Application of Land Surface temperature from Landsat series to monitor and analyze forest ecosystems: A bibliometric analysis

Abstract

Aim of study: Land surface temperature (LST) is an essential variable to monitor and characterize forest ecosystems. This variable has been consistently captured for almost four decades by the Landsat program. The current study aimed at identifying trends, knowledge gaps and opportunity areas in the use of Landsat derived LST for the monitoring and analysis of forest ecosystems. Materials and methods: A bibliometric analysis of scientific articles indexed in Scopus in the period 1995-2020 was conducted. Main results: Annual increase rate in the number of publications on the topic analyzed was 22.58%. The journal with more publications on the topic was Proceedings of SPIE, followed by Remote Sensing. The authors with the highest productivity on this topic were C. Quintano, I. Vorovencii, O. E. Yakubailik and M. A. Zoran. Regarding productivity by country, 38 countries with publications on this topic were identified, with the highest productivity located in China, USA and India. This group of countries also represented the most solid network of cooperation between countries. Forest ecosystems more frequently analyzed were temperate forests, followed by tropical forests. The analysis of keywords highlighted topics such as remote sensing, NDVI, MODIS and evapotranspiration. The analysis of thematic evolution indicated that areas of research and interpretation of LST data has evolved in parallel with remote sensing areas. Research highlights: Landsat LST analysis is an evolving topic with potential to contribute to improve ecosystem knowledge and to support diverse challenges in forest resources decision-making.