Development of Green Zone Energy Mapping for Community-based Low Carbon Emissions

Abstract

The world is heading to digital industrial 4.0; this means everything must be connected. In another-word, energy consumption demand will elevate exponentially scale. Smart-green sources are being substantial to save the sustainability of energy and the environment. The development of green energy alternatives, with low-zero emission sources, becomes potential. However, the urban-city initiative's monitoring and active-management energy pattern are more effective than investing in a new renewable energy source. This paper proposes a new method to build a regulation-system that monitors excessive energy used from the radiance threshold of night-time satellite data. This research dataset consists of light-meter surveys, DMSP-OLS and NPP-VIIRS night-time satellite datasets, and other supporting data. The outcome is a class-criteria zone energy map with three criteria class, ambient, moderate, and excessive. The radiance threshold class determined from cross-analysis of night-time satellite data with light-meter surveys through regression analysis. The histogram of radiance distribution reveals the profiling of the class-criteria. Results show moderate-class becomes a key to attention and can be used to disclose any aspect of spatial-temporal dynamical of urban-cycle. By using this method provides an effective way of assessing energy uses with space-technology.