Mapping Of Weeds in Cassava Fields Using Geographic Information Systems (GIS) 1n Derived Savanna of Nigeria (Published)
The investigation of weed spectrum in cassava fields was carried out in Derived savanna agro-ecology (Ido Local Government Area) of southern Nigeria in 2017. Thirteen (13) cassava farms were surveyed. Coordinate points, elevation of the investigation sites and mapping were conducted with Geographic information system (GIS). Weed flora composition of each location was studied by sampling randomly using ’M’ pattern of quadrat placement and average from the samples was recorded. Results showed that thirty-six (36) weed species cutting across twenty-one (21) families were identified. This showed the richness and dominance of weed flora identified in the agro-ecology. Tridax procumbens, Talinum fruticosum, Euphorbia heterophylla, Chromolaena odorata and Ageratum conyzoides were the most frequent weed species and evidently showed their broader environmental tolerance. Weediness in cassava fields ranged from 4.67/10 to 8.33/10 across locations. Cultural practices and location might have influenced the weediness and weed flora composition.
Change Detection in Landuse / Landcover Mapping in Asaba, Niger Delta B/W 1996 And 2015. A Remote Sensing and GIS Approach (Published)
Remote sensing is used in this research work for the development and acquisition of Landuse/land cover data, pattern and its attendant effects in Asaba, Delta State Nigeria. Remote sensing images and digital data verified by ground trothing (field work) satellite data are used to assess the rate of change in Landuse / Land cover between 1996 and 2015. It also examines the extent to which images and GIS softwares effectively contribute to mapping landuse/cover in the Niger Delta region. Remote sensing and geographic Information System (GIS) help integrate natural, cultural, social and economic information to create spatial information system on the available terrain resources. Sets of NARSDA images were acquired corresponding with the years, field checked to ascertain the data captured on the terrain.. The digital satellite data are incorporated as input data into IDRISI 32 GIS environmental to separately map out the landuse/land cover units and their magnitude determine. Five distinct units were identified in classification of landuse/landed cover pattern categories as follows: Farmland, Build up land, Waste land, Forest land and Water bodies. Land consumption rate indicate a progressive spatial expansion of the city was high in 1996/2006 and higher between 2006 and 2015. Also, land absorption coefficient being a measure of consumption of new urban land by increased urban population, was high between 1996 and 2006 and between 2006 and 2015. Ground trothing was carried out to ascertain the accuracy of data and there are major changes in the landuse/land cover. It was discovered that there is rapid inbuilt-up areas evidently explained in buildings projects that resulted in decrease in forest land, agricultural land and open space. This is attributed to the anthropogenic activities of farming, bush burning, grazing, etc. However, the area occupied by water remained unchanged over the years. This study demonstrates that remotely sensed data and GIS based approach is found to be timely and cost effective than the conventional method of analysis, classification of land use pattern effective for planning and management