A Gis-based Analysis and Prediction of Land-use Change in a Coastal Tourism Destination Area

نویسندگان

  • Jeffery S. Allen
  • Kang Shou Lu
  • Thomas D. Potts
چکیده

South Carolina is the nation's second largest coastal resort state in terms of beach destination trips, superseded only by Florida. Its coastal resources and tourism industry are now undergoing tremendous coastal change due to tourism development and associated commercial and residential growth. As the negative elements of coastal change draw more public attention, and sustainable development becomes a goal for many coastal communities, the continuing coastal change associated with accelerated growth becomes a critical issue. Many agencies and organizations have initiated research programs to develop new techniques for obtaining timely and valid land-use change information to assist in coastal management. This study, as an integral part of a five-year multi-disciplinary and multi-institutional coastal research project funded by NASA/SC-EPSCoR, is designed to develop and apply GIS-based methodologies for analysis, modeling and prediction of coastal land-use change. It takes a micro approach to examine the parcel-based land-use change at the local scale. A spatial multivariate logistic regression model was developed and 20 variables were selected for predicting the possibilities of landuse change for Murrells Inlet. The results indicate that GIS has advantages over conventional methods in integrating various data sources, performing spatial analysis, modeling spatial process, and mapping the results in land-use change studies. It appears that building permits and parcel data should be used as alternative data sources for change detection and analysis because they contain detailed change information. They are available in digital format and can be updated on a regular basis as more local government agencies utilize GIS for creating and maintaining parcel maps. The logistic regression model used successfully predicted spatial land-use change. Both maps and statistical results show that the primary roads, commercial cluster, commercial zoning, private ownership, and land availability are significant predictor variables for commercial parcel land use. In addition, beachfront, open view, residential zoning, private ownership, land availability, primary roads and commercial centers are major factors that predict residential development. The results also indicate that Murrells Inlet has experienced tremendous land-use change over the last three decades. The recent period from 1982 to 1996 has brought about rapid residential growth, but little commercial development. The continuing growth appears to be transforming the area into a residential community for metropolitan Myrtle Beach. There is a significant difference in spatial preference between commercial and residential land uses with commercial parcels linearly distributed along the primary roads. As beachfront and waterfront areas are encroached mainly by seasonal homes, residential development moves inland though somewhat restricted by existing parklands and wetlands. Allen, Lu and Potts 288 Overall spatial patterns show that the area is lacking an integrated plan for development. Limited public access to waterfront and beachfront and the lack of a focal point in the business district are major problems from the tourism planning perspective.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A GIS-BASED ANALYSIS AND PREDICTION OF PARCEL LAND-USE CHANGE IN A COASTAL TOURISM DESTINATION AREA Presented at the 1999 World Congress on Coastal and Marine Tourism Vancouver, British Columbia, Canada

South Carolina is the nation’s second largest coastal resort state in terms of beach destination trips, superseded only by Florida. Its coastal resources and tourism industry are now undergoing tremendous coastal change due to tourism development and associated commercial and residential growth. As the negative elements of coastal change draw more public attention, and sustainable development b...

متن کامل

Organizing Coastal Land Use for Urban Tourism Development (Case Study: Sorkhrood)

Planning for land, as the main element of the environment and the most basic pillar of a settlement, for being the background of a life with health, comfort and satisfaction of the inhabitants, is very important. Tourism with a wide range of environmental, economic, social and physical impacts is one of the factors affecting the pattern of land use which, depending on the region's ability to at...

متن کامل

Estimation of acceptance capacity and assessment of ecological power in order to identification of tourism territorial arenas (case study: tourism complex of Potas located in Khor-o- biabanak

Introduction A huge influx of tourists on weekends from overcrowded metropolitan cities unable to provide tourists with the leisure needs of parks and natural areas to take advantage of the tourism potential of planners has led planners to capacity-building tourism development and location. Because the expansion of tourism has been accompanied by environmental and ecological incompatibilities...

متن کامل

Simulation and prediction of land use and land cover change using GIS, remote sensing and CA-Markov model

This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful...

متن کامل

Land use changes analysis and prediction using remote sensing and QGIS MOLUSCE Plugin in the Siahkal County

Quantifying land use change dynamics is critical in tackling environmental and socio-economic challenges such as climate change in recent years. This study takes Siahkal County in Guilan Province as the research subject and analyzes the land use changes in two different years: 2000 and 2021, and predicts the change in 2031. We carried out land use change analysis using LANDSAT-7 ETM+ and LANDSA...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003