共查询到20条相似文献，搜索用时 15 毫秒
1.
Henry Villegas 《国际地球制图》2013,28(1):67-74
Abstract On November the 13th of 1985, the City of Armero (Colombia) was destroyed by debris flows generated by a reactivation of the Nevado del Ruiz Volcano. The flows ocurred in at least three principal pulses, as was observed by the disater's survivors. Landsat TM 5 data processing was carried out in subscenes taken before and after the lahar sedimentation. False color composites were generated and combined with the geological information available in order to visualize the magnitude of the catastrophe and the flow characteristics. Taking advantage of Landsat TM 5 images with high spectral resolution, a detailed photogeological mapping of the three principal pulses of the debris flows was carried out. Landsat TM 5 proved to be a powerful complementary source of information for hazard assesment of these catastrophic debris flows. The images were used in addition to ground‐based information, and were an easy way to help ordinary people and decision makers understand such hazardous volcanic situations. 相似文献
2.
L-band (HH) synthetic aperture radar imagery from Shuttle Imaging Radar-B (SIR-B) and Landsat multispectral scanner (MSS) images over parts of the Punjab plains were combined in order to utilize the complementary information contained in multispectral data sets. Among the various combination of Landsat MSS with SIR-B, the combination of Landsat MSS band 5 (0.6–0.7 μm) and band 7 (0.8–1.1 μm) with SIR-B data was found to be optimum in delineating landcover units. The integrated data was found to be superior in providing landcover information in comparison to SIR-B alone or a combination of landsat MSS band 4,5 and 7. 相似文献
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Abstract This study examined the complementarity of radar and optical data for feature identification. Spaceborne radar and Landsat Thematic Mapper (TM ) multispectral data sets were assessed independently and in combination to classify a site near Wad Medani, Sudan. Radar processing procedures included speckle reduction, texture extraction and post‐processing smoothing. Relative accuracy of the resultant classifications was established by comparison to ground truth information derived from field visitation. Neither speckle filtering nor post‐classification smoothing were improvements over the poor results obtained with the unfiltered, original radar data. Texture measures were significant improvements over the original data (20 percent overall accuracy increase) and several, but not all, individual classes had excellent results. Landsat TM had good overall results (80 percent correct) but considerable spectral confusion between urban and bare soil. Combination of radar with Landsat TM greatly improved results, achieving near perfect classification of all individual classes. The systematic strategy of this study, determination of the best individual method before introducing the next procedure, was effective in managing a complex set of analysis possibilities. 相似文献
5.
Dengsheng Lu Guiying Li Emilio Moran Mateus Batistella Corina C. Freitas 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):798-808
This research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the roles of radar data with different spatial resolutions and wavelengths. The wavelet-merging technique was used to merge TM and radar data to generate a new dataset. A constrained least-squares solution was used to unmix TM multispectral data and multisensor fusion images to four fraction images (high-albedo, low-albedo, vegetation, and soil). The impervious surface image was then extracted from the high-albedo and low-albedo fraction images. QuickBird imagery was used to develop an impervious surface image for use as reference data to evaluate the results from TM and fusion images. This research indicated that increasing spatial resolution by multisensor fusion improved spatial patterns of impervious surface distribution, but cannot significantly improve the statistical area accuracy. This research also indicated that the fusion image with 10-m spatial resolution was suitable for mapping impervious surface spatial distribution, but TM multispectral image with 30 m was too coarse in a complex urban–rural landscape. On the other hand, this research showed that no significant difference in improving impervious surface mapping performance by using either PALSAR L-band or RADARSAT C-band data with the same spatial resolution when they were used for multi-sensor fusion with the wavelet-based method. 相似文献
6.
Arjun Sheoran 《国际地球制图》2013,28(4):370-382
The purpose of this study was to evaluate the relative classification accuracies of four land covers/uses in Kenya using spaceborne quad polarization radar from the Japanese ALOS PALSAR system and optical Landsat Thematic Mapper data. Supervised signature extraction and classification (maximum likelihood) was used to classify the different land covers/uses followed by an accuracy assessment. The original four band radar had an overall accuracy of 77%. Variance texture was the most useful of four measures examined and did improve overall accuracy to 80% and improved the producer’s accuracy for urban by almost 25% over the original radar. Landsat provided a higher overall classification accuracy (86%) as compared to radar. The merger of Landsat with the radar texture did not increase overall accuracy but did improve the producer’s accuracy for urban indicated some advantages for sensor integration. 相似文献
7.
A Narayana 《Journal of the Indian Society of Remote Sensing》1992,20(2-3):165-172
Some of the studies involving digital temporal data require normalisation. Many of the normalisation methods need information on prevailing atmospheric conditions, sensor-related details etc., whereas some other methods use only the information which are within the data set. A study was conducted in Kudremukh Iron Ore miningsite, Karnataka using multi-date data from Landsat MSS of 1976 and 1985. A normalisation method using only the scene statistics of the images is suggested which brings the multi-date data at par. This method is compared with some of the other methods which use only the information content of the data set. Comparison of these methods was made by scattergrams, distance measure etc. By generating scattergrams for various combinations of non-normalised and normalised images, different methods were compared. Based on ground information, some changed and unchanged classes were noted on the various normalised and original images. Using the distance measure for classes in different images, the normalisation procedures were compared. The proposed method turned out to be the best among the methods compared. 相似文献
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采用归一化互相关算法精确配准Landsat 8影像得到了2014年—2016年不同季节冰川的运动速率,并利用其热红外波段对不同时刻的地表温度进行反演;通过强度追踪法处理TerraSAR-X影像得到了2008年4月—10月不同时段的冰川运动速率。两种数据得到的结果表明:冰川末端流速较小,中部流速增大,流速从轴部向两侧递减;冬季流速明显小于夏季,变化趋势与温度变化具有一致性。冰川西侧分支的移动速率相对较大,从Landsat 8和TerraSAR-X提取的最大速率分别为2.56 m·d~(-1)和2.74 m·d~(-1)。最后对稳定区域的冰川流速进行统计,结果显示Landsat 8提取的冰川流速精度控制在1—9 cm d~(-1),基于TerraSAR-X的强度追踪法提取移动速率的精度控制在2cm·d~(-1),验证了两种数据监测冰川移动的可靠性。 相似文献
9.
Abstract This study examined the complementarity of spaceborne radar and optical data for surface feature identification. RADARSAT data sets were assessed independently and in combination with Landsat Thematic Mapper (TM) multispectral data. The primary methodology was spectral signature extraction and the application of a statistical decision rule to classify the surface features for a site near Kericho, Kenya. Relative accuracy of the resultant classifications was established by digital integration and comparison to reference information derived from field visitation. Speckle filtering was a great improvement over the poor results achieved with the unfiltered, original radar data but still not adequate for accurate land cover classification. The extraction and use of Variance texture measures was found to be very advantageous. The overall results were not significant improvements over speckle removal (6% increase) but several individual classes, forest and urban, had excellent results with texture. Combinations of radar with Landsat TM greatly improved results, achieving near perfect classification of all individual classes. The highest overall accuracy was achieved with a merger that included the best individual texture image and six reflectance bands of the TM data. The systematic strategy of this study, determination of the best individual method before introducing the next procedure, was effective in managing a very complex, almost infinite set of analysis possibilities. 相似文献
10.
TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda. 相似文献
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陆地卫星TM及JERS-1卫星SAR数据用于西藏东部斑岩铜矿勘查 总被引：2，自引：0，他引：2
本文介绍了利用陆地卫星TM及JERS-1卫星SAR数据在西藏东部地区进行斑岩铜矿勘查项目的早期研究成果。文中通过对现有地质资料的分析认为,研究区内的矿化作用除受三叠系火山岩建造控制外,还与喜山期的中酸性侵入体有关。而陆地卫星TM图像的解译结果表明,区内的主要矿床几乎都分布在与三叠纪古火山机构相关的环形构造内。为了增强和提取出与斑岩铜矿化有关的蚀变岩信息,研究中采用了对数残差、矿物指数和HSI变换等方法对陆地卫星TM及JERS-1卫星SAR数据进行了处理与分析,所提取出的蚀变信息与目视解译所发现的环形构造位置极为吻合。实践证明,遥感图像上的环形影像及蚀变岩石信息对矿产勘查有指示价值。 相似文献
12.
融合Landsat ETM+和MODIS数据估算高时空分辨率地表短波反照率 总被引：2，自引：0，他引：2
提出一种通过融合高空间低时间分辨率、低空间高时间分辨率地表短波反照率,来估算高时空分辨率地表短波反照率的方法。首先,利用Landsat ETM+数据,通过窄波段到宽波段的转换得到一景或多景空间分辨率较高的ETM+蓝天空短波反照率;然后,在MODIS短波反照率产品基础上,以天空光比例因子为权重,得到空间分辨率较低的MODIS蓝天空短波反照率;最后,利用STARFM(Spatial and Temporal Adaptive Reflectance Fusion Model)模型融合ETM+短波反照率的空间变化信息和MODIS短波反照率的时间变化信息,得到高时空分辨率的地表短波反照率。针对STARFM模型在异质性区域估算精度降低的问题,通过以MODIS反照率影像各像元的端元(各地类)反照率取代MODIS像元反照率来提取时空变化等信息参与STARFM模型的融合过程,达到提高异质性区域估算精度的目的。结果显示,直接利用STARFM模型估算得到的高空间分辨率地表短波反照率处在合理的精度范围内(RMSE0.02),用改进后的STARFM模型估算得到的异质性区域短波反照率和真实ETM+短波反照率间的相关系数增大。 相似文献
13.
In remote sensing–based forest aboveground biomass (AGB) estimation research, data saturation in Landsat and radar data is well known, but how to reduce this problem for improving AGB estimation has not been fully examined. Different vegetation types have their own species composition and stand structure, thus they have different data saturation values in Landsat or radar data. Optical and radar data also have different characteristics in representing forest stand structures, thus effective use of their features may improve AGB estimation. This research examines the effects of Landsat Thematic Mapper (TM) and ALOS PALSAR L-band data and their integrations in forest AGB estimation of Zhejiang Province, China, and the roles of textural images from both datasets. The linear regression models of AGB were conducted by using (1) Landsat TM alone, (2) ALOS PALSAR data alone, (3) their combination as extra bands, and (4) their data fusion, based on non-stratification and stratification of vegetation types, respectively. The results show that (1) overall, Landsat TM data perform better than PALSAR data, but the latter can produce more accurate estimates for bamboo and shrub, and for forests with AGB values less than 60 Mg/ha; (2) the combination of TM and PALSAR data as extra bands can greatly improve AGB estimation performance, but their fusion using the modified high-pass filter resolution-merging technique cannot; (3) textures are indeed valuable in AGB estimation, especially for forests with complex stand structures such as mixed forests and pine forests with understories of broadleaf species; (4) stratification of vegetation types can improve AGB estimation performance; and (5) the results from the linear regression models are characterized by overestimation and underestimation for the smaller and larger AGB values, respectively, and thus, selecting non-linear models or non-parametric algorithms may be needed in future research. 相似文献
14.
《地理信息系统科学与遥感》2013,50(3):345-370
Many data fusion methods are available, but it is poorly understood which fusion method is suitable for integrating Landsat Thematic Mapper (TM) and radar data for land cover classification. This research explores the integration of Landsat TM and radar images (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) for land cover classification in a moist tropical region of the Brazilian Amazon. Different data fusion methods—principal component analysis (PCA), wavelet-merging technique (Wavelet), high-pass filter resolution-merging (HPF), and normalized multiplication (NMM)—were explored. Land cover classification was conducted with maximum likelihood classification based on different scenarios. This research indicates that individual radar data yield much poorer land cover classifications than TM data, and PALSAR L-band data perform relatively better than RADARSAT-2 C-band data. Compared to the TM data, the Wavelet multisensor fusion improved overall classification by 3.3%-5.7%, HPF performed similarly, but PCA and NMM reduced overall classification accuracy by 5.1%-6.1% and 7.6%-12.7%, respectively. Different polarization options, such as HH and HV, work similarly when used in data fusion. This research underscores the importance of selecting a suitable data fusion method that can preserve spectral fidelity while improving spatial resolution. 相似文献
15.
Venkatesh Raghavan P. V. Panchanathan 《Journal of the Indian Society of Remote Sensing》1990,18(3):9-17
Lineament patterns detected from remotely sensed data provide useful information to geoscientists, specially in the study of basement tectonics, groundwater targetting and mineral exploration. Improvements in the spatial resolution of satellite images have resulted in the detection of short and faint lineaments which have hitherto gone unnoticed The IRS-1A LISS-II data offers a significant improvement in spatial resolution as compared to the Landsat MSS. A set of computer programmes developed for analysis of lineaments were used to study the parameters such as lineament frequency, length and density in order to quantify the added information derived using IRS-1A LISS-II images. The incremental contribution of LISS-II images are of the order of 100 per cent for lineament frequency and about 60 per cent for total line kilometers of lineaments detected. 相似文献
16.
Detecting and Downscaling Wet Areas on Boreal Landscapes 总被引：1，自引：0，他引：1
This letter presents an approach to classify wet areas from European Remote Sensing 2 (ERS-2) synthetic aperture radar (SAR)-, Landsat Thematic Mapper (TM)-, and Light Detection and Ranging (LiDAR)-derived terrain data and downscale the result from the coarse resolution of satellite images to finer resolutions needed for land managers. Using discrete wavelet transform (DWT) and support vector machines (SVM), the algorithm finds multiple relationships between the radar, optical, and terrain data and wet areas at different spatial scales. Decomposing and reconstructing processes are performed using a 2-D DWT (2D-DWT) and inverse 2D-DWT respectively. The underlying relationships between radar, optical, and terrain data and wet areas are learned by training an SVM at the coarse resolution of the wet-area map. The SVM is then applied on the predictors at a finer resolution to produce wet-area detailing images, which are needed to reconstruct a finer resolution wet-area map. The algorithm is applied to a boreal landscape in northern Alberta, Canada, characterized by many wet-area features including ephemeral and permanent streams and wetlands. 相似文献
17.
An accurate map of forest types is important for proper usage and management of forestry resources. Medium resolution satellite images (e.g., Landsat) have been widely used for forest type mapping because they are able to cover large areas more efficiently than the traditional forest inventory. However, the results of a detailed forest type classification based on these images are still not satisfactory. To improve forest mapping accuracy, this study proposed an operational method to get detailed forest types from dense Landsat time-series incorporating with or without topographic information provided by DEM. This method integrated a feature selection and a training-sample-adding procedure into a hierarchical classification framework. The proposed method has been tested in Vinton County of southeastern Ohio. The detailed forest types include pine forest, oak forest, and mixed-mesophytic forest. The proposed method was trained and validated using ground samples from field plots. The three forest types were classified with an overall accuracy of 90.52% using dense Landsat time-series, while topographic information can only slightly improve the accuracy to 92.63%. Moreover, the comparison between results of using Landsat time-series and a single image reveals that time-series data can largely improve the accuracy of forest type mapping, indicating the importance of phenological information contained in multi-seasonal images for discriminating different forest types. Thanks to zero cost of all input remotely sensed datasets and ease of implementation, this approach has the potential to be applied to map forest types at regional or global scales. 相似文献
18.
Chitrini Mozumder K. Venkata Reddy Deva Pratap 《Journal of the Indian Society of Remote Sensing》2013,41(2):269-277
There is a need for timely information about changes in the air pollution levels in cities for adopting precautionary measures. Keeping this in view, an attempt has been made to develop a model which will be useful to obtain air quality information directly from remotely sensed data easily and quickly. For this study pixel values, vegetation indices and urbanization index from IRS P6 LISS IV and Landsat ETM+ images were used to develop regression based models with Air Pollution Index (API), which were calculated from in-situ air pollutant information. It was found that among the 12 parameters of IRS, highest correlation exists between pixel values in NIR (Near Infra-Red) band (Pearson correlation ?0.77) and Normalized Difference Vegetation Index (NDVI) (Pearson correlation ?0.68) and both have inverse relationship with API. In case of Landsat, the highest correlation was observed in SWIR (Short Wave Infra-Red) band (Pearson correlation ?0.83) and NIR (Pearson correlation ?0.78). Both single and multivariate regression models were calibrated from best correlated variables from IRS and Landsat. Among all the models, multivariate regression model from Landsat with four most correlated variables gave the most accurate air pollution image. On comparison between the API modeled and API interpolated images, 90.5 % accuracy was obtained. 相似文献
19.
植被净初级生产力NPP(Net Primary Production)遥感估算与分析,有赖于高时空分辨率的遥感数据,但目前中高分辨率的遥感数据受卫星回访周期及天气的影响,在中国南方地区难以获取连续时间序列的数据,从而影响了高精度的区域植被净初级生产力的遥感估算。为此,提出一种基于多源遥感数据时空融合技术与CASA模型估算高时空分辨率NPP的方法。首先,利用多源遥感数据,即Landsat8 OLI数据与MODIS13Q1数据,采用遥感数据时空融合方法,获得了时间序列的Landsat8 OLI融合数据;然后,基于Landsat8 OLI时空融合数据,并采用CASA模型,以长株潭城市群核心区为例,进行区域植被NPP的遥感估算。研究结果表明,基于时间序列Landsat融合数据估算的30m分辨率的NPP具有良好的空间细节信息,且估算值与实测值的相关系数达0.825,与实测NPP数据保持了较好的一致性。 相似文献
20.
针对以光谱特征差异为依据,提取森林湿地信息精度低的问题,该文采用兼容多源数据的分类回归树(CART)提取方法,并以大沾河国家森林湿地进行实证研究。基于Landsat8遥感数据、Radarsat-2极化雷达数据和地形辅助数据,采用SPM软件分别构建3种特征变量组合的CART决策树模型,并获取分类规则,最后根据规则对研究区的森林湿地信息进行提取。结果表明:3种特征变量组合中,兼容光谱、纹理、雷达与地形辅助数据的CART决策树的森林湿地信息提取精度最高,用户精度和制图精度分别达到了88.46%和82.14%。研究结果体现了雷达数据与地形辅助数据有助于提取森林湿地信息。 相似文献