Remote sensing approach for watershed based resources management in the Sikkim Himalaya: A case study

Integrated and environmentally sustainable development strategies have become inevitable for micro-level planning these days. The usefulness of remotely sensed data from earth resource satellites for watershed management is discussed for an eastern Himalayan watershed covering 39.09 km² area. The biophysical conditions were assessed based on field experience. The SPOT HRV-I MLA and PLA scenes were interpreted for land use/cover categories and associated characteristics. These parameters were found to be significant towards evolving the management priorities for development of agriculture, soil conservation, afforestation and rain water harvesting structures in ecologically fragile Himalayan region. The remote sensing inputs were important in deriving the relevant details faster and precisely.     

Evaluation of multisensor data for delineating salt affected soils in arid rajasthan

The Landsat (MSS and TM), SPOT (PLA and MLA) and IRS (LISS-I and LISS-II) images of crop free period (April, May), rainfed crop (October) and rabi irrigated crop (January, February) have been evaluated for their capabilities of mapping (1) primary salt affected soils: (slightly, moderately and severely) (2) saline water irrigated saline soils, (3) sodic water irrigated sodic soils and (4) salt affected soils due to tank seepage in the arid region of Rajasthan. The moderately and severe salt affected soils could be mapped with Landsat, (IRS LISS-I) and SPOT, images of any season. However, the summer season imagery provided maximum extent of salt affected soils. The LISS-II imagery also provided delineation of slightly salt affected soils in addition to the moderate and severely salt affected soils. The delineation of saline and sodic water irrigated areas was possible by using Landsat False Colour Composite for the January month by their characteristic reflectance, existing cropping pattern and the quality of irrigation water being used in the area. The IRS (LISS-II) and SPOT PLA images for the May month were also used for mapping of saline and sodic water irrigated soils.     

Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja,Nigeria

This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis.     

Evaluation of image fusion methods using PALSAR,RADARSAT-1 and SPOT images for land use/ land cover classification

This research aimed to explore the fusion of multispectral optical SPOT data with microwave L-band ALOS PALSAR and C-band RADARSAT-1 data for a detailed land use/cover mapping to find out the individual contributions of different wavelengths. Many fusion approaches have been implemented and analyzed for various applications using different remote sensing images. However, the fusion methods have conflict in the context of land use/cover (LULC) mapping using optical and synthetic aperture radar (SAR) images together. In this research two SAR images ALOS PALSAR and RADARSAT-1 were fused with SPOT data. Although, both SAR data were gathered in same polarization, and had same ground resolution, they differ in wavelengths. As different data fusion methods, intensity hue saturation (IHS), principal component analysis, discrete wavelet transformation, high pass frequency (HPF), and Ehlers, were performed and compared. For the quality analyses, visual interpretation was applied as a qualitative analysis, and spectral quality metrics of the fused images, such as correlation coefficient (CC) and universal image quality index (UIQI) were applied as a quantitative analysis. Furthermore, multispectral SPOT image and SAR fused images were classified with Maximum Likelihood Classification (MLC) method for the evaluation of their efficiencies. Ehlers gave the best score in the quality analysis and for the accuracy of LULC on LULC mapping of PALSAR and RADARSAT images. The results showed that the HPF method is in the second place with an increased thematic mapping accuracy. IHS had the worse results in all analyses. Overall, it is indicated that Ehlers method is a powerful technique to improve the LULC classification.     

Hyperspectral image noise reduction based on rank-1 tensor decomposition

In this study, a novel noise reduction algorithm for hyperspectral imagery (HSI) is proposed based on high-order rank-1 tensor decomposition. The hyperspectral data cube is considered as a three-order tensor that is able to jointly treat both the spatial and spectral modes. Subsequently, the rank-1 tensor decomposition (R1TD) algorithm is applied to the tensor data, which takes into account both the spatial and spectral information of the hyperspectral data cube. A noise-reduced hyperspectral image is then obtained by combining the rank-1 tensors using an eigenvalue intensity sorting and reconstruction technique. Compared with the existing noise reduction methods such as the conventional channel-by-channel approaches and the recently developed multidimensional filter, the spatial–spectral adaptive total variation filter, experiments with both synthetic noisy data and real HSI data reveal that the proposed R1TD algorithm significantly improves the HSI data quality in terms of both visual inspection and image quality indices. The subsequent image classification results further validate the effectiveness of the proposed HSI noise reduction algorithm.     

Role of remote sensing in residential site selection: A case study of Hisar town and its environs

To tackle the problems arising due to rapid urbanization, the urban planners need relevant data base. Since the conventional methods of data acquisition and processing ate not cost and time effective, introduction of new techniques is necessary. Application of satellite remote sensing is an alternative. Ia this paper attempt has been made to find out the usefulness of visual interpretation technique of satellite remote sensing data in the selection of new residential site. SPOT 1 HRV 1 MLA (FCC) date has been used to map existing landuse/landcover of Hisar town and its environs. Based on existing landuse/lsndcover conditions and evaluation of various suitability parameters like physiography, slope, drainage, availability of drinking water and wind direction, a new residential site has been selected. This study may be useful to the urban planners in the preparation of a comprehensive plan Df the town.     

Assessment of SPOT 5 and QuickBird remotely sensed imagery for mapping tree cover in savannas

The relative abundance and distribution of trees in savannas has important implications for ecosystem function. High spatial resolution satellite sensors, including QuickBird and IKONOS, have been successfully used to map tree cover patterns in savannas. SPOT 5, with a 2.5 m panchromatic band and 10 m multispectral bands, represents a relatively coarse resolution sensor within this context, but has the advantage of being relatively inexpensive and more widely available. This study evaluates the performance of NDVI threshold and object based image analysis techniques for mapping tree canopies from QuickBird and SPOT 5 imagery in two savanna systems in southern Africa. High thematic mapping accuracies were obtained with the QuickBird imagery, independent of mapping technique. Geometric properties of the mapping indicated that the NDVI threshold produced smaller patch sizes, but that overall patch size distributions were similar. Tree canopy mapping using SPOT 5 imagery and an NDVI threshold approach performed poorly, however acceptable thematic accuracies were obtained from the object based image analysis. Although patch sizes were generally larger than those mapped from the QuickBird image data, patch size distributions mapped with object based image analysis of SPOT 5 have a similar form to the QuickBird mapping. This indicates that SPOT 5 imagery is suitable for regional studies of tree canopy cover patterns.     

应用图像卷积运算提取城市范围

通过一种卷积算法,从遥感分类数据中计算城市用地比例,并以该比例作为划分城市和非城市区的阈值,进而提取城市范围。方法构建了评价提取结果的指标体系,以确定卷积模板大小和阈值的选取。以北京为研究区,利用2007年SPOT 5多光谱影像分类数据,对方法的可行性进行了验证。结合统计数据中的建成区面积,采用504种模板和阈值组合进行提取试验,讨论了模板和阈值对提取结果的影响。最终选择(205, 51)的模板和阈值组合,对城市范围进行提取。研究结果表明：(1)该方法解决了遥感监测的城市用地分布区与城市范围存在差异的问题,为城市研究基础数据的准备提供了新的方法;(2)阈值过高或过低会造成城市范围的明显缩小或扩大;较小的模板不利于消除随机误差,较大的模板则会导致结果过于平滑;(3)对于SPOT 5多光谱影像分类数据,模板大小在193—205像元(约4 km²)、阈值接近50时,提取结果最好。     

用SPOT卫星影像研究阿木尔林业局森林火灾损失

本研究以1987年5月30日接收的法国SPOT卫星标准假彩色合成影像为主要信息源,对大兴安岭阿木尔林业局火灾造成的林地损失进行了研究。文中着重介绍了面积量算方法、原理和误差;选取适量地面样地,用抽样统计和角规辅助目测方法计算蓄积损失并与二类调查结果进行比较;在影像上按火烧等级的判读结果、现地景观与烧死率─火灾的定量描述,及三者之间的一致性。结果表明,应用SPOT卫星资料,按本研究所介绍的方法进行火灾损失估计,可快速、经济地获得所需结果,并可满足精度要求。     

Urban land use mapping and zoning of Bombay Metropolitan Region using remote sensing data

Bombay Metropolitan Region covering an area of about 4,360 sq. km. was selected for urban land use studies and for urban land use zoning. Urban land use mapping was carried out using SPOT multispectral linear array imagery on 1∶25,000 scale employing visual analysis tehcniques. Fifteen maps were prepared depicting the spatial distribution of various urban classes in the Greater Bombay and New Bombay regions. Sixteen urban land use maps were also prepared using Landsat TM data showing the distribution of land use pattern on 1∶50,000 scale for the entire metropolitan region. Urban land use zoning was carried out based upon suitability index on 1∶250,000 scale. This map provides information on the areas to be used for construction and areas to be kept under green belt in the metropolitan region. This study is a joint venture of Space Applications Centre with Bombay Metropolitan Development authority.     

Field-based sub-boundary extraction from remote sensing imagery using perceptual grouping

This study presents an approach for the automatic extraction of dynamic sub-boundaries within existing agricultural fields from remote sensing imagery using perceptual grouping. We define sub-boundaries as boundaries, where a change in crop type takes a place within the fixed geometry of an agricultural field. To perform field-based processing and analysis operations, the field boundary data and satellite imagery are integrated. The edge pixels are detected using the Canny edge detector. The edge pixels are then analyzed to find the connected edge chains and from these chains the line segments are detected using the graph-based vectorization method. The spurious line segments are eliminated through a line simplification process. The perceptual grouping of the line segments is employed for detecting sub-boundaries and constructing sub-fields within the fixed geometry of agricultural fields. Our strategy for perceptual grouping involves the Gestalt laws of proximity, continuation, symmetry and closure. The processing and analysis operations are carried out on field-by-field basis. For each field, the geometries of sub-boundaries are determined through analyzing the line segments that fall within the field and the extracted sub-boundaries are integrated with the fixed geometry of the field.The experimental validation of the approach was carried out on the SPOT4 multispectral (XS) and SPOT5 XS images that cover an agricultural area located in the north-west section of Turkey. The overall matching percentages between the reference data and the automatically extracted sub-boundaries were computed to be 82.6% and 76.2% for the SPOT5 and SPOT4 images respectively. The higher matching percentage of the SPOT5 image is due to the fact that some of the boundaries present in the SPOT5 image were not detected in the coarser resolution SPOT4 image. For the SPOT5 image, of the total 292 fields processed, 177 showed a total agreement between the detected segments and the reference data. For the SPOT4 image, 154 fields showed a total agreement between the detected segments and the reference data.     

遥感技术在黄土高原土地利用现状调查中的应用研究

本研究选取黄土高原典型丘陵沟壑区——陕西省米脂县为试验区,用TM磁带、TM假彩色合成影像、SPOT多光谱影像和彩色红外航空像片同时对试区进行土地利用现状分类与制图的比较研究。通过对土地利用现状分类系统、TM图像计算机增强处理与自动分类、TM最佳波段组合、三种影像的目视判读与制图、以及遥感信息源的综合评价等多方面的试验研究,为遥感技术在黄土高原1:5万土地利用现状调查制图中的应用提供了一套技术数据及可行的方法。     

SPOT地面场定标与星上定标结果的比较分析

本文研究是在遥感辐射定标场选择的基础。利用６Ｓ大气辐射传输模型进行ＳＰＯＴ遥感数据的定标和地物的光谱反射率反演,即在遥感器飞越辐射定标场上空,在定标场选择若干像元区,测量遥感器对应的各波段地物的光谱反射率和大气光谱参量,并利用大气辐射传输模型给出遥感器人瞳处各光谱带的辐射亮度,最后确定它与遥感器对应输出的数字量化的数量关系,求解定标系数。然后,对相应的研究训练区的遥感数据进行大气辐射校正,进而反演训练区内的地物光谱反射率。最后,通过将反演值与实地测量的地物光谱反射率进行对比分析,来估算定标不确定度,并比较说明两种不同方式定标差异及优势和限制。     

《风云二号》静止气象卫星

《风云二号》静止气象卫星１９９７年６月１０日２０点０１分,从我国西昌卫星发射中心,由长征三号运载火箭成功地将我国自己研制的《风云二号》静止气象卫星发射入轨（封面）。６月１７日,《风云二号》卫星成功地定点在东经１０５°赤道上空。６月２１日１４时０１分,...     

SPOT5影像数据不同融合方法的比较与评价

采用小波IHS变换、小波PCA变换、EHLERS变换等五种不同融合技术对SPOT5的多光谱影像和全色影像进行融合,并从均值、标准差等方面对融合结果进行了评价。研究表明：EHLERS融合后影像有很好的整体视觉效果,但在细节表达方面有所缺陷;改进后的IHS融合后影像清晰度较低;PCA变换融合容易导致影像失真;而小波IHS和小波PCA融合技术以数据保留量大、失真程度小、视觉效果好、影像层次分明等特点证明了小波分解技术的优势。     

The Utility of Very High Spatial Resolution Images to Identify Urban Objects

Abstract

Landsat MSS, TM and SPOT XS imageries were used in conjunction with unsupervised, supervised and hybrid classilication techniques to classify land cover types in semi‐arid savannas of Mathison Pastoral Station in the Katherine region of northern Australia. Accuracy assessment was based on field data from 246 ground survey sites over a 745‐km² study area. Of 14 land cover classes identified by traditional mapping means, all combinations of imageries and classification techniques differentiated at least seven land cover types. The overall accuracy for these classifications ranged between 43% and 67%. SPOT XS image delivered the best accuracy followed by TM and MSS; unsupervised classification performed better than supervised and hybrid methods. User's and producer's accuracy of individual land units ranged from 0% to 100%. Riparian woodlands, woodland on limestone slopes, shrubland on clay plains, woodland on limestone plains and shadows were the best‐mapped classes. The land units that were associated with undulating hills were not mapped accurately. However, incorporation of a digital elevation model (DEM) in a GIS improved the overall accuracy. The user's and producer's accuracy of dominant land cover types were also enhanced. The classification results and the efficacy of the techniques at Mathison were similar to those found for a nearby semi‐arid area (Kidman Springs) about 200 km from Mathison. However, the overall accuracy was lower at Mathison than at Kidman Springs. Spectral classification masks were developed from the SPOT XS and TM imageries at Kidman Springs, and were applied to classify SPOT XS and TM imageries at Mathison. Initial results showed that the classification mask could be successfully extrapolated to map dominant land cover types but only with moderate accuracy (50%).     

UL-Isomap based nonlinear dimensionality reduction for hyperspectral imagery classification

The paper proposes an upgraded landmark-Isometric mapping (UL-Isomap) method to solve the two problems of landmark selection and computational complexity in dimensionality reduction using landmark Isometric mapping (LIsomap) for hyperspectral imagery (HSI) classification. First, the vector quantization method is introduced to select proper landmarks for HSI data. The approach considers the variations in local density of pixels in the spectral space. It locates the unique landmarks representing the geometric structures of HSI data. Then, random projections are used to reduce the bands of HSI data. After that, the new method incorporates the Recursive Lanczos Bisection (RLB) algorithm to construct the fast approximate k-nearest neighbor graph. The RLB algorithm accompanied with random projections improves the speed of neighbor searching in UL-Isomap. After constructing the geodesic distance graph between landmarks and all pixels, the method uses a fast randomized low-rank approximate method to speed up the eigenvalue decomposition of the inner-product matrix in multidimensional scaling. Manifold coordinates of landmarks are then computed. Manifold coordinates of non-landmarks are computed through the pseudo inverse transformation of landmark coordinates. Five experiments on two different HSI datasets are run to test the new UL-Isomap method. Experimental results show that UL-Isomap surpasses LIsomap, both in the overall classification accuracy (OCA) and in computational speed, with a speed over 5 times faster. Moreover, the UL-Isomap method, when compared against the Isometric mapping (Isomap) method, obtains only slightly lower OCAs.     

SPOT 5卫星影像测绘能力分析

HRS同轨立体影像获取能力是SPOT5卫星最突出的一个关于测绘制图的新特性,它确定了SPOT5卫星在测绘中的重要应用前景。本文从SPOT5HRS的立体成像方式,SPOTImage公司最新推出的Reference3D产品及陕西宝鸡地区的HRS立体影像测量试验等方面对SPOT5HRS影像测绘能力进行了分析和评价,说明了SPOT5卫星影像测绘将是解决我国西部困难地区基础测绘的一种重要手段。     

DMSP-OLS与NPP-VIIRS夜间灯光数据测算统计指标能力评估——以京津冀地区县域GDP、人口及能源消耗为例

夜间灯光数据记录了地球表面的人造灯光强度,是估计社会统计指标的有效手段之一。为了评估DMSP-OLS和NPP-VIIRS 2种夜间灯光数据对社会统计指标的模拟潜力,采用4种常用的灯光校正方法分别对2种夜间灯光数据进行灯光饱和性校正,根据校正后的夜间灯光数据分别建立与京津冀地区县域GDP、人口和能源消耗3种社会统计指标间的线性回归模型,从模型拟合的相关系数、F统计量值与概率p值中分析并评价了2种夜间灯光数据对GDP、人口和能源消耗3种社会统计指标的测算能力。本文研究结果表明：EANTLI法是2种夜间灯光数据的最佳校正方式,而HSI法不适用于夜间灯光数据校正后与县域社会统计指标的线性关系拟合2种夜间灯光数据对GDP的拟合效果都较好,NPP-VIIRS夜间灯光数据估算社会统计指标的拟合能力要优于DMSP-OLS数据。     

环境一号卫星高光谱数据水体信息提取方法

环境一号卫星A星上的超光谱成像光谱仪(HSI)是中国第一个高光谱成像光谱仪.为充分利用HSI数据的高光谱特性,本文以2009年10月5日的影像为研究区,得到HSI数据影像反射率,分析水体等地类光谱特征差异及选择各地类敏感波段;利用传统指数NDVI和NDWI,构建新的基于指数的水体指数IWI,试验得出,IWI指数增加了各...