TITLE:
Spatial Distribution of Soil Moisture Content and Tree Volume Estimation in International Institute of Tropical Agriculture Forest, Ibadan, Nigeria
AUTHORS:
Abiodun Akintunde Alo, Chukwuka Friday Agbor, Alice Jebiwott, Olubodun Temiloluwa
KEYWORDS:
Forest Soil Moisture, Temperature Dryness Vegetation Index, Spatial Data, Vegetation Indices
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.10 No.8,
August
31,
2022
ABSTRACT: The role of soil moisture in the survival and
growth of trees cannot be over-emphasized and it contributes to the net
productivity of the forest. However, information on the spatial
distribution of the soil moisture content regarding the tree volume in forest
ecosystems especially in Nigeria is limited. Therefore, this study combined
spatial and ground data to determine soil moisture distribution and tree volume
in the International Institute of Tropical Agriculture (IITA) forest, Ibadan. Satellite images of 1989, 1999, 2009 and
2019 were obtained and processed using topographic and vegetation-based
models to examine the soil moisture status of the forest.Satellite-based soil moisture obtained was validated with
ground soil moisture data collected in 2019. Tree
growth variables were obtained for tree volume computation using Newton’s
formular. Forest soil moisture models employed in this study include Topographic Wetness Index (TWI), Temperature Dryness
Vegetation Index (TDVI) and Modified Normalized Difference Wetness Index
(MNDWI). Relationships between index-based and ground base Soil Moisture
Content (SMC), as well as the correlation
between soil moisture and tree volume, were examined. The study revealed strong
relationships between tree volume and TDVI, SMC, TWI with R2 values of 0.91, 0.85, and 0.75, respectively. The regression values of 0.89
between in-situ soil data and TWI and 0.83 with TDVI ascertain the reliability
of satellite data in soil moisture mapping. The decision of which index to
apply between TWI and TDVI, therefore, depends on available data since both
proved to be reliable. The TWI surface is considered to be a more suitable soil
moisture prediction index, while MNDWI exhibited a weak relationship (R2 = 0.03) with ground data. The strong relationships between soil moisture and tree volume suggest tree volume can
be predicted based on available soil
moisture content. Any slight undesirable change in soil moisture could
lead to severe forest conditions.