Land Use Change Statistics Research Articles

Monitoring spatial LULC changes and its growth prediction based on statistical models and earth observation datasets of Gautam Budh Nagar, Uttar Pradesh, India

It is well known and witnessed the fact that in recent years the growth of urbanization and increasing urban population in the cities, particularly in developing countries, are the primary concern for urban planners and other environmental professionals. The present study deals with multi-temporal satellite data along with statistical models to map and monitor the LULC change patterns and prediction of urban expansion in the upcoming years for one of the important cities of Ganga alluvial Plain. With the help of our study, we also tried to portray the impact of urban sprawl on the natural environment. The long-term LULC and urban spatial change modelling was carried out using Landsat satellite data from 2001 to 2016. The assessment of the outcome showed that increase in urban built-up areas favoured a substantial decline in the agricultural land and rural built-up areas, from 2001 to 2016. Shannon’s entropy index was also used to measure the spatial growth patterns over the period of time in the study area based on the land-use change statistics. Prediction of the future land-use growth of the study area for 2019, 2022 and 2031 was carried out using artificial neural network method through Quantum GIS software. Results of the simulation model revealed that 14.7% of urban built-up areas will increase by 2019, 15.7% by 2022 and 18.68% by 2031. The observation received from the present study based on the long-term classification of satellite data, statistical methods and field survey indicates that the predicted LULC map of the area will be precious information for policy and decision-makers for sustainable urban development and natural resource management in the area for food and water security.

Strategies for Assessing the Impact of Survey Lags on the Analysis and Interpretation of Land Use Change Statistics

The Department of the Environment's Land Use Change Statistics (LUCS) represent a major new data series in the field of town and regional planning. They begin to fill a long-standing and, given the land management aims of planning, rather basic gap in the planning data record and have the potential to change the way in which we approach land-use studies and policy monitoring. LUCS data are derived from the process of updating Ordnance Survey mapping and, as a consequence, are recorded with a time lag between date of change and date of survey that varies according to survey regime and land-use type. In the analysis of LUCS data it is essential that an appropriate allowance is made for both the temporal and the spatial incidence of survey lags. In this paper we will discuss three approaches to reducing the impact of recording lags on particular types of substantive research: use of LUCS data based on analysis by survey year, the construction of robust indicators of land-use change, and the fitting of modelled lag descriptions. We conclude with a brief discussion of the implications for land-use theory in general.

The Collection of National Land-Use Statistics in Great Britain: A Critique

The collection of land-use change statistics under DoE Circular 71/74 is criticised on three grounds. First, there is no standard land-use classification employed consistently by all local authorities. Second, there is no standard and unambiguous set of areal units to which such a classification could be applied. Third, there is no efficient means of collecting land-use data in a form which meets the information needs of policymakers. Adoption of a standard land-use classification applied to functional units is advocated. It is argued that point sampling is a cheap and efficient means of collecting land-use statistics in a form which meets planning needs. The advantages of point sampling compared with alternative techniques are considered in detail.