Nearest Neighbor Method to Estimate Urban Areas Using Modis Ndvi Time Series

Time series of satellite images allows better monitoring and detecting the dynamics of urban growth. The objective of this research is to detect the urban area between the city of Rio de Janeiro and São Paulo in the period of 2014-2015 using MODIS digital time series. We used the product MOD13Q1 referring to the Normalized Difference Vegetation Index (NDVI) 16-day composite data, with spatial resolution of 250 meters. The high variety of elements imposes a great difficulty in mapping urban areas. Therefore, we calculated the nearest neighbor using the Euclidian distance for each time signature. The different image group of the urban targets were into a single image considering the minimum value of each pixel within the set. Therefore, a limit value separated the urban areas from the rest. This methodology allowed the detection of urban areas considering their diversity. The algorithm is written in C ++ language.