calculated 60 VIs found in literature and compared them to optimized VIs developed specifically for this study. The VIs were calculated using both the original narrow band spectra and the spectra resampled to the band properties of six satellite sensors (MSI – Sentinel 2, OLCI – Sentinel 3, MODIS – Terra/Aqua, OLI – Landsat 8, WorldView 4 and RapidEye) to investigate the influence of bandwidths and band positions. The results showed that canopy N:P was significantly related to both existing VIs (r2 = 0.16 - 0.48) and optimized VIs (r2 = 0.59 – 0.72) with correlations similar to what was observed for canopy N or canopy P. Existing VIs calculated with MSI and OLI sensors bands showed higher correlation with canopy N:P compared to the other sensors while the correlation with optimized VIs was not affected by the differences in sensors’ bands. This study might lead to future practical applications using in situ reflectance measurements to sense canopy N:P in grasslands.  相似文献   

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