Weston Mwase

Biographic Data

ID9057514
NAMEWeston Mwase
GIVEN NAMESWeston
FAMILY NAMEMwase
SIGNATUREMWASE W
AFFILIATIONSLilongwe University of Agriculture and Natural Resources
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Forest cover restoration analysis using remote sensing and machine learning in central Malawi

    Open AccessJabulani Nyengere, Precious Masuku et al.ARTICLETrees Forests and People2025

    Forests play a crucial role in maintaining ecological balance and supporting human well-being, yet they are increasingly threatened by anthropogenic pressures. Over the past two decades (2000–2020), Malawi has experienced a 21 % decline in forest cover, necessitating urgent and effective restoration strategies. Community-led forest regeneration initiatives have emerged as a viable solution to counteract this degradation. This study employs remote…

  • Determinants of household participation in natural forest regeneration

    Open AccessJabulani Nyengere, Precious Masuku et al.ARTICLETrees Forests and People2025

    Deforestation remains a prominent issue in Malawi's forest reserves and village forest areas. The Kapirimutu village forest has exhibited a significant increase in forest cover over the previous decade due to community involvement in natural forest regeneration (NFR) initiatives. This study investigates the determinants of household participation in the successful NFR initiatives in the Kapirimutu village forest, a model forest in central Malawi,…

  • Web-based spatial decision support system for optimum route to forest fires

    Open AccessHarineck Mayamiko Tholo, Wilfred Kadewa et al.ARTICLETrees Forests and People2025

    Efficient access to fire incidents is crucial for successful firefighting operations. This study aimed at developing a web-based spatial decision support system (SDSS) to determine optimal routes to forest fires and risk zones in the Viphya Plantations, Malawi. The system integrates remote sensing analysis to identify fire risk zones and a web-based SDSS to suggest optimal response routes. Remote sensing data was used to map areas prone to forest…

  • Allometric models for estimating above- and below- ground tree carbon for community managed miombo woodlands

    Open AccessMemory Malakini, Steve Makungwa et al.ARTICLETrees Forests and People2020

    In Southern Africa there are no local allometric models that can precisely and accurately estimate tree carbon stocks in community managed forests. This study developed the local allometric models for estimating tree carbon stocks in community managed forests and tested predictive performance of existing models when applied on community managed forests. While the developed allometric models are robust in tree carbon estimation, the existing allom…