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Modeling Drivers of Deforestation in Uganda Using Regression Analysis: Efforts Towards Zero Deforestation by 2030

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F22%3A43921434" target="_blank" >RIV/62156489:43110/22:43921434 - isvavai.cz</a>

  • Alternative codes found

    RIV/62156489:43410/22:43921434

  • Result on the web

    <a href="https://doi.org/10.11118/978-80-7509-831-3-0204" target="_blank" >https://doi.org/10.11118/978-80-7509-831-3-0204</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.11118/978-80-7509-831-3-0204" target="_blank" >10.11118/978-80-7509-831-3-0204</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Modeling Drivers of Deforestation in Uganda Using Regression Analysis: Efforts Towards Zero Deforestation by 2030

  • Original language description

    Uganda, located in the Tropical region of Africa, is blessed with natural forests that serve enormous environmental ecosystems and biodiversity. Moreover, the country is known for its tropical rain forests and various hardwood, birds, and animal species. Over the years, the Trend in the natural forest land has declined at an alarming rate; hence need to investigate the possible drivers. The loss of such biodiversity and ecosystems risks desertification and extreme climatic condition. As the world moves towards Zero Deforestation 2030, understanding the determinants of deforestation and forest degradation is paramount. Therefore, the main objective of this study is to understand the impact and relationships between net forest conversion, energy emission, agriculture, and forest production of Roundwood. We used data from FAO for the period 2004-2016. Using the ADF and KPSS test, we checked for the unit root presence in the variables. Also, the study used two different regression models; ordinary multiple linear and dynamic linear regressions. The results showed that there were unit roots in the selected regressors. To analyze the determinants of deforestation, we used net forest conversion in Uganda. There was 94 % variation in the dependent variable (Net Forest conversion). The outcome of the dynamic linear regression showed that agriculture and energy emission positively impact net forest conversion, whereas forest production of Roundwood has a negative effect. Based on our findings, this study recommended the modernization of agriculture by the government of Uganda to stop cutting down the forests on a big scale. Also, the study suggested that, as Roundwood production has a negative impact on net forest conversion, there is a need for the government to strictly legislate to ensure effective and efficient management and production of Roundwood products towards total forest conservation by 2030.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    40102 - Forestry

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Public recreation and landscape protection – with environment hand in hand…: Conference proceedings

  • ISBN

    978-80-7509-830-6

  • ISSN

    2336-6311

  • e-ISSN

    2336-632X

  • Number of pages

    6

  • Pages from-to

    204-209

  • Publisher name

    Mendelova univerzita v Brně

  • Place of publication

    Brno

  • Event location

    Křtiny

  • Event date

    May 9, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article