Author(s)

Abiodun Akintunde Alo¹, Chukwuka Friday Agbor², Alice Jebiwott³, Olubodun Temiloluwa¹

¹Department of Social and Environmental Forestry, University of Ibadan, Ibadan, Nigeria.
²Department of Environmental Modeling and Biometrics, Forestry Research Institute of Nigeria, Ibadan, Oyo Nigeria.
³Department of Social Sciences, Catholic University of Eastern Africa, Nairobi, Kenya.

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.

Forest Soil Moisture, Temperature Dryness Vegetation Index, Spatial Data, Vegetation Indices

Alo, A. , Agbor, C. , Jebiwott, A. and Temiloluwa, O. (2022) Spatial Distribution of Soil Moisture Content and Tree Volume Estimation in International Institute of Tropical Agriculture Forest, Ibadan, Nigeria. Journal of Geoscience and Environment Protection, 10, 364-384. doi: 10.4236/gep.2022.108022.