Urban expansion: a geo-spatial approach for temporal monitoring of loss of agricultural land

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International Archives for Photogrammetry and Remote Sensing


This paper presents some preliminary results from research on monitoring the urban growth of Shenzhen in China. Agriculture is still the pillar of national economies in many countries including China. Thus, agriculture contributes to population growth. Population growth follows either exponential or logistic growth models. These models can be examined using a time-series of geospatial data, mainly historical earth observation imagery from satellites such as LANDSAT. Such multitemporal data may provide insights into settlement analysis as well as on population dynamics and hence, quantify the loss of agricultural land. In this study, LANDSAT data of ten dates, at approximately five yearly intervals from 1977 to 2017 were used. The remote sensing techniques used for analysis of data for 40 years were image selection, then followed by geometric and radiometric corrections and mosaicking. Also, classification, remote sensing image fusion, and change detection methods were used. This research extracted the information on the amount, direction, and speed of urbanization, and hence, the number of hectares of agricultural land lost due to urban expansion. Several specific elements were used in the descriptive model of landscape changes and population dynamics of the city of Shenzhen in China. These elements are: i) quantify the urban changes, from a small town (37.000 people in the early 1970’s) to the megalopolis of around 20 million habitants today. ii) Examining the rate of urban extension on the loss of agricultural landscape and population growth. iii) The loss of food production was analysed against the economic growth in the region. iv) The aspects of loss of agricultural land, area of built-up urban land, and increase in population are studied quantitatively, by the temporal analysis of earth observation geospatial data. The experimental results from this study show that the proposed method is effective in determining loss of agricultural land in any city due to urbanization. It can be used by town planner and other stakeholders such as land surveyors and agriculture experts to mitigate the mushrooming of unplanned settlements in many town / villages and loss of land for agriculture which might cause problems in food security.



urbanization, land use, agricultural, image fusion, remote sensing, geospartial