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.
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