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This study analyses some characteristics of ancient construction and clarifies how they used renewable energy in their homes. This article analyzes ancient houses that were nature-oriented and used renewable energy. This study focuses on the structural system of ancient houses in Sistan. It dissects the structural elements of the old homes. The autopsy of the ancient house structure of Sistan shows the reader the techniques used in ancient architecture to provide energy. The research methods of this article are to examine the energy supply experiences of houses in the form of a case study of an old Sistan house to discover their energy-supplying techniques. This article uses the techniques used in Sistani houses with the application of modern house-building technologies, to develop a nature-oriented model. In fact, the model presented in this article is a modernized version of the ancient house of Sistan. This model gives a house completely friendly to nature and the environment and knowledge-oriented. The model contributes to housing programs addressing new requirements. Our proposed housing model and its general principles are replicable in other regions globally to use green energy sustainably. [ABSTRACT FROM AUTHOR]

The development of urbanization and the transformation of green lands into impermeable land increase temperature and create urban heat islands (UHIs). Our observations with remote sensing instruments of Landsat platforms show considerable changes in land use types in Beijing city with the shrinking of green lands, expansion of built environments, and a slight increase in the temperature during the recent four decades. Using remote sensing instruments of Landsat platforms and registered data from two meteorological stations in Beijing, this study finds the relationship between land surface temperature (LST) and the increasing conversion of cultivated lands into built-up areas. This article presents innovative research that shows the mutual correlation well and recommends revisions in the land use policies for better weather. The geographically weighted regression model (GWR) with a Gaussian weighting kernel function analyzes the impact of various urban land use types on the LST and the increase UHIs. In Beijing city, green lands show fewer standard deviations (SD) in the average temperatures equal to 0.109, while the industrial spaces exhibit a high SD equal to 0.212. The outcomes of this paper contribute to finding optimal land use policies everywhere in the world with the increasing urbanization through simulating its model for a more comfortable life. [ABSTRACT FROM AUTHOR]