A review study on urban cities land classification accuracy using remote sensing and social communication network techniques.

This research focus on the urban land uses and covers techniques that have used for classification and mapping which is considered to be one of the main aspects of the decision making in the developing countries that urbanized widespread. Land use and land cover LULC classification and mapping are two aspects of decision making in developing countries with widespread urbanization, and can be used in climate change, agriculture, ecology, water quality, improving living conditions, and identifying and developing regional development plans. This classification and mapping used in climate change, agriculture, ecology, water quality, improving living standards and identifying and developing plans for regional development. Remote sensing imagery have been used for land cover and land uses classification and urban land mapping. However, there is limitation due to hardly identifying urban land use and land function issues due to the rare of high-resolution urban land use maps availability along with having a low accuracy. In this paper several different methods have been discussed adopted for this purpose including the use data from multisource remote sensing with WeChat mobile application data, Landsat 8 Imagery with open social data, and area of interest AOI method. All of these methods have proved to be successful in their area in urban land use mapping and LULC classification by giving an improved accuracy in mapping and classification. [ABSTRACT FROM AUTHOR]