Purpose-Deforestation is one of the Global Forests issues that concern the United Nations (UN) for several decades and it thus leads to a vision of increasing the forestland area by 2030 that is the same size as South Africa. With this concern, spatiotemporal data analysis had been an effective way to visualize and represent the area that have been damaged and affected with the integration of the use of Geographical Information System. The National Greening Program (NGP) of the Philippines is in charge of the rehabilitation of unproductive, denuded and degraded forestlands in every province. Method-Using the spatiotemporal data in the form of shapefiles, predictors that could contribute on how the forestland may be rehabilitated were analysed and foreseen. Also, 230 with the analysis stage of Artificial Neural Network (ANN) with Back Propagation, a forecasting model was identified. Result-It has been determined that with the combination of ANN and Spatiotemporal visualization, possible additional increase in the size of the rehabilitated forestland and its representation can be done efficiently. Conclusion-Thus, the finding may be used as a helpful way for the NGP for forestland rehabilitation and reforestation strategic planning and resource management. Practical Implications-A dynamic and interactive web application may be implemented to monitor implementation of the program. Furthermore, public awareness may be initiated about the importance of forestland.
This study focused on the development of a decision-support system to forecast the inventory needs of the City Schools Division of Mabalacat. Each Property Custodian, called District Property Custodian for primary and Secondary School Supply Officer for secondary, is responsible for determining the needs and excess items of schools within their jurisdiction. Their tasks involve itemization of each school's physical properties to be able to forward proper requests for additional needs to division office. Such task requires time to be finished as the bulk of data needed to be processed and analyzed are increasing annually. Hence, delays had been experienced from requests to the delivery of the requested items. The Property Custodians should be able to plan the demand or identify the number of needed equipment and items of each school within their jurisdictions before the request will be delivered. The said manual procedures in the inventory had been automated in the new system. In order to forecast the necessary number of items for each school in the division office, the researchers applied Moving Average and Exponential Smoothing. The data resulted in the said forecast had been used to request items with neither minimal excess nor insufficiency that results in wastage.
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