NDLI: Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research

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Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research

Content Provider	MDPI
Author	Mariana-Daniela, González-Zamar Esteban, Vázquez-Cano Eloy, López-Meneses Abad-Segura, Emilio
Copyright Year	2020
Description	Research Highlights: the wide variety of multispectral sensors that currently exist make it possible to improve the study of forest systems and ecosystem services. Background and Objectives: this study aims to analyze the current usefulness of remote sensing in forest management and ecosystem services sciences, and to identify future lines of research on these issues worldwide during the period 1976–2019. Materials and Methods: a bibliometric technique is applied to 2066 articles published between 1976 and 2019 on these topics to find findings on scientific production and key subject areas. Results: scientific production has increased annually, so that in the last five years, 50.34% of all articles have been published. The thematic areas in which more articles were linked were environmental science, agricultural, and biological sciences, and earth and planetary sciences. Seven lines of research have been identified that generate contributions on this topic. In addition, the analysis of the relevance of the keywords has detected the ten main future directions of research. The growing worldwide trend of scientific production shows interest in developing aspects of this field of study. Conclusions: this study contributes to the academic, scientific, and institutional discussion to improve decision-making, and proposes new scenarios and uses of this technology to improve the administration and management of forest resources.
Starting Page	969
e-ISSN	19994907
DOI	10.3390/f11090969
Journal	Forests
Issue Number	9
Volume Number	11
Language	English
Publisher	MDPI
Publisher Date	2020-09-07
Access Restriction	Open
Subject Keyword	Forests Remote Sensing Forest Management Ecosystem Service Scientific Production Research
Content Type	Text
Resource Type	Article

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