Study On Extraction And Application Of Impervious Surface Area Information In Yantai City

Urban area has been subjected to the attention of researchers since it is the mostpowerful source of economic development. Although now urban area covers a smallfraction of the earth land area, it has had profound impact on the development of riverbasin and even the global environment. High-speed urban expansion has producedincalculable damage to the sustainable development of the environmental andsocial-economic-ecological systems, and these repercussions should be directed moreattention by decision makers to make informed decisions which could balance thepositive and negative aspects of urban sprawl to ensure sustainable development.Impervious surface refers to the artificial surface through which water cannotpenetrate into the soil, such as roads, parking lots, buildings, roofs, etc. In recent years,impervious surface became an indicator of the urbanization degree; at the same time,impervious surface is also an important indicator of urban environmental quality. It isof significance to extract and monitor impervious surface area for environmentalmonitoring and urban planning.The extraction methods of urban impervious surface based on remotely sensedimages can be divided into per-pixel classification and sub-pixel classification.Per-pixel classification utilizes traditional methods such as maximum likelihoodmethod to monitor and extract the urban impervious surface area information inremote sensing images; sub-pixel classification algorithms decompose pixels,defining the impervious surface information depending on the density of impervioussurface.Jiaodong Peninsula is the largest peninsula and is one of the most developedeconomical areas in China. Yantai is one of the most representative mid-sized coastalcities in China with150years history since it opened the harbor for internationalbusiness in May1861. Now it is the largest fishing seaport and the second largestindustrial city in Shandong province. With the help of multitemporal remote sensingimages, it is of great practical significance to take Yantai city as the case study area toextract and monitor Yantai city’s impervious surface information. However, until nowthere is no research studying the impervious surface information extraction in Yantaicity. In this study, Yantai City, Jiaodong peninsula, was chosen as the case study area,the Landsat TM/ETM+remotely sensed images of1989,1995,1999,2000,2006and2009were selected as the main data sources, and China-Brazil Earth ResourcesSatellite images, digital elevation model data, land use maps and vector administrativedata were chosen as the auxiliary data. Image resolution and unity, imageenhancement, registration, geometric correction, minimum noise fraction, pixel purityindex transform were performed to the images. After that, the vegetation-impervioussurface area-soil (V-I-S) model and normalized spectral mixture analysis (NSMAS)model were used to extract the impervious surface area density component diagram tostudy the urban developing dynamics of Yantai city. Then the percent impervioussurface area was introduced into the decision tree classification method as thedecision rules to classify the land covers of the case study area in order to improve theaccuracy of monitoring the land cover change in Yantai city; and it was also used toexplore the relationships of percent impervious surface area and surface temperaturepreliminarily.The results showed that:(1) It is of high accuracy to combine vegetation-impermeable surface area-soil modeland the normalized spectral mixture analysis model for the extraction of theimpervious surface density of Yantai city, and the density information can be used asthe foundation data for the further researches;(2) The low-density and medium density area of Yantai city still cover a large urbanareas, generally Yantai city is still in the low-density development stage.(3) The accuracies of decision tree classification methods taking the three phases ofthe Yantai urban impervious surface density as decision rules were highest among thethree classification methods (Impervious surface area-decision tree method, maximumlikelihood method and artificial neural network classification method as comparison).Statistics of the classification results found that from1989to2009, the extendingimpervious area of Yantai City accounted to approximately35.83km2, and wastransferred from agricultural land, bare land and vegetation land cover areas;(4) The study of the relationships between percent impervious surface and landsurface temperature, normalized difference vegetation index and land surface temperature extracting from the four different seasons of1995,2000,2006and2009.The results demonstrated that there was a strong linear relationship between landsurface temperature and percent impervious surface area for the four seasons, whilethe linear relationship between land surface temperature and normalized differencevegetation index is much less strong and is seasonal effected. The results suggest thatpercent impervious surface area provides an alternative parameter to the typicalnormalized difference vegetation index for analyzing land surface temperaturequantitatively in urbanized environments.