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1.
The scope of this research was to study lake morphology using spatial simulation technique, to develop revised elevation-capacity curve, to develop elevation-water spread area curve, to study the relation between suspended sediment and remote sensing satellite data, and to estimate suspended sediment load in the lake using a Geographic Information System coupled with ground truth. The study area was the Bhopal Upper Lake, which has been classified as one of the major wetlands in India by the Ministry of Water Resources, India. A precise digital elevation model was created using 0.5 meter interval contour information collected from bathometric surveys. Water-spread areas at different water levels were simulated spatially in a Geographic Information System (GIS) through the neighbourhood connectivity operator. Revised elevation-capacity curve and elevation-area curve of the lake were prepared using the simulated results. Simulated water spread area at full tank level (FTL) was compared with the actual water spread area delineated using remote sensing data. Water samples at different locations of the lake were collected and located using the Global Positioning System (GPS) instrument. These samples were analysed in the laboratory for suspended sediment concentration. Different image processing techniques were applied to LANDSAT 5 TM satellite digital data (except thermal band). Correlation between radiance values of band 2 and suspended sediments was established and a positive linear equation was found to fit the data best. Spatial distribution of suspended sediment load was estimated using the developed regression equation and band 2 radiance image of the complete lake. Total suspended sediment load and loss of capacity at full tank level were computed.  相似文献   

2.
为分析高分一号WFV传感器16 m遥感影像在水质反演方面的能力,本文选取南四湖为研究区,以高分一号卫星影像与Landsat-8卫星OLI影像为数据源,结合地面同步实测水体浊度数据,建立反演水体浊度的原始光谱反射率模型、归一化反射率模型和波段比值模型,并对各模型进行精度评价,分别比较两个传感器在浊度反演能力方面的差异。结果表明:利用高分一号WFV 16m遥感影像进行水质反演具有较高的精度,且具备更高的空间分辨率和更短的重访周期,可以替代Landsat-8多光谱数据。  相似文献   

3.
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   

4.
Pollution of water resources by sediments eroded from degraded watersheds is a critical concern around the world. Current methods for locating these eroding areas and off-site damage to water resources through visual observations and field sampling with subsequent laboratory analysis are time consuming and expensive. There is thus, a justified interest in developing algorithms for quick estimation of suspended sediment concentrations in large water-bodies from remotely sensed data. This paper presents the results of a ground validation study on characterization and quantification of surface suspended sediment concentrations (SSC) in sediment laden water bodies through an n-waveband specific numerical index, total information content. A comparison of SSC-predictive potential of the proposed new index, derived from four broad (100–300 nm) Landsat MSS, five broad (40–300 nm) Landsat TM and eight narrow (20–40 nm) IRS-P4 OCM spectral bands, with that of the conventional (NIR-Red and NIR+Red) indices, computed from the same spectral band data, is also presented. The study reveaied that at SSCs 250 mg/1, the proposed index (derived from either broad / narrow landsat MSS/TM or IRS-P4 OCM spectral data) could lead to SSC predictions (with mean errors within 20%) comparable with those obtained with the conventional indices (derived from the same spectral band data). It could further be observed that, in general, lower sediment concentrations (i.e. SSCs 150 mg/1) were associated with higher prediction inaccuracies. A comparison of the mean errors of predictions associated with the proposed and the conventional (NIR-Red and NIR+Red) indices computed from broad and narrow band data for SSCs 150 mg/I, revealed that an increase in number of wavebands (from 4 MSS to 5 TM or 8 OCM bands) and a decrease in the bandwidth of these wavebands (from broad MSS/ TM bands to narrow OCM bands) led to a significant increase in the prediction accuracy of the proposed new index. These prediction accuracies were observed to be the highest with the proposed index calculated from narrow OCM-P4 spectral data. However this could not be observed with the conventional indices at any of the SSC ranges and with the proposed index at SSCs 250 mg/l. This shows that the lower SSC-predictive potential of proposed index was a significant function of both the number and the bandwidth of spectral bands used for its computation. In fact in one of the cases, lower SSC (150 mg/l) -predictive accuracy of the proposed index was found to be significantly higher than that of the conventional (NIR+R) index. The proposed algorithm could thus compress the information contained in the entire reflectance spectrum of the sediment laden water bodies to their sediment type and concentration specific characteristic values. This characteristic of the proposed index was not shared by any of the conventional indices, based on only two waveband data. In fact the proposed index appears to be the only mean of completely compressing and quantifying the information contained in all the information channels of a narrow band spectrometer (consisting of 200 wavebands) to be shortly launched by ISRO for satellite based inventory of natural resources.  相似文献   

5.
Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N = 504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R2 is 0.76, while the adjusted R2 values for regional models vary from 0.77 to 0.89, all significant (p-value < 0.0001). The regional models are subject to the leave-one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical proprieties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat/TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown.  相似文献   

6.
Atmospheric correction (AC) is a necessary process when quantitatively monitoring water quality parameters from satellite data. However, it is still a major challenge to carry out AC for turbid coastal and inland waters. In this study, we propose an improved AC algorithm named N-GWI (new standard Gordon and Wang’s algorithms with an iterative process and a bio-optical model) for applying MERIS data to very turbid inland waters (i.e., waters with a water-leaving reflectance at 864.8 nm between 0.001 and 0.01). The N-GWI algorithm incorporates three improvements to avoid certain invalid assumptions that limit the applicability of the existing algorithms in very turbid inland waters. First, the N-GWI uses a fixed aerosol type (coastal aerosol) but permits aerosol concentration to vary at each pixel; this improvement omits a complicated requirement for aerosol model selection based only on satellite data. Second, it shifts the reference band from 670 nm to 754 nm to validate the assumption that the total absorption coefficient at the reference band can be replaced by that of pure water, and thus can avoid the uncorrected estimation of the total absorption coefficient at the reference band in very turbid waters. Third, the N-GWI generates a semi-analytical relationship instead of an empirical one for estimation of the spectral slope of particle backscattering. Our analysis showed that the N-GWI improved the accuracy of atmospheric correction in two very turbid Asian lakes (Lake Kasumigaura, Japan and Lake Dianchi, China), with a normalized mean absolute error (NMAE) of less than 22% for wavelengths longer than 620 nm. However, the N-GWI exhibited poor performance in moderately turbid waters (the NMAE values were larger than 83.6% in the four American coastal waters). The applicability of the N-GWI, which includes both advantages and limitations, was discussed.  相似文献   

7.
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8.
In the present study an attempt has been made to estimate acreage and condition of tea plantations by using satellite based digital remotely sensed data in visible, near infra-red and middle infra-red spectral regions, in the Nilgiri district of Tamilnadu state. Landsat MSS and TM data, acquired on Dec. 26, 1990 were used in the analysis, Different spectral band combinations, Landsat MSS (1234), TM (1234), TM (2345) and TM (123457) were used for identification of tea plantations. District-boundary-overlaying approach with complete enumeration of digital data was used for estimation of tea acreages. Condition assessment of tea plantations is based on the Greenness Index. Use of Landsat MSS data resulted in an underestimation of area under tea whereas the acreages estimated by using TM spectral band combinations 1234 and 2345 compared closely with the estimates of Department of Horticulture (DOH). The distribution pattern of various condition classes of tea plantations compared well with the prevailing ground conditions as observed during post-classification field survey in September 1992 in the district.  相似文献   

9.
A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set.The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.  相似文献   

10.
It is challenging to develop Landsat-5 TM (TM5) image-based retrieval models for estimating the suspended particulate matter concentration (CSPM) in water when missing coincident ground CSPM measurements. This study, with the Poyang Lake in China as a case study, proposed an approach for developing TM5-based CSPM retrieval models with the assistance of moderate resolution imaging spectroradiometer (MODIS) images. After validation with an independent dataset, a cubic CSPM retrieval model of 250 m MODIS red band was used to estimate the CSPM values at 100 sampling points from the MODIS images (MODIS-based CSPM) captured at three time periods. The MODIS-based CSPM values at the time period with the largest CSPM variation were combined with their coincident TM5 image reflectance for TM5-based model calibrations. The linear, quadratic, cubic, power and exponential models of MODIS-based CSPM against TM5 single bands and their combinations were calibrated, respectively. Four best-fitting TM5-based CSPM models were selected to retrieve the CSPM values at 100 sampling points from the TM5 images (TM5-based CSPM) at the other two time periods, and the coincident MODIS- and TM5-based CSPM values were compared to assess TM5-based model performances. Model calibration results showed that the cubic and exponential models of TM5 red band (band 3) and red subtracting mid-infrared band (band 5) obtained the best fitting for estimating CSPM from the TM5 image on 12 August 2005, and they explained 94–97% of the variation of MODIS-based CSPM values with an estimated standard error of 6.617–8.457 mg/l. Model validations indicated that the exponential model of TM5 red band got the best result for estimating CSPM from TM5 images when the MODIS-based CSPM values were assumed as ground truths (correlation coefficient between MODIS- and TM5-based CSPM values = 0.96, root mean square error = 4.60 mg/l). We concluded that the TM5-based CSPM retrieval models could be developed with the assistance of MODIS, and the approach proposed in this study will be helpful for other researchers who also want to retrieve CSPM from TM5 image archive but without coincident ground CSPM measurements.  相似文献   

11.
淤泥质潮滩通常是测绘"盲区"。本文讨论采用多时相陆地卫星提取潮滩水边线以此构建潮滩数字高程模型(DEM)的方法。探讨在不同潮情条件下,各光谱波段对淤泥质潮滩水边线判断的敏感性,分析表明沙质海岸与淤泥质海岸水边线的确定方法有较大差别。采用了GIS技术对提取的水边线赋予相应的高程值,该值采用研究区附近潮位站理论潮位推算卫星过境的瞬时潮位值,以此构建潮滩DEM,与近期实测资料进行对比:在106.2 cm-358.6 cm高程范围内,二者相对误差<0.5 m的区域占总面积约70%,0.5～1.0 m为20%,>1.0 m占10%。遥感构建DEM作为一种手段对实测资料的欠缺是一种补充,随着遥感技术的发展精度有望提高。  相似文献   

12.
Chlorophyll-a (Chl-a) and Suspended Solid Concentration (SSC) shows the productivity of water and their surrounding environment. These parameters can be effectively estimated through several remote sensing techniques. From the recent reports on the Gulf of Thailand, it is found that Chl-a and SSC are increasing in coastal areas due to changing environment caused by variations in the global carbon cycle, climate change and water pollution linking to anthropogenic conditions such as high population density and rapid urbanization in neighbouring coastal areas deteriorating the coastal and marine environment. Various models are evaluated in this study for estimation of marine Chl-a and SSC by employing Ocean Colour Monitor-2 sensor of Oceansat-2 satellite for Northern Gulf of Thailand. The retrieval of Chl-a and SSC by the atmospheric correction of visible bands from 400 to 700 nm to attain normalized water-leaving radiances and then a suitable algorithm is applied. The In-situ reflectance values of sea waters are measured using the ASD spectroradiometer. The reflectance values of the spectroradiometer are correlated for the same day atmospherically corrected satellite reflectance and the analysis offers high correlation R2 0.73. Satellite derived, Chl-a and SSC are correlated with observed in situ Chl-a and SSC. This analysis offered better correlation of R2 0.86 and 0.85 respectively with the algorithms of Chl-a and SSC.  相似文献   

13.
Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water.  相似文献   

14.
A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+.  相似文献   

15.
To understand the absolute radiometric calibration accuracy of the HJ-A CCD-1 sensors, image from these sensors were compared to nearly simultaneously image from Landsat-7 ETM+ sensors. Although the HJ-A CCD-1 sensor has almost the same wavelength of each central band and band width as Landsat-7 ETM+ sensor, there is slightly difference in spectral response function (SRF). The impacts of SRF difference effects would produce ~2 % uncertainty in predicting reflectance of HJ-A CCD-1 sensor using Landsat-7 ETM+ sensor. The reflectance observed by satellite at top-of-atmosphere generally depends on its’ geometric conditions. The results reveal that the impacts of geometrical conditions would impact on the vicarious cross-calibration accuracy, which should be removed. The performances of cross-calibration are calibrated and validated by four image pairs collected from Yellow River Delta, China, and Qingdao City, China, at four independent times. The results indicate that the HJ-A CCD-1 sensors can be cross calibrated to the Landsat-7 ETM+ sensors to within an accuracy of 3.99 % (denoted by Relative Root Mean Square Error) of each other in all bands except band 4, which has a 6.33 % difference.  相似文献   

16.
针对国产风云三系列中分辨率卫星快速有效地进行水体识别的问题,基于2011—2016年数据进行了辽宁省主要湖泊水库的光谱分析,提出了晴空条件和有云情况下分别采用归一化水体指数方法和通道值与归一化水体指数相结合方法进行湖泊水库的提取。结果表明:FY3B/MERSI湖泊光谱曲线具有水体光谱特征,具体表现为8通道的数据反射率最高,18通道数据反射率最低。通过与49景TM数据水体提取结果进行对比,FY3B/MERSI数据水体提取的面积精度达到85%以上,总体分类精度达到90%以上,Kappa系数在0.56~0.95之间。提出了简便、快捷的计算模型,为国产卫星数据的业务应用提供了初步方法。  相似文献   

17.
A Laboratory experiment has been conducted to establish relation between absolute percent reflectance as measured by Exotech spectro-radiometer compatible to LANDSAT MSS and corresponding known sediment concentrations in a specially designed laboratory sedimentation tank under known illumination conditions. Sediment samples are collected from the bed load deposits of JAYAKWADI reservoir by using a bed load sampler and are analysed in the laboratory for their particle size distribution. Sediment concentrations in the range of 50–1100 mg/l are used in the experiment. A multiple linear regression equation has been developed between absolute percent reflectance and sediment concentration. The results indicate that diffused absolute reflectance from water volume increases with increased sediment concentration and separability between bands is higher at higher concentrations. Exotech band 2 provides significant response from suspended sediment concentrations. There is almost one to one correspondence between predicted (from the model) suspended sediment concentrations and actual concentrations with a coefficient of determination of 0.962 and a standard eror of estimate of 56.47 mg/l. This may be due to the fact that most of the noise sources are nearly eliminated in the controlled laboratory experiment.  相似文献   

18.
云南中甸地区CBERS-1卫星数据质量分析   总被引：1，自引：0，他引：1  
将云南中甸地区CBERS-1的CCD数据(轨道号20000480402)与该地区已有的Landsat-5TM数据(轨道号132-41)进行对比,从图像的空间分辨率、几何畸变程度、辐射精度、清晰度、噪声等5方面入手,对CBERS-1的数据质量进行了分析  相似文献   

19.
有机悬浮物OSM (Organic Suspended Matter)是湖泊有机碳库的重要组成成分,对研究湖泊生态环境和初级生产力具有重要意义.本研究以太湖、巢湖、涌湖、小兴凯湖、滇池、洪泽湖、呼伦湖和南漪湖8个内陆湖泊为研究区,发展了适合内陆水体的有机悬浮物浓度遥感估算方法.基于B6、B7波段的斜率和B10、B11波...  相似文献   

20.
Salinization is one of the major soil problems around the world. However, decadal variation in soil salinization has not yet been extensively reported. This study exploited thirty years (1985–2015) of Landsat sensor data, including Landsat-4/5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operational Land Imager), for monitoring soil salinity of the Yellow River Delta, China. The data were initially corrected for atmospheric effects, and then matched the spectral bands of EO-1 (Earth Observing One) ALI (Advanced Land Imager). Subsequently, soil salinity maps were derived with a previously developed PLSR (Partial Least Square Regression) model. On intra-annual scale, the retrievals showed that soil salinity increased in February, stabilized in March, and decreased in April. On inter-annual scale, soil salinity decreased within 1985–2000 (−0.74 g kg−1/10a, p < 0.001), and increased within 2000–2015 (0.79 g kg−1/10a, p < 0.001). Our study presents a new perspective for use of multiple Landsat data in soil salinity retrieval, and further the understanding of soil salinization development over the Yellow River Delta.  相似文献   

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