Home > Other Scientific Research Area > Enviormental Science > Volume-6 > Issue-4 > Analysis on the Impact of Saihanba Forest Farm on Ecological Environment

Analysis on the Impact of Saihanba Forest Farm on Ecological Environment

Call for Papers

Volume-6 | Issue-6

Last date : 26-Oct-2022

Best International Journal
Open Access | Peer Reviewed | Best International Journal | Indexing & IF | 24*7 Support | Dedicated Qualified Team | Rapid Publication Process | International Editor, Reviewer Board | Attractive User Interface with Easy Navigation

Journal Type : Open Access

Processing Charges : 700/- INR Only OR 25 USD (for foreign users)

First Update : Within 7 Days after submittion

Submit Paper Online

For Author

Research Area



Analysis on the Impact of Saihanba Forest Farm on Ecological Environment


Wenjing Ai | Bo Wang | Xin Lin



Wenjing Ai | Bo Wang | Xin Lin "Analysis on the Impact of Saihanba Forest Farm on Ecological Environment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-4, June 2022, pp.383-390, URL: https://www.ijtsrd.com/papers/ijtsrd50025.pdf

If people do not fail the green hills, the green hills will not fail people. Ecological civilization is a historical trend in the development of human civilization. In this paper, the indicators of social, geographical and meteorological factors that mainly affect the ecological environment in the Saihanba forest farm were selected. The data of 10 indicators, such as environmental management index, forest cover area and dryness in Saihanba Mechanical Forestry from 1962 to 2020 were collected, and the entropy-weight-AHP fuzzy comprehensive evaluation model was applied to quantitatively evaluate the ecological environment of Saihanba in 1962 and 2020 respectively, and the analysis shows that the ecological environment score of Saihanba in 2020 has increased significantly, which is about twice of the ecological environment score in 1962.In summary, the modeling approach used in this paper is analyzed and summarized. Through intelligent use of analogical techniques, quantitative and qualitative analysis, the model in this paper is highly accurate and reasonable.

Saihanba; ecological environment construction; AHP-entropy weight method; fuzzy comprehensive evaluation


IJTSRD50025
Volume-6 | Issue-4, June 2022
383-390
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

Thomson Reuters
Google Scholer
Academia.edu

ResearchBib
Scribd.com
archive

PdfSR
issuu
Slideshare

WorldJournalAlerts
Twitter
Linkedin