East Java Province GRDP Projection Model Using Night-Time Light Imagery

Abstract

Economic growth, regional development, and human activities are some of the things that are very strongly related and influence each other. Approaches to forecasting the growth of the three are mostly carried out using both conventional and non-conventional data. Utilization of Nighttime Light Imagery satellite imagery is included in a non-conventional approach to forecasting Gross Regional Domestic Product. This study applies the use of satellite imagery to predict the regional development of East Java Province, to find patterns of agglomeration and the formation of clusters of economic development in the future.

Using Histogram Extracted from Satelite Imagery and Convolutional Network to Predict GRDP in Java Region

“…NTL imagery data has been widely used to describe socio-economic activities in a coverage area, including estimating electricity consumption [7], extracting builtup areas [8], estimating house rental costs [9], estimating poverty [10], estimating human development index [11], estimating impact of disasters [12], and also to estimate GDP [13]. This is due to the ability of NTL imagery to capture light intensity in an area at night which has a strong correlation with socio-economic activity.…”

“…Most of the methods used to estimate GRDP use conventional statistical methods and machine learning methods. [13], [14] used the linear regression method to perform cross-sectional and time series analyses, [15] used the correlation index to create an ELIM model, and [17] used the isolation forest method to estimate GRDP in rural areas. [18] used the SVM, Random Forest, Lasso, and Enet methods to estimate GRDP in Java and create microregional GRDP.…”