Hsiang-te Kung

Applications of Landsat‐5 TM imagery in assessing and mapping water quality in Reelfoot Lake, Tennessee

Water quality in Reelfoot Lake, Tennessee, was investigated in the field over 15 years ago. However, the spatial variations of water quality were not studied. The remote sensing technique has been proved a powerful tool in mapping spatial distributions of some water quality parameters such as chlorophyll‐a concentration. Additionally, different regression methods and various independent variables have been used to establish relationships between water quality parameters and spectral reflectance. The results from this study indicate that Landsat TM2 and TM3, as a set of independent variables in multivariate regression analysis, are good predictors of water quality in Reelfoot Lake. TM2 is positively correlated to water quality, and TM3 is negatively correlated to water quality. Poor water quality, or a high algae load, results in a high reflectance measured by TM2 and a low reflectance measured by TM3. Maps of spatial distribution of Secchi disk depth, turbidity, chlorophyll‐a, and total suspended solids present apparent spatial variations of water quality in the lake.

The change of land use/cover and characteristics of landscape pattern in arid areas oasis: An application in Jinghe, Xinjiang

This paper uses 3S technology in macroscopic. Combining the integrated technology of ecological quantity analytical method with GIS technology through ArcGIS and Fragstats, the authors study the images of 1972, 1990, 2001, and 2005 and obtained land use data in Jinghe County. Then, the change of land use/cover and landscape pattern had been analyzed in the Jinghe County of Xinjiang. The conclusions were as follows: (1) The trend of LUCC is that the area of oasis expands slowly in nearly 33 years between 1972 to 2005 in Jinghe County. (2) The water area is mainly influenced by Ebinur Lake, so the area expands a little in this period. (3) The area of salinization-land expands at first and reduces later. The area of sand land decreases and the other land class increases, while the probability of transfer is always high. (4) Landscape change is also obvious throughout the decades. Overall, landscape density increases, the largest path index decreases at first and expends later, the weight area index decreases, and the shape of landscape becomes regulated. The nearest distances, the degrees of reunite, and outspread decreases. It shows that the connection of the main path in 1972 is better than 2005, wherein the patch becomes more complex. From the changes of Shannon’s Diversity Index and Shannon’s Evenness Index, we know that the diversity of landscape and the Interspersion Juxtaposition Index increase. The degree of diversity landscape and fragmentation increase also shows that the land uses become more complex. All in all, it is essential to intensify the spatial relationships among landscape elements and to maintain the continuity of landscape ecological process and pattern in the course of area expansion.

Studies on the reflectance spectral features of saline soil along the middle reaches of Tarim River: a case study in Xinjiang Autonomous Region, China

There has been growing interest in the use of reflectance spectroscopy as a rapid and inexpensive tool for soil characterization. In this study, 53 soil samples were collected from the oasis in the Weigan and Kuqa River delta along the middle reaches of Tarim River to investigate the level of soil chemical components in relation to soil spectral. An approach combining spectral technology and multi-variant statistical analysis was used to determine the reflectance spectral features of saline soil. The spectral data was first pretreated to remove noises and absorption bands from water, which eliminated influence from instrument errors and other external background factors. Several spectral absorption features were calculated for several saline soil samples to confirm that soil at the same salinity level had similar absorption spectral properties. Secondly, a correlation relationship between reflectance spectra and salinity factors was estimated by bivariate correlation method. Fourteen salinity factors including eight major ions and soil electrical conductivity (EC), soil salt content (SSC), pH, and total dissolved solid (TDS) in the saline soil were evaluated. Datasets of the salinity factors that correlated significantly with field data measurements of reflectance rate and the corresponding spectrum data were used to construct quantitative regression models. According to the multiple linear regression analysis, SSC, SO42−, TDS, and EC had a correlation coefficient at 0.746, 0.908, 0.798, and 0.933 with the raw spectral data, respectively, which confirmed strong correlation between salinity factors and soil reflectance spectrum. Findings from this study will have significant impact on characterization of spectral features of saline soil in oasis in arid land.

Management of flood disasters in the Jianghan Plain, China

This study examines the causes of flood disasters in Jianghan Plain, China and provides practical solutions to mitigate them. Results from this study indicate that both historical archives and more recent recorded data point to an increasing frequency in flood disasters since 1961. Furthermore, damage and losses from flood disasters have also increased significantly in the region. By analyzing the physical geographic factors and human activities, this study found that the main causative factors contributing to increasing flood disasters are landform/topography, climate elements, reduced drainage capacity of rivers in contrast to increased flood discharge, and human activities. Finally, the study examines various practical solutions to mitigate flood disasters in the Jianghan Plain.

Heavy metal concentrations in soils and crops of Baoshan-Wusong area, Shanghai, China

Summary Sampling around the Baoshan-Wusong area indicated that concentrations of heavy metals in soils were higher than the background levels of agricultural soils of Shanghai-suburbs. Statistical test showed Zn, Cd, Cr, Hg, F, and Pb contaminants were present in the surface soils, and high correlation coefficients were identified between the soluble fraction of those contaminants in soils and their concentrations in wheat grains and leaves. To characterize its spatial variation, the fuzzy pattern recognition was introduced to assess comprehensively polluted conditions at sites, and logarithm regression was used to identify the main polluted source. Results showed that soil pollution occurred predominantly around the industrial complex, covering about 20 sq.km but was not widespread. This finding plus other statistical data revealed that the high level of metal concentrations were primarily due to industrial activities but not from soil parent materials and farming practices. The metal concentrations decreased with the increasing distance away from the complex along the southeast direction.

Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan–Kuqa river delta oasis in Xinjiang, China

Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline–alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.

Fuzzy clustering analysis in environmental impact assessment — A complement tool to environmental quality index

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of environmental quality/impact incorporates multiple parameters. In such cases the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification can be accomplished. The methodology is relatively simple and the results can be interpreted to provide valuable information to support decision making and improve management of the environment.

Seismic vulnerability evaluation of bridges in Memphis and Shelby County, Tennessee

The focus of this paper is to develop a screening procedure to obtain information and assess vulnerability of bridges located in the New Madrid seismic zone (NMSZ). This screening methodology includes structural elements, site, foundation, and importance of the bridge. An inventory of the river-crossing bridges in Memphis and Shelby County is made using the developed screening procedure; potentially hazardous bridges that require further detailed seismic evaluation and/or immediate seismic retrofitting are identified. The results of this study are important for future maintenance and improvement, earthquake loss estimates, seismic hazard/risk reduction, and earthquake preparedness/rescue plans for river-crossing bridges in the NMSZ.

Estimation of soil salt content (SSC) in the Ebinur Lake Wetland National Nature Reserve (ELWNNR), Northwest China, based on a Bootstrap-BP neural network model and optimal spectral indices

Soil salinity is recognized worldwide as a major threat to agriculture, particularly in arid regions. Producers and decision-makers thus require updated and accurate maps of salinity in agronomical and environmentally relevant regions. The goals of this study were to test various regression models for estimating soil salt content based on hyperspectral data, HJ-CCD images, and Landsat OLI data using; develop optimal band Difference Index (DI), Ratio Index (RI), and Normalization Index (NDI) algorithms for monitoring soil salt content using image and spectral data; and to compare the performances of the proposed models using a Bootstrap-BP neural network model (Bootstrap-BPNN) from different data sources. The results showed that previously published optimal remote sensing parameters can be applied to estimate the soil salt content in the Ebinur Lake Wetland National Nature Reserve (ELWNNR). Optimal band combination indices based on DI, RI, and NDI were developed for different data sources. Then, the Bootstrap-BP neural network model was built using 1000 groups of Bootstrap samples of remote sensing indices (DI, RI and NDI) and soil salt content. When verifying the accuracy of hyperspectral data, the model yields an R2 value of 0.95, a root mean square error (RMSE) of 4.38g/kg, and a residual predictive deviation (RPD) of 3.36. The optimal model for remote sensing images was the first derivative model of Landsat OLI, which yielded R2 value of 0.91, RMSE of 4.82g/kg, and RPD of 3.32; these data indicated that this model has a high predictive ability. When comparing the salinization monitoring accuracy of satellite images to that of ground hyperspectral data, the accuracy of the first derivative of the Landsat OLI model was close to that of the hyperspectral parameter model. Soil salt content was inverted using the first derivative of the Landsat OLI model in the study area.

Seismic vulnerability evaluation of essential facilities in Memphis and Shelby County, Tennessee

This study is designed to assess potential seismic vulnerability of highly occupied or heavily used essential facilities, including 202 schools, 22 hospitals, and 74 fire stations, in Memphis and Shelby County, Tennessee which may be strongly affected by earthquakes in the New Madrid seismic zone (NMSZ). The seismic evaluation system uses existing data such as site, subsurface condition, foundation, structural characteristics, and results of previous site-specific seismic hazard studies. Results of the study reveal the current overall risk of damage of the essential facilities subject to the recognized seismic hazard in the study area and identify a preliminary pool of the most vulnerable facilities for the highest priority to be used in developing a detailed study to identify retrofit/replacement plans in the near future. Results also provide useful information for long-term upgrade strategies for essential facilities and general buildings in the Memphis area. The study results are important for future detailed study, facility maintenance and improvement, earthquake loss estimates, seismic hazard/risk reduction, and earthquake preparedness/rescue plans in the region.