In the eve of the Beijing Olympics Games, Qingdao in China, as the host city of OSC of Beijing 2008 Olympic Games, was surrounded by <i>Enteromorpha prolifera</i>, which was followed with interest by whole China and the world. The Enteromorpha often comes from other ocean, monitoring the drifting path of the Enteromorpha will become very important.The Study area is mainly the Yellow Sea. And the data sources are Terra MODIS 1B images from 2000-2010 years. The data preprocessing include BOW-TIE processing, image registration, clip, merge, and masking. And the NDVI was selected as the index of derived<i> Enteromorpha prolifera </i>information, to get the range of <i>Enteromorpha prolifera</i>, and get that of dynamic change with time, and monitor the drifting path of the <i>Enteromorpha</i>.
This article utilized aerosol product of MODIS and aerosol data provided by AERONET which is real-time monitoring data about aerosol in a station to study spatial-temporal changes of aerosol in the Yellow Sea of China in 2006, and adopted some indexes such AOD (Aerosol Optical Depth) and Angstrom index (α and β), and analyzed monthly distribution and annual average of aerosol. The result suggested that AOD had significant negative correlation with Angstrom-α (r=-0.7261), and significant positive correlation with Angstrom-β (r=0.9576), and Angstrom-α had significant negative correlation with Angstrom-β (r=-0.8791). AOD and Angstrom-β came up to the maximum in Spring, then in Summer and Winter, and down to the minimum in Fall in the study area, and Angstrom-α was completely opposite. AOD and Angstrom-β had a upward trend from offshore to deep sea area, and from the north to the south of the Yellow Sea, while Angstrom-α had a downward trend. Analysis of Angstrom-α displayed that the offshore was polluted by small particles from anthropic activities, and the main content of aerosol was large particle of sea salt in the deep sea field. The main type of aerosol was consisted of small particle aerosol emitted from anthropic activities in Summer and Fall, and of sea-salt particle in Spring and Winter in the Yellow Sea. Spatially the diameter of aerosol in the north of the sea was bigger than one in the south. This study obtained the general distribution spatially and temporally in the Yellow Sea of China, and especially the fact that the main content of aerosol in the offshore was small particle from anthropic activities was paid attention to
The wetland is one kind of very important ecosystem on the Earth. Lianyungang has a large amount of wetland which are
decreased in area and ecosystem function in recent decades. The purpose of this paper is to extract wetland information
and assess ecosystem health of coastal wetlands in Lianyungang. The TM images of 1987 and 2009 were used to extract
wetland information through visual interpretation and supervised classification methods. And nine indexes were used to
establish the evaluation system for the methods of single-factor and PSR (Pressure-State-Response) model used to
evaluate wetland ecosystem health of Lianyungang. The results showed that: Coastal wetland of Lianyungang is
decreasing in area, and has general level of wetland ecosystem health; Natural sate of wetlands has some change;
External pressure is large. The ecological function has a certain degree of degradation, and the ecosystem can still
The MODIS land surface temperature data were used to analysis the temporal and spatial characteristics of heat island of
Lianyungang. Based on preprocessing data, this paper mainly discuss the relationship between urban heat island and its
ground, vegetation, illumination and man-made features, specifically analyze the influences of these factors to urban heat
island in Lianyungang. The results showed that: the city heat island has a close relationship with the degree of the
urbanization (city buildings, population number, population density, industry development, transportation, and so on),
geographic conditions, human activity manner, etc.; and the urban heat island intensity is strongest at autumn and winter,
weakest at summer. Finally, we give some suggestions about heat island and building a technical system for
Lianyungang's future developing.
Lianyungang is one of the first 14 Chinese coastal cities opening to the outside world in 1984, she had developed about
20 years and has many changes in urban size or structure. And remote sensing has been an important technology for
monitoring city development and growth. So, this paper presented the developments and growths of Lianyungang using
TM data. Through the processing of three years TM data of 1987, 2000 and 2007 and extraction of urban information,
the results showed that three districts and four countries of Lianyungang had great change in size and shape. The results
showed that the changes of all county urban scale was relatively small from 1987 to 2000, and rapid sprawled from 2000
to 2007; and they sprawled in different direction. The counties except Lianyungang city had the same development
pattern which was centered on old city zone and spread to the surrounding area. The development mode of Lianyungang
city was different with them. It was a ribbon mode from west to east, namely from Haizhou, Xinpu districts to Lianyun
districts. The status of developments of all districts and counties was related to the needs of economic development,
traffic, policy and so on. At present Lianyungang obtains a lot of attention and support from the state and Jiangsu
Province, and has changes everyday.
Ocean primary productivity is the ability that the ocean primary producers convert inorganic matter into organic matter
through the assimilation. It is an important parameter used to estimate ocean biological resources and reflect the
characteristics and quality of the ocean ecological environment. With the development of ocean color remote sensing, it
has become possible by using the satellite remote sensing to monitor the ocean primary productivity. So, this study
selected China's coastal ocean (0°- 41°N, 105°- 130°E) as the main location, used NPP products of SeaWiFS estimated
from VGPM (Vertically Generalized Production Model), Eppley-VGPM and CbPM (Carbon-based Production Model)
from 1998-2007 to research the characteristics of space distribution and dynamic changes of NPP with time. The results
showed that: these models result have many same aspects and have many differences; the mean NPP of VGPM in all
ocean regions have two peaks, that of Eppley-VGPM and CbPM just have one peak; the NPP of China coastal ocean has
obviously seasonal and apatial variation. In time, the lowest value of NPP was in winter and the highest was in spring
and summer; in space, the Bohai and the Yellow Sea had relatively high NPP, relatively low value of the NPP was in
South China Sea.
Leaf area index (LAI) is a critical vegetation parameter for the global and regional scale studies of the climatic and environmental change. There are many methods that can be used to get LAI. In this paper, the method, developed by Qi et al. (2000) was selected. The process includes three steps: the first step is model inversion, using BRDF model to produce LAI with pixels chose randomly in one vegetation type region; the second step is quality control, removing the outliers, fitting equations using the LAI from second step and satellite data NDVI; the third step is LAI mapping, selecting the best equation and applying it to the whole region to mapping spatial LAI distribution. The main objective of this paper is to get one method that can be used in Arid and Semi-arid Northwestern China to derive LAI in the case of lack of LAI measurements. The results derived by the above approach were compared with ones derived from the empirical method (Sellers et al. 1996) and the LAI measured in field. The results suggested that the method can get good result and R<sup>2</sup> was 0.7947, though they were greater than field measurements. The results from empirical method were closer to the measurements than ones from Qi's method, but the higher the values of NDVI were, the greater the values of estimated LAI were than LAI measurements, when the values of NDVI were greater than a certain values (here 0.74). However, the result derived from Qi's method is closer to the LAI measured in field. In general, this method was feasible in arid and semi-arid northwestern China and can get satisfactory results.
Community land model or common land model (CLM) describes the exchange of the fluxes of energy, mass and momentum between the earth's surface and the planetary boundary layer. This model is used to simulate the environmental changes in China. Hence, it requires a complete parameters field of the land surface. The present paper focuses on making the surface datasets of CLM in China. In the present paper, vegetation was divided into 39 Plant Function Types (PFTs) of China from its classification map. The land surface datasets were created using vegetation type, five land cover types (lake, wetland, glacier, urban and vegetated), monthly maximum Normalized Difference Vegetation Index (NDVI) derived from SPOT_VGT data and soil properties data. The percentages of glacier, lake and wetland were derived from their own vector maps of China. The fractional coverage of PFTs was derived from China vegetation map. Time-independent vegetation biophysical parameters, such as canopy top and bottom heights and other vegetation parameters related to photosynthesis, were based on the values documented in literatures. The soil color dataset was derived from landuse and vegetation data based on their correspondent relationship. The soil texture (clay%, sand% and silt%) came from global dataset. Time-dependent vegetation biophysical parameters, such as leaf area index(LAI) and fractional absorbed photosynthetically active radiation(FPAR), were calculated from one year of NDVI monthly maximum value composites for the China region based on equations given in Sellers <i>et al</i>. (1996a,b) and Los <i>et al</i>. (2000). The resolution of these datasets for CLM is 1km.
Leaf area index (LAI) is an important characteristic of vegetation and a critical vegetation parameter for the global and regional scale studies of the climatic and environmental change. There are many methods that can be used to get LAI, generally, they belong to the three types: filed measurement; empirical and modeling methods. In this paper, we try to get one method that can be used in Arid and Semi-arid Northwestern China to derived LAI in the case of lack of LAI measurements. The empirical method was selected to derive LAI for different type vegetation from SPOT-VGT and landuse data. The study area was the Heihe River basin that has a large-scale area and diverse vegetation types. There were 7 types of vegetation to be mapping LAI using the methodology. They were irrigated, dry, forest, shrub, dense grass, moderate-dense grass and alkaline lands. The parameters of vegetations were modified based on the study area and vegetation types. The results were compared with the whole China LAI map and filed measured LAI. The results suggested that the method was feasible in arid and semi-arid northwestern China. And the results could be greatly improved if using big scale vegetation class map or plant function type data, and the parameters were derived based on the vegetation types in their own region.