Abstract:
This study is based on the impact of un sustainable sand mining within Lwera wetlands along kampala masaka highwway in Mpigi and Kalungu districts in Uganada. For this research four sets of Ortho-rectified multispectral remote sensed imagery that is to say, two Landsat 5&8(30m) two Sentinel 2A (10m) images to characterize the degree of damage of the wetland as a result of un-sustainable sand mining over time. The Landsat and Sentinel images were preferred given their high repetitive coverage and free accessibility. The images were extracted from the USGS web portal (http://glovis.usgs.gov/).Images used where those captured during the dry season. From the random Forest classification algorithm, the results representing the four years under this research were later processed in ArcGIS 10.8 software
In reference to the three land cover classes, random Forest results revealed that vegetation cover represented the biggest class followed by sand fields while open water was the least class for all the four study years. Vegetation area decreased from 2070 ha (2016) to 1900 ha (2019). The area under vegetation however declined to 1800 ha in 2021.The increasing trend in areal extent was also observed for open water for example from 750 ha in 2016 to 1000 ha in 2019 and then 1050 ha in 2021. The area under sand fields increased between 2016 and 2019 (for example from about 1300 ha to 900 ha). This however increased to 1000 ha in 2021.
In addition, five locations were chosen for which the water collection process was carried out in the identified sand fields. These samples in their natural state were taken for physical parameter analysis and mainly three parameters were tested for every sampling point that’s turbidity, total dissolved solid and total suspended solids. The geographical coordinates for each sampling point were taken by use of a Global Positioning System. However, the result of this research will go to great extent in assisting in the developing sustainable development policies in term of discriminatory sand mining
In order to enforce the proposed potential management and mitigation measures for curbing unsustainable sand mining activities, a quantitative analysis method of mathematical models and numerical simulations in theoretical economics which analyses the supervision scheme of law enforcement officers to minimize costs as carried out.
Index Terms— Land Degradation, GIS, Sand Mining, ArcGIS, Random forest classification algorithm
