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This study evaluated the Spatial pattern of Land Surface Temperature (LST) over Umuahia North (Urban Area) and Bende LGA (Rural Area), Abia State, Southeast Nigeria. LANDSAT Imagery spanning Row 056 and Path 188, with 30m spatial resolution was captured on the 17th of May, 2018. Temperature and relative humidity were measured using a thermometer and multi-purpose Hydro-20 - 100 % model. Eight measurements were taken for each parameter at an interval of 8 hours at an elevation of 1.5m above the ground. Coordinates and elevation of the points were captured using a Garmin Handheld GPS. Data obtained were imported in compatible formats with ArcGIS 10.5 and the values for the un-sampled locations within the study area was determined through the interpolation of the collected data. A subset covering the study area was extracted for bands 1,2,3,4 and 5. Bands 1, 2 and 3 which are visible bands were used in generating a true colour composite image of the study area; the bands 4 and 5 which are not visible bands were used for the NDVI (Normalized Differential Vegetation Index). Result showed that Bende LGA had a vegetal cover of 45,741.26hectares out of a total of 60,152.76 hectares while Umuahia North had 19,689.09 hectares of vegetal cover out of a total of 24,459.75 hectares. Umuahia North had an average daily temperature of 31.309̊ C while Bende had 27.405̊ C. The average relative humidity in Bende LGA was 82.37% while Umuahia North was 67.274%. In conclusion, the study showed the existence of heat islands in the urban areas in Umuahia North LGA which was characterized by higher temperature but lower relative humidity. The heat island could be attributed to the gradual loss of vegetation cover and the increase in built-up environments in Umuahia North LGA.

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It is a priority issue in technical and vocational education and training (TVET) to improve school engagement in order to promote teaching and learning in TVET institutions. This study appears to be the foremost to examine the dataset of a psychological intervention program for preservice TVET teachers' school engagement in a Nigerian public university. Using a school engagement measure, quantitative data was collected from 35 pre-service TVET teachers in a treatment group and 35 pre-service TVET teachers in a control group. To conduct the statistical analysis of the data from pre to posttest gathering, IBM SPSS version 22 was used. The study dataset showed that pre-service TVET teachers in the treatment condition demonstrated a significant increase in school engagement score at posttest compared to pre-service TVET teachers in the control condition. The technique used in this study to obtain the presented dataset may be very beneficial for understanding Nigeria's pre-service TVET teacher population when it comes to increasing their school engagement.

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