Green vegetation cover has steadily increased since establishment of community forests in Western Chitwan, Nepal

Dai, J., Roberts, D. A., Stow, D. A., An, L. and Zhao, Q. (2020) Green vegetation cover has steadily increased since establishment of community forests in Western Chitwan, Nepal. Remote Sensing, 12(24), 4071. (doi: 10.3390/rs12244071)

Abstract

Community forests have been established worldwide to sustainably manage forest ecosystem services while maintaining the livelihoods of local residents. The Chitwan National Park in Nepal is a world-renowned biodiversity hotspot, where community forests were consolidated in the park’s buffer zone after 1993. These western Chitwan community forests stand as the frontiers of human–environment interactions, nurturing endangered large mammal species while providing significant natural resources for local residents. Nevertheless, no systematic forest cover assessment has been conducted for these forests since their establishment. In this study, we examined the green vegetation dynamics of these community forests for the years 1988–2018 using Landsat surface reflectance products. Combining an automatic water extraction index, spectral mixture analysis and the normalized difference fraction index (NDFI), we developed water masks and quantified the water-adjusted green vegetation fractions and NDFI values in the forests. Results showed that all forests have been continuously greening up since their establishment, and the average green vegetation cover of all forests increased from approximately 30% in 1988 to above 70% in 2018. With possible contributions from the invasion of exotic understory plant species, we credit community forestry programs for some of the green-up signals. Monitoring of forest vegetation dynamics is critical for evaluating the effectiveness of community forestry as well as developing sustainable forest management policies. Our research will provide positive feedbacks to local community forest committees and users.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhao, Dr Qunshan

Creator Roles

Zhao, Q.: Conceptualization, Writing – review and editing

• Authors: Dai, J., Roberts, D. A., Stow, D. A., An, L., and Zhao, Q.
• College/School: College of Social Sciences > School of Social and Political Sciences > Urban Studies
• Journal Name: Remote Sensing
• Publisher: MDPI
• ISSN: 2072-4292
• ISSN (Online): 2072-4292
• Copyright Holders: Copyright © 2020 The Authors
• First Published: First published in Remote Sensing 12(24):4071
• Publisher Policy: Reproduced under a Creative Commons licence

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
190698		Urban Big Data Research Centre	Nick Bailey	Economic and Social Research Council (ESRC)	ES/L011921/1	S&PS - Urban Big Data
304042		UBDC Centre Transition	Nick Bailey	Economic and Social Research Council (ESRC)	ES/S007105/1	S&PS - Administration