INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This research is about the Correlation and Regression analysis in forest productivity, how the volume of a forest depends upon height and girth of the tree species in a particular habitat. It is very important for forest manager to know the productivity analysis for better management of biodiversity and sustainability. The correlation and regression of the data helps to analyze the dependency and determination of the volume using height and girth of the trees.
In an area taking the sample plots and conducting a survey for kind of tree species, their height and girth measurement to find out the volume and applying statistical tools like correlation and regression helped to analyze that there is correlation between these three variables. The primary data was collected in the sample plot of 20*20 in the region of Sirsi, Karnataka. It is analyzed that the height and girth have the significant impact on the volume of the trees and hence influence the productivity of the forest.
Keywords:
Productivity, Volume, Multiple linear regression, Biodiversity, Management, Tree species
Cite Article:
"Analysis of Forest Volume Based on Height and Girth of Trees", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 7, page no.d831-d836, July-2023, Available :http://www.ijnrd.org/papers/IJNRD2307396.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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