共查询到20条相似文献，搜索用时 31 毫秒
1.
以黄海及东海海域为对象,研究用MOD IS数据提取我国海域悬浮泥沙时空分布的定量遥感方法,建立了基于MOD IS数据的悬浮泥沙定量遥感实用模式。研究表明,用250 m和1 000 m分辨率的MOD IS数据进行悬浮泥沙浓度的定量遥感,可以达到实际应用的精度要求。这说明,MOD IS数据是研究近岸水体中悬浮物输运变化规律的一种经济实用数据源。 相似文献
2.
基于遥感反演结果的悬浮泥沙时空动态规律研究--以珠江河口及邻近海域为例 总被引：9，自引：1，他引：9
选择了珠江口及其邻近海域1995年~2000年152个时相的NOAA/AVHRR影像反演的悬浮泥沙浓度结果,通过对悬浮泥沙反演结果影像的叠加,求算叠加像素点像素平均值,计算了研究海域在1995~2000年间月、季及丰枯水期几个时间尺度上的悬浮泥沙平均浓度及其平均变化。结果大致表明了陆地径流对海域的影响范围和悬浮泥沙在海域的运动方向。 相似文献
3.
The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance Rrs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APDm) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr−1, whereas the Rrs(λ) uncertainty at 412 nm is the highest (APDm 47–62%, RMS 0.0027–0.0041 sr−1). The uncertainties of the aerosol optical thickness (AOT) τa, diffuse attenuation coefficient for downward irradiance at 490 nm Kd(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of Kd(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task. 相似文献
4.
以MODIS红外谱段数据为基准,对高光谱红外谱段数据进行辐射交叉定标试验,同时运用高光谱红外谱段数据对近海海表水温进行了评估试验.交叉定标数据选取2012年—2013年冬、夏两季各一幅代表性图像,MODIS与高光谱红外谱段数据成像时间均为同一天白天.实验结果表明,天宫一号高光谱红外谱段数据与MODIS数据具有极好的相关性,相关系数R大于0.95;在此基础上建立了基于MODIS 32波段的辐亮度线性回归校正方程,并用于海表温度反演、检测自然与人工扰动造成的海表温度异常.基于校正数据反演的中国南北典型冬、夏代表性季节的海表温度与常识较为一致.由此表明,基于MODIS交叉定标的天宫一号数据可用于实际的业务化定量评估;同时,由于空间分辨率较高,天宫一号高光谱红外谱段数据在海水精细空间动态变化检测上表现出极好的性能. 相似文献
5.
Wenting Quan 《Journal of the Indian Society of Remote Sensing》2014,42(3):495-503
In this study, a theoretical model for studying the scaling effects on the two-band ratio of red to near-infrared band (TBRRN) is suggested. The model is used to explain the relationship between scaling error and local scale error; the results revealed that a special scale scaling procedure can be divided into a series smaller scale scaling procedures, and the total scaling error is the sum of the scaling error of these series’ smaller scale scaling procedure. Consequently, under the condition that the local scale is adequately fine, the total scale error at the target scale may be estimated accurately. In order to understand the mechanisms associated with scale in practical remote sensing, TBRRN data with 250 m and 1 km resolution is estimated from MODIS data at 645 and 859 nm, retrieved on September 1, 2009, in the Yellow River estuary, China. It is found that the TBRRN estimated from the 1 km resolution MODIS data is ~2.94 % smaller than as estimated from the 250 m MODIS data. The large scaling error distributes neither in the turbid waters, nor in the low suspended sediment regions, but instead in the high-low suspended sediment concentration transitional zone, which may be attributed to the spatial variable of suspended sediment in the transitional zone. This paper also points out that, owing to the importance of total scale error in achieving NASA’s mission in oceanic remote sensing, the way in which to conveniently and precisely estimate the total scale error of remote sensing parameters may potentially be an important topic in the field of oceanic remote sensing, both in present research and in the future. 相似文献
6.
Accurate estimation of chlorophyll-a concentration in turbid coastal waters by means of remote sensing is challenging due to the optical complexity of these waters. We have developed a four-band quasi-analytical algorithm for assessment of chlorophyll-a concentration in coastal waters. The objectives of this study are to validate the applicability of three-band semi-analytical algorithm, quasi-analytical algorithm, and four-band quasi-analytical algorithm in estimating chlorophyll-a concentration in turbid coastal waters for MODIS sensor. These three algorithms are calibrated and evaluated against coastal evaluation datasets provided by SeaWiFS Bio-optical Archive and Storage System. The algorithm validation results indicate that the four-band quasi-analytical algorithm produces a superior performance to both three-band semi-analytical algorithm and quasi-analytical algorithm. By comparison, using four-band quasi-analytical algorithm produces 21.61 % uncertainty in estimating chlorophyll-a concentration from turbid coastal waters, lower than 77.90 % for three-band semi-analytical algorithm and 74.31 % for quasi-analytical algorithm, respectively. The significantly reduced uncertainty in chlorophyll-a concentration assessment is due to effectively removal of pigment-package effects and particle overlapping effects on the chlorophyll-a absorption estimation using a optical classification method. These findings imply that, provided that an atmospheric correction scheme for visible and near-infrared bands is available, the database of MODIS imagery could be used for quantitative monitoring of chlorophyll-a concentration in turbid coastal waters by four-band quasi-analytical algorithm. 相似文献
7.
MODIS数据的海洋表面温度反演 总被引：4，自引：0，他引：4
以黄海及东海海域为对象,研究用MODIS数据提取我国海域海洋表面温度的方法,建立了适合于我国海域的MODIS海洋表面温度遥感实用模式。研究表明,此算法的反演精度比较高,用这种模式计算的海面温度可较真实地反映海洋表面温度分布状况。由于同一天可以获取同一地区的上午和下午两景MODIS数据,因此MODIS数据在探测海洋现象方面具有独特的优势。 相似文献
8.
针对我国近岸高浑浊水体区域MODIS短波红外波段大气校正产品中存在的信号饱和及条带问题,利用神经网络模型,采用准同步的HJ-1A/B卫星CCD影像及实测遥感反射率数据对MODIS/Terra水色遥感大气校正产品进行了质量改进。改进后结果与MODIS/Terra遥感反射率产品相比,平均相对误差为13.3%,信号饱和区域修复结果与实测数据各波段平均相对误差为28.2%。结果表明,该方法在保证结果精度的情况下,能有效地修复MODIS/Terra水色波段因为信号饱和而产生的数据空白区域,同时也能较好地解决MODIS/Terra大气校正产品中的条带问题。 相似文献
9.
Monitoring turbidity and Surface Suspended Sediment Concentration (SSSC) of inland waters is essential to address several important issues: erosion, sediment transport and deposition throughout watersheds, reservoir siltation, water pollution, human health risks, etc. This is especially important in regions with limited conventional monitoring capacities such as West Africa. In this study, we explore the use of Moderate Resolution Imaging Spectroradiometer data (MODIS, MOD09Q1 and MYD09Q1 products, red (R) and near infrared (NIR) bands) to monitor turbidity and SSSC for the Bagre Reservoir in Burkina Faso. High values of these parameters associated with high spatial and temporal variability potentially challenge the methodologies developed so far for less turbid waters. Field measurements (turbidity, SSSC, radiometry) are used to evaluate different radiometric indices. The NIR/R ratio is found to be the most suited to retrieve SSSC and turbidity for both in-situ spectoradiometer measurements and satellite reflectance from MODIS.The spatio temporal variability of MODIS NIR/R together with rainfall estimated by the Tropical Rainforest Measuring Mission (TRMM) and altimetry data from Jason-2 is analyzed over the Bagre Reservoir for the 2000–2015 period. It is found that rain events of the early rainy season (February-March) through mid-rainy season (August) are decisive in triggering turbidity increase. Sediment transport is observed in the reservoir from upstream to downstream between June and September. Furthermore, a significant increase of 19% in turbidity values is observed between 2000 and 2015, mainly for the July to December period. It is especially well marked for August, with the central and downstream areas showing the largest increase. The most probable hypothesis to explain this evolution is a change in land use, and particularly an increase in the amount of bare soils, which enhances particle transport by runoff. 相似文献
10.
The accurate assessment of total suspended sediment (TSM) concentration in coastal waters by means of remote sensing is quite challenging, due to the optical complexity and significant variability of these waters. In this study, three-band semi-analytical TSM retrieval (TSTM) model with HJ-1A/CCD spectral bands was developed for the retrieval of TSM concentration from turbid coastal waters. This model was calibrated and validated by means of one calibration dataset and three independent validation datasets obtained from three different turbid waters. It was found that the TSTM model may be used to retrieve accurate TSM concentration data from highly turbid waters without the spectral slope of the model requiring further optimization. Finally, the TSM concentration data were quantified from the HJ-1A/CCD images after atmospheric correction using the dark-object subtraction technique. Upon comparing the model-derived and field-measured TSM concentration data, it was observed that the TSTM model produced <29% uncertainty in deriving TSM concentration from the HJ-1A/CCD data. These findings imply that the TSTM model may be used for the quantitative monitoring of TSM concentration in coastal waters, provided that the atmospheric correction scheme for the HJ-1A/CCD imagery is available. 相似文献
11.
Algal blooms and the resulting deterioration of water quality have threatened the environmental health of inland lakes. This study investigated the spatiotemporal dynamics of gypsum blooms in the Salton Sea, the largest inland water body in California. An innovative gypsum bloom index (GI) was proposed to detect gypsum blooms based on Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra data for three bands (469, 555, and 859 nm) during 2000–2018. Discoloration (from green to reddish brown) was observed in the gypsum bloom-infested waters mapped using the hue, saturation, and value (HSV) color model. We found that: (1) the GI is able to effectively map gypsum blooms in the Salton Sea with a relatively high accuracy (85 %); (2) the largest gypsum bloom area was observed in summer (August and September), with notable gypsum blooms lasting more than 40 days in 2003, 2005, 2006, 2016, and 2018; (3) the gypsum bloom-infested waters shifted from the center to the southeastern shore of the lake during 2003–2018, and the frequency of gypsum blooms significantly increased since 2008. Meanwhile, the temporal and spatial differences between the northwestern and southeastern lake increased over the observation period; and (4) discoloration occurred in the gypsum bloom-infested waters and lasted for 14 days on average, longer periods of discoloration (more than 20 days) occurred d in 2002, 2016, and 2018. The reconstruction of gypsum bloom dynamics in the Salton Sea provides valuable information for the practical management and restoration of the Salton Sea. 相似文献
12.
中国东海叶绿素浓度变化分析及其海水温度响应 总被引：1，自引：0，他引：1
海洋叶绿素浓度时空格局分析及与海水温度的响应研究对于海洋资源的开发和保护及赤潮的预防具有重要意义。本文基于2004—2018年东海叶绿素浓度和海水温度数据运用趋势分析及ArcGIS10.2软件，对东海叶绿素浓度作了时空分析研究，并结合海水温度进行了回归分析，以探究叶绿素对海水温度变化的响应机制。结果表明：①东海叶绿素浓度在2004—2018年间没有明显的年际变化特征。年内则随时间上下波动，冬季为波峰，夏季为波谷。离海岸带越近，叶绿素浓度越高。②东海海域海水温度在年际尺度上呈波动式起伏变化。在季节尺度上夏秋两季温度较高，春季次之，冬季最低。从沿海到外海海域海温逐渐升高。③就空间相关性而言，东海海域叶绿素浓度与海水温度整体呈负相关，在不同海域相关程度不同。长江口和外海区域叶绿素浓度与海水温度具有很强的相关性；在沿海区域，由于受到城市环境、经济发展及人类生产生活的影响，海水温度与叶绿素浓度的相关性不明显。 相似文献
13.
Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20–520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters. 相似文献
14.
定量分析气溶胶与痕量气体之间的时空变化关系有助于进一步研究气粒转化。本文采用2006年—2015年MODIS气溶胶光学厚度(AOD)、细粒子模态比(FMF)和OMI痕量气体(SO_2、NO_2和HCHO)数据,对黄海、东海和南海区域上空的细粒子气溶胶与痕量气体进行定量分析。先对气溶胶和痕量气体作均值分析发现:AOD_(fine)、SO_2、NO_2和HCHO的均值在黄海、南海、东海均依次减小;再对气溶胶对痕量气体的敏感度分析发现:黄海地区的AOD_(fine)对SO_2最敏感,敏感度为0.424,这与中国东部沿海城市的人为排放有关;而东海和南海地区对HCHO的敏感度较高,依次为0.664和0.545,主要受东南亚和中国南方地区生物质燃烧影响。最后,对3个区域的气溶胶与痕量气体按季节作相关性分析发现:黄海地区AOD_(fine)在夏秋两季与SO_2的相关性较强(R0.5),主要由于夏秋两季的温湿度大,利于发生气—粒转化;东海地区夏季HCHO与AOD_(fine)相关性较明显(R=0.57);南海春季HCHO与AOD_(fine)相关性较好(R=0.57),呈现出区域与季节性的变化。最终发现,气溶胶与痕量气体随着时空变化存在相关关系。 相似文献
15.
M. Moussavi Alashloo Hwee-San Lim Robabeh Asadpour Sahabeh Safarpour 《Journal of the Indian Society of Remote Sensing》2013,41(3):663-673
Remote sensing has been extensively used for water delineation and has played an important role in water quality evaluation and environmental management strategies. Suspended sediments are important determinants of water quality in coastal zones. Remote sensing enables the effective monitoring of total suspended sediments (TSS) and the detection of areas with critical water quality issues. This study aims to develop and implement regression models for estimating and mapping TSS concentrations from Advanced Land Observation Satellite (ALOS) images over the coastal waters of Langkawi Island, Malaysia. The algorithm was developed based on the water reflectance model, which is a function of the inherent optical properties of water. Such properties can then be linked to TSS concentration. In this study, an ALOS Advanced Visible and Near Infrared Radiometer type 2 device was used as the imaging sensor system. Concurrent complementary in-situ water samples were collected within the area coverage of the sensor, and digital numbers (DN) for each band corresponding to the sea-truth locations were determined. The extracted DN values were converted into reflectance values and then regressed with their respective sea-truth data. An algorithm was proposed to obtain the regression coefficient. This algorithm can estimate TSS concentrations with a high correlation coefficient (R2?=?0.96) and low root-mean-square error (RMSE?=?1.98 mg/l). Finally, a map of the TSS concentration was generated by using the proposed algorithm. This study found that TSS mapping can be conducted by using ALOS data over the coastal waters of Langkawi Island, Malaysia. 相似文献
16.
Nivedita Sanwlani Prakash Chauhan Ranganath R. Navalgund 《Journal of the Indian Society of Remote Sensing》2010,38(4):617-626
Space-borne ocean-colour remote sensor-detected radiance is heavily contaminated by solar radiation backscattered by the atmospheric
air molecules and aerosols. Hence, the first step in ocean-colour data processing is the removal of this atmospheric contribution
from the sensor-detected radiance to enable detection of optically active oceanic constituents e.g. chlorophyll-a, suspended sediment etc. In standard atmospheric correction procedure for OCEANSAT-1 Ocean Colour Monitor (OCM) data, NIR
bands centered at 765 and 865 nm wavelengths were used for aerosol characterization. Due to high absorption by water molecules,
ocean surface in these two wavelengths acts as dark background, therefore, sensor detected radiance can be assumed to have
major contribution from atmospheric scattering. For coastal turbid waters this assumption of dark surface fails due to the
presence of highly scattering sediments which causes sufficient water-leaving radiance in NIR bands and lead to over-estimation
of aerosol radiance resulting in negative water leaving radiance for λ < 700 nm. In the present study, for the turbid coastal
waters in the northern Bay of Bengal, the concept of spatial homogeneity of aerosol and water leaving reflectance has been
applied to perform atmospheric correction of OCAEANSAT-1 OCM data. The results of the turbid water atmospheric correction
have also been validated using in-situ measured water-leaving radiance. Comparison of satellite derived water-leaving radiance for five coastal stations with in-situ measured radiance spectra, indicates an improvement over the standard atmospheric correction algorithm giving physically
realistic and positive values. Root Mean Square Error (RMSE) between the in-situ measured and satellite derived water leaving radiance for wavelengths 412 nm, 443 nm, 490 nm, 512 nm and 555 nm was found
to be 1.11, 0.718, 0.575, 0.611 and 0.651%, respectively, using standard atmospheric correction procedure. By the use of spatial
homogeneity concept, this error was reduced to 0.125, 0.173, 0.176, 0.225, and 0.290 and the correlation coefficient arrived
at 0.945, which is an improvement over the standard atmospheric correction procedure. 相似文献
17.
Since coastal waters are one of the most vulnerable marine systems to environmental pollution, it is very important to operationally monitor coastal water quality. This study attempts to estimate two major water quality indicators, chlorophyll-a (chl-a) and suspended particulate matter (SPM) concentrations, in coastal environments on the west coast of South Korea using Geostationary Ocean Color Imager (GOCI) satellite data. Three machine learning approaches including random forest, Cubist, and support vector regression (SVR) were evaluated for coastal water quality estimation. In situ measurements (63 samples) collected during four days in 2011 and 2012 were used as reference data. Due to the limited number of samples, leave-one-out cross validation (CV) was used to assess the performance of the water quality estimation models. Results show that SVR outperformed the other two machine learning approaches, yielding calibration R2 of 0.91 and CV root-mean-squared-error (RMSE) of 1.74 mg/m3 (40.7%) for chl-a, and calibration R2 of 0.98 and CV RMSE of 11.42 g/m3 (63.1%) for SPM when using GOCI-derived radiance data. Relative importance of the predictor variables was examined. When GOCI-derived radiance data were used, the ratio of band 2 to band 4 and bands 6 and 5 were the most influential input variables in predicting chl-a and SPM concentrations, respectively. Hourly available GOCI images were useful to discuss spatiotemporal distributions of the water quality parameters with tidal phases in the west coast of Korea. 相似文献
18.
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
19.
ABSTRACT The temporal resolution of vegetation indices (VIs) determines the details of seasonal variation in vegetation dynamics observed by remote sensing, but little has been known about how the temporal resolution of VIs affects the retrieval of land surface phenology (LSP) of grasslands. This study evaluated the impact of temporal resolution of MODIS NDVI, EVI, and per-pixel green chromatic coordinate (GCCpp) on the quality and accuracy of the estimated LSP metrics of prairie grasslands. The near-surface PheonoCam phenology data for grasslands centered over Lethbridge PhenoCam grassland site were used as the validation datasets due to the lack of in situ observations for grasslands in the Prairie Ecozone. MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data from 2001 to 2017 were used to compute the time series of daily reference and to simulate 2–32 day MODIS VIs. The daily reference and simulated multi-day time series were fitted with the double logistic model, and the LSP metrics were then retrieved from the modeled daily time series separately. Comparison within satellite-based estimates showed no significant difference in the phenological metrics derived from daily reference and multi-day VIs resampled at a time step less than 18 days. Moreover, a significant decline in the ability of multi-day VIs to predict detailed temporal dynamics of daily reference VIs was revealed as the temporal resolution increased. Besides, there were a variety of trends for the onset of phenological transitions as the temporal resolution of VIs changed from 1 to 32 days. Comparison with PhenoCam phenology data presented small and insignificant differences in the mean bias error (MBE) and the mean absolute error (MAE) of grassland phenological metrics derived from daily, 8-, 10-, 14-, and 16-day MODIS VIs. Overall, this study suggested that the MODIS VIs resampled at a time step less than 18 days are favorable for the detection of grassland phenological transitions and detailed seasonal dynamics in the Prairie Ecozone. 相似文献
20.