Advances in Vegetation Structure Modelling Using Remote Sensing to Support the Acquisition of Sustainable Development Goals through Forest Management-Reference-Cited by-同舟云学术

Advances in Vegetation Structure Modelling Using Remote Sensing to Support the Acquisition of Sustainable Development Goals through Forest Management

Published:2023-09-18 Issue:18 Volume:15 Page:4589
ISSN:2072-4292
Container-title:Remote Sensing
language:en
Short-container-title:Remote Sensing

Author:

Lamelas María Teresa¹²^ORCID,Domingo Darío²³^ORCID

Affiliation:

1. Centro Universitario de la Defensa Zaragoza, Academia General Militar, Ctra. de Huesca s/n, 50090 Zaragoza, Spain

2. GEOFOREST-IUCA, Department of Geography, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Spain

3. EiFAB-iuFOR, University of Valladolid, Campus Duques de Soria, 42004 Soria, Spain

Abstract

Forest ecosystems cover 31% of the world [...]

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Link

https://www.mdpi.com/2072-4292/15/18/4589/pdf

Reference14 articles.

1. FAO, and UNEP (2020). The State of the World’s Forests 2020. Forests, Biodiversity and People, FAO.

2. Latifi, H., and Heurich, M. (2019). Multi-Scale Remote Sensing-Assisted Forest Inventory: A Glimpse of the State-of-the-Art and Future Prospects. Remote Sens., 11.

3. Forest Structure. A Key to the Ecosystem;Trofymow;Proceedings of the Workshop on Structure, Process, and Diversity in Successional Forests of Coastal British Columbia,1998

4. Tupinambá-Simões, F., Pascual, A., Guerra-Hernández, J., Ordóñez, C., de Conto, T., and Bravo, F. (2023). Assessing the Performance of a Handheld Laser Scanning System for Individual Tree Mapping—A Mixed Forests Showcase in Spain. Remote Sens., 15.

5. Martínez-Rodrigo, R., Gómez, C., Toraño-Caicoya, A., Bohnhorst, L., Uhl, E., and Águeda, B. (2022). Stand Structural Characteristics Derived from Combined TLS and Landsat Data Support Predictions of Mushroom Yields in Mediterranean Forest. Remote Sens., 14.