Land Use Change Map Research Articles

The impact of interactions in spatial simulation of the dynamics of urban sprawl

This study investigated the modeling process for simulating the spatial dynamics of an urban ecosystem. Logistic regression is a common method for empirically modeling and analyzing land use and land use change. In most conventional applications of logistic regression, only the individual factors of the system are considered in the development of the logistic regression functions. However, this does not consider the relationships among factors that potentially occur within most ecosystems. Factors in a system, especially an urban system, are usually not fixed and not independent of each other, but rather are influenced by each other. Based on this point of view, the interactions of factors are introduced into a logistic regression in this study. This technique has been tested with a case study using historical land use maps and a spatially explicit dynamic cellular automata urban sprawl model. Using historical land use data, a logistic regression was used to analytically weight the scores of the driving factors of an urban sprawl model for predicting probability maps of land use change. The results of the case study have verified that interactions of factors can significantly improve the prediction of spatial dynamics of urban sprawl, and can provide a means to improve cellular automata models for simulation of the dynamics of urban and other ecosystems.

Monitoring land-use change in the Pearl River Delta using Landsat TM

The Pearl River Delta in the People's Republic of China is experiencing rapid rates of economic growth. Government directives in the late 1970s and early 1980s spurred economic development that has led to widespread land conversion. In this study, we monitor land-use through a nested hierarchy of land-cover. Change vectors of Tasseled Cap brightness, greenness and wetness of Landsat Thematic Mapper (TM) images are combined with the brightness, greenness, wetness values from the initial date of imagery to map four stable classes and five changes classes. Most of the land-use change is conversion from agricultural land to urban areas. Results indicate that urban areas have increased by more than 300% between 1988 and 1996. Field assessments confirm a high overall accuracy of the land-use change map (93.5%) and support the use of change vectors and multidate Landsat TM imagery to monitor land-use change. Results confirm the importance of field-based accuracy assessment to identify problems in a land-use map and to improve area estimates for each class.

Urban expansion and loss of agricultural land - a GIS based study of Saharanpur City, India

This paper uses remote sensing (aerial photographs and satellite images) combined with field checks and surveys to measure the loss of agricultural land to urban expansion in Saharanpur City between 1988 and 1998. It shows how such techniques allow a detailed mapping of land use changes and includes details of the location of the agricultural land losses, the nature of the land use changes that caused these and the quality of the agricultural land that was lost. The paper also describes which non agricultural land uses were responsible for most of the agricultural land losses and discusses what these findings imply for India and for other nations where urbanization is reducing the supply of high quality agricultural land.

Urban expansion and loss of agricultural land - a GIS based study of Saharanpur City, India

This paper uses remote sensing (aerial photographs and satellite images) combined with field checks and surveys to measure the loss of agricultural land to urban expansion in Saharanpur City between 1988 and 1998. It shows how such techniques allow a detailed mapping of land use changes and includes details of the location of the agricultural land losses, the nature of the land use changes that caused these and the quality of the agricultural land that was lost. The paper also describes which non agricultural land uses were responsible for most of the agricultural land losses and discusses what these findings imply for India and for other nations where urbanization is reducing the supply of high quality agricultural land.

A CARTOGRAPHIC SIMULATION MODEL OF THE EFFECTS OF ECONOMIC ACTIVITY ON THE ENVIRONMENT

The principles of systems mapping are employed in a model simulating the effects of human activity on the environment. The model takes the form of series of maps which are organized within three basic units or “blocks.” Block I contains general preliminary maps of land use and environmental change within an area which can serve as a basis for subsequent forecasting and proposals for improving land use. Block II contains maps that take stock of, evaluate, and predict human impacts on specific environmental components, and show the spatial distribution of measures proposed to ameliorate these impacts. Block III consists of maps synthesizing the component-related information of the preceding block for the purpose of providing summary assessments about the condition of the environment and land use conflicts in an area and targeting areas deserving the most comprehensive reclamation efforts. Methods of compiling the various maps are described in detail. Translated from: Izvestiya AN SSSR, seriya geograficheskaya, 1986, No. 2, pp. 114–127.