A concept of satellite-based IoT for downscaling the MODIS data to extract Land Surface Temperature

Internet of Things (IoT) is a key concept that makes the revolution in the present era to make the world smarter. By combining the key technologies, the pace of the processing and delivering of information can be changed. Now, in the context of agriculture monitoring where crop health depends on several parameters like LST, soil moisture, precipitation, etc., therefore timely information of these parameters are playing a major role for monitoring the crop health. These parameters are provided by various satellite sensors which are having different spatial and temporal granularity, therefore in this paper, a new concept of satellite-based IoT is proposed by which we can retrieve all the information at the single platform the power of cloud (storage and processing). The proposed approach tries to extract Land Surface Temperature (LST) automatically from the MODIS data on a spatial equivalent of Landsat 8 which leads to a motivation of providing LST having single day temporal granularity. The basic challenge to handle and efficiently use huge data that can be overcome easily by cloud and its computing.