Abstract

Combined heat and power (CHP) schemes have the potential for reducing residential heating costs. As these schemes use waste heat from electricity generation, the power station associated with them must, for reasons of efficiency, be near to a region where the heat usage per unit area (heat-load density) is high. To plan CHP schemes, the heat-load density of urban areas needs to be mapped and monitored. To calculate heat-load density for residential areas workers have conventionally multiplied the number of dwellings per unit area by the average head-load per dwelling. This is time-consuming and must be repeated in full, for each resurvey. In this paper the use of remotely sensed data from the Landsat Multispectral Scanning System (MSS) to estimate heat-load density is proposed. A survey using these data for the City of Sheffield was faster and no less accurate than a survey performed by conventional means. However, Landsat MSS data were unable to discriminate between more than four classes of heat-load density, a level of discrimination that may be increased if Landsat Thematic Mapper (TM) or SPOT High Resolution Visible (HRV) data were to be used in future surveys of this kind.