The Changjing River triangle area, where includes Jiangsu and Zhejinag province and Shainghai and so is called as Changjing delta, is a key area of Chinese economic development, but the economic sustainable development of Changjing delta in last ten years is restricted by coastal water quality deterioration, such as nitrogen and phosphorus content increasing, eutrophication, red tide and man activity pollution. The routine marine water quality assessment by boat, buoy and coastal observation station sampling is difficult to monitor its special and timely variation. In this paper, first, the situation of water quality of Changjing delta is introduced. Second, the satellite remote sensing algorithm of retrieve the parameters of water quality, such as total nitrogen (TN), total phosphorus (TP) and transparency, are discussed in detail. Finally, the rule of water quality classification briefly is mentioned and the water quality classification images are presented in the paper. The preliminarily result shows that the ocean color satellite data has its latent capability of quasi-realtime coastal water quality monitoring.
Spatial conception exists in remote sensing imagery as well as spectral information. It acts as more importance role in dominant landscape objects detection in high-resolution remote sensing imagery. Multiscale analysis is a new approach to meet the requirement of how to use spatial information in classification. Compared with traditional pixel based classification methods, multiscale analysis is composed of two fundamental components: the generation of a multiscale representation and information extraction. The paper focuses on one segmentation techniques- Fractal Net Evolution Approach (FNEA) and its usage in improvement in coastal remotely sensed image classification. FNEA is considered as one of effectual region-based segmentation and its threshold is a combination of size and homogeneity. We discuss two different segmental strategies which are speed-first and scale-first, and their impacts on image-objects. We can get the optimal segmental scale by analyzing the relationship between average size of each image-object and the different scale.
In recent years, great amount of polluted water discharged into the north part of Lake TaiHu, results in water eutrophication and frequent occurrences of blue-green algal bloom in the area. In order to obtain the information about blue-green algal bloom distribution for monitoring water quality, four navigation of in situ hyperspectral measurement and MODIS data of 250 m resolution were used to study the radiance reflectance character and distribution of blue-green algal bloom in the lake. Hyperspectral measurement showed that the peak of water leaving radiance near 700 nm transferred to 750-780 nm as the water covered with blue-green algal bloom and increased with the increasing density of water bloom. Band ratio of channel I to channel II and band synthesize of MODIS image of 250 m resolution were used for detection of algal bloom, and proved that band ratio of channel I to channel II was more suitable for detection of algal bloom. The methods for differentiating submerged vegetation and algal bloom from MODIS image were also tested: The area covered with submerged vegetation usually had high secchi depth, with algal bloom usually low secchi depth, and the phenomena can be used efficiently for differentiating submerged vegetation and algal bloom on MODIS image.
EOS\MODIS data have been proved a suitable and relative low-cost complementary tool to monitor large inland lake water quality for its re-visit frequency, moderate spatial and spectral resolution and appropriate channels designed for inversing water quality parameters. In this study, by the support of hi-tech research and development program of China, Lake water quality remote monitoring pre-operational system (LWQRMPS) was constructed aimed for practical monitoring of Taihu Lake water quality. The main water quality parameters including Chl-a and SPM, TN and TP inversion algorithm were developed. These parameters were obtained every month from time series fusion satellite data. With the routine trophic state evaluation system, the water quality was assessed every month based on the above retrieved MODIS water quality parameters, varied level of eutrophic area was computed. The obvious high reflectance in near-infrared spectrum caused by blue-green algal bloom support the application of 250m MODIS data in the algal bloom emergency monitor. Therefore, MODIS data were utilized successfully for inversing water quality parameters, evaluating eutrophication status, and detecting algal bloom in near real time. Standard thematic maps were produced and distributed to corresponding management departments. The accuracy of products and retrieve algorithm for operational use were tested with separate data sets. The result suggested that system is good enough for practical monitoring water quality of large size lakes and acquired identification.
Field investigation was carried out during 4, April, 2001 to 15, April, 2001 around Zhoushan Fishing Ground. The surface nutrient and suspended sediment (SS) concentration exhibit remarkable features. Most striking are that all data show very high values at the end member Changjiang Diluted Water (CDW), decrease abruptly at the onset of mixing of Taiwan Warm Current. The frontal zone is mainly located near 123°E, which is supported powerfully by NOAA sea surface temperature (SST) image. Total phosphorus (TP) concentration is affected profoundly with SS concentration, for robust relationship between total particulate (TPP) and TP is observed in most stations (R2=0.9073, n=10). Positive correlation between in-situ concentration of TP and SS are found. The experimental regression equation is represented as CTP=0.0195*CSS+0.5266, R2=0.5645(n=32). NO3- is the main form of DIN, of more than 82% in DIN, exhibits considerable conservative feature. Although lack of in-situ CDOM measurement, good relationship was established between in-situ DIN concentration with near real time SeaWiFS ACD data: CDIN=135.1351*CACD-6.0, R2=0.7514 (n=15). The two empirical regression algorithms were utilized for inversing TP and DIN concentration from SeaWiFS SS and ACD. The algorithms were adopted to evaluate the impaction of terrestrial pollutant input to the area by CDW.
A simple and fast multi-channel filtering algorithm is presented in the paper for texture segmentation. This algorithm requires only a small number of channels and automatically determines the channel parameters by analysis of the Fourier power spectrum. Also it does not need a priori knowledge about the type and number of textures occurring in the input images. We can gain categories number by the square-error plot of different clusters. It does not involve any human intervention. The algorithm is tested extensively with a variety of Brodatz's textures and real textures. The segmentation results validate the practicability of this algorithm.
As one of important applications in Synthetic Aperture Radar (SAR) images, the recognition of urban area has received considerable attentions in remote sensing. The extraction of line segment is very critical technology to recognize the urban area because many objects such as streets and buildings are line segment. The common method to extract line segment is Hough transform, but most of the previous methods are based on binary images. So we have to select a threshold to binarizate the image, but at most time we can not determine the threshold properly, resulting in the lost of useful information. To solve the problem, an improved Hough transform algorithm on gray level, which can make the extraction of line segment independent of the noise and the length of line segment, is proposed. The approach is validated by the analysis of SAR images.
Over the past two decades algal blooms appear to have increased in frequency intensity and geographic distribution. Algal blooms have caused harmful effects on the marine ecological balance even to human health. Monitor programs especially trending toward including continuous data collection by in situ detectors for example remote sensing is in emergently demand. In this research NDVI imagery obtained from MODIS satellite data combined with SST and chl-a proved to be a sensitive measure of phytoplankton amount providing a means of improving the detection and delineation of algal blooms.
Monitoring and restoration the water quality of lake need proper water quality parameters. Traditional measurement of water quality requiring laborious laboratory work is expensive and time consuming. Hyperspectral measurement can offer fast and easy way for estimating trophic status. Hyperspectral data on 7-8 March 2004 and water chemical data from 1997 to 2003 was used for retrieval of water quality parameters. The quantification of spectra with water quality parameters: chlorophyll a suspended solids total nitrogen(TN) total phosphorus(TP) chemical oxygen demand(COD) secchi depth(SD) were regressed. Results showed that the reflectance ratio of R702/R685 R6201R53 1 and R554/R675 had high correlations with the concentration of chlorophyll a suspended solids and total phosphorus respectively TN COD can be calculated from TP or Chi a for good relations between them SD is negatively correlated with suspended solids concentration total phosphorus (TP) (less than 0. 25 mg/L) linearly correlated with logarithm chlorophyll a concentration trophic status index (TSI) exponentially correlated with COD concentration.
To illustrate the relationship between nutrients of Taihu Lake and growth of algal three ecological model were introduced: 1)OECD management model 2)Monod equation 3)logistic equation. Based on these models of lake eutrophication good relationships between nutrients concentration and chlorophyll-a were found. Taking advantage of the consistent correlation to estimate nutrient concentration in Taihu Lake from CMODIS chl-a image was possible.
Scientists suggested that satellite remote sensing represent the most suitable technique for synoptic monitoring the change and extent of polluted water after late 80s. They try to establish the relationship of remote sensing parameters and oceanic components which are without optical activity. This technique permitted employ satellite-based data to estimate of regional and global phytoplankton primary production and provided a possible means for monitoring the spatial and seasonal variations of near-surface distribution of nutrient in water. Dugdale et al (1989) determined linkage between SST and nitrate in sea water of upwelling area: SST = F (NO3), consequently the concentration and distribution of nitrate can be retrieved from the SST image. Robinson (1989) suggested that CDOM have direct relationship with polluted component in water as dissolved organism, so CDOM can be used as tracer in the mixing process of estuary water. Pattiaratchi et al (1994) determined the concentration of chl-a and the relationship betweeh chl-a and nutrient, further retrieved the distribution of nutrient. Arnone at al (2000) succeeded in establishing salinity distribution image from SeaWiFS image through acquiring the relationship between CDOM and salinity. Chen Zhiqiang (2000) found out strong positive correlation between CDOM and nitrate and slilicate, succeeded in retreiving nutrient distribution inverse model in Zhujiang River Estuary from CDOM image.
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