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1.
PLoS One ; 15(11): e0240739, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33147229

RESUMO

The paper explores seasonal movements of Bronze Age mobile pastoralists in the western Tianshan mountainous region of Xinjiang, China. Fieldwork by a team from the Institute of Archaeology of the Chinese Academy of Social Science (CASS) and the University of Sydney, Australia have identified cyclical land use practices associated with the Andronovo cultural complex. Their pattern of seasonal movements has been reconstructed through ethnographic studies and analysis of modern snow and grass cover. Using this detailed combination of data, the study defines requirements for seasonal pastures-winter, summer and spring/autumn-and shows a clear correlation between modern land use and seasonal patterns of movement in the Bronze Age.


Assuntos
Criação de Animais Domésticos/métodos , Migração Humana , Gado/crescimento & desenvolvimento , Estações do Ano , Algoritmos , Altitude , Animais , Arqueologia , China , Fósseis , Geografia , Humanos , Gado/classificação , Modelos Teóricos , Poaceae/crescimento & desenvolvimento , Neve
2.
Sensors (Basel) ; 19(22)2019 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-31698853

RESUMO

The temporal analysis of land surface temperature (LST) has generally been studied using data from the same season, as temperature varies greatly over time. However, the cloud cover in thermal remotely sensed images and the coarse resolution of passive sensor system significantly limits data availability of same season for comparative temporal analysis in many parts of the world. To address this problem, we propose a new method for temporal monitoring of surface temperature based on LST normalization (LSTn); deploying the average open water temperature to normalize LST when monitoring temporal change in the surface temperature of newly coastal reclaimed areas. This method was applied in the Lingding Bay area, Guangdong Province, Southern China. Original LST and LSTn values were calculated for years 1987, 1997, 2007, and 2017. In contrast to the original LST, results show that LSTn can reduce seasonal variability when monitoring temporal change in surface temperatures. Additionally, LSTn revealed pronounced differences between the temperature of impervious surfaces and other land cover types. This method offers more robust detection of surface urban heat islands than original LST in newly developed coastal areas.

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