Study on the Forest Vegetation and Its Water and Soil Conservation Value in Fuxian Lake Drainage Area in Yunnan Province

By using French SPOT5 satellite remote sensing image to contrast on the spot,the forest vegetation in Fuxian Lake basin was categorized into 23 forest types,6 vegetation subtypes,5 vegetation types,and the areas were respectively calculated.The tree species structure and the coverage degree of every kind of forest vegetation were investigated,and the characteristics of forest vegetation were analyzed.The results showed that the soil conservation amount of forest in Fuxian Lake basin was 137.50×106 t/a,and the soil conservation value was 622.30×106 yuan/a.Moreover,the water source conservation value was 506.84×106 yuan/a.

Evaluation of Spectral Scale Effects in Estimation of Vegetation Leaf Area Index Using Spectral Indices Methods

Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers(SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition(VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index(NDVI), Modified Simple Ratio Indices(MSRI) and Triangle Vegetation Index(TVI), although the coefficient of determination R^2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant(SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis(PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting(SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.

Research and Analyze the Factors Affecting to the Formation of the Economy Area of Fresh Vegetables Cultivation at Ho Chi Minh City Suburb

Vietnam＇s economy is developing more and more rapidly, people＇s income are increasing, and the living condition is better. Today, consumer are increasingly aware of the quality of products, especially fresh food, but they have a little opportunity to choose the products which satisfy the needs, because they are limited to the product information and product origin. Fresh vegetables are one of the essential foods in the family living. The selection of fresh vegetables is not only to serve the basic needs as eating and drinking, but also to include the need for safety. Currently, consumer demand for fresh vegetable are great, especially when the living standards are becoming higher and people pay more attention to their health, especially for the consumer of Ho Chi Minh City. How fresh is vegetable market in Ho Chi Minh City today like.＇？ What is consumers＇ awareness of fresh vegetable？ What factors impact the fresh vegetable buying behavior of consumers？ Why does the development of fresh vegetable market in Ho Chi Minh City currently face many difficulties？ This study surveys the research, analyzes the factors affecting the economic area formation of fresh vegetable plantation at suburb of rio Chi Minh City.

Mapping Spatial Distribution Characteristics of Lineaments Extracted from Remote Sensing Image Using Fractal and Multifractal Models

Mapping mineral prospectivity in vegetated areas is a challenge. For this reason, we aimed to map spatial distribution characteristics of linear structures detected in remote sensing images using fractal and multifractal models. The selected study area was the Pinghe District of the Fujian Province（China）, located in the Shanghang-Yunxiao polymetallic and alunite ore belt（within the Wuyishan polymetallic belt）, where mineral resources such as copper, molybdenum, gold, silver, iron, lead, zinc, alunite and pyrophyllite have been discovered. The results of our study showed that：（1） the values of fractal dimension for all lineaments, NW-trending lineaments, and NE-trending lineaments, are 1.36, 1.32, and 1.23, respectively, indicating that these lineaments are statistically self-similar;（2） the fractal dimensions of the spatial distribution of the linear structures in the four selected hydrothermal-type ore deposits of the Pinghe District, named Zhongteng, Panchi, Xiaofanshan and Fanshan, are 1.43, 1.52, 1.37 and 1.37, respectively, which are higher than the mean value in South China;（3） the spatial distribution of the linear structures extracted from the remote sensing image and displayed by the contour map of fractal dimensions, correlates well with the known hydrothermal ore deposits; and（4） the results of the anomaly map decomposed by the spectrum-area（S-A） multifractal model is much better than the original fractal dimension contour map, which showed most of the known hydrothermal-type deposits occur in the high anomalous area. It is suggested that a high step tendency possibly matches with the boundary of the volcanic edifice and the deep fault controlling the development of the rock mass and the volcanic edifice. The complexity of the spatial distribution of mapped lineations（faults） in the Pinghe District, characterized by high values in the anomaly map, may be associated with the hydrothermal polymetallic ore mineralization in the study area.

Field assessment of bacteria and nutrient removal by vegetative filter strips

Strategies are sought to reduce the impact of nonpoint sources of pollution,including fecal bacteria,and meet TMDL criteria.Vegetative filter strips(VFSs)are one such strategy,though the data of VFS function under field conditions,particularly for fecal bacteria,are limited.The objective of this study was to evaluate the efficiencies in removing fecal bacteria,N,and P from VFSs installed to treat contaminated runoff from a working feedlot.VFSs were found to be effective in removing a broad range of constituents from beef feedlot runoff pretreated by a settling basin.The first 30 m provided most or all of the reductions found within the 150 m VFSs studied:reductions average 85%of inflow water,85%of sediment,77%of N,and 84%of P.Fecal bacteria removal by the VFSs was about one order of magnitude:reductions at 30 m ranged from 83.5%for FC and FS to 91%for E.coli.On the site being studied,this provided an important level of protection and reduced surface-flow concentrations of fecal coliforms to below the 200 CFU/100 mL(coliform-forming units,CFU)water-quality standard for Kansas.