Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Research findings on algorithms are discussed in a new report. According to news reporting out of the Universitas Padjadjaran by NewsRx editors, research stated, "AbstractLandscape change is intricately linked to natural resource utilization. Landscape dynamics are closely tied to land us e and land cover (LULC), serving as a representation of ecosystems and human act ivities." Our news editors obtained a quote from the research from Universitas Padjadjaran : "In the Citarum River Basin, Indonesia, a comprehensive approach is necessary to comprehend landscape dynamics as a manifestation of human interaction with th e environment. This research aims to analyze landscape dynamics and its factors that can significantly drive changes. We focused on the Cirasea Watershed, which serves as an upper region of the Citarum River Basin. Data was acquired from La ndsat-series imageries from 1993 to 2023, and LULC analyses were conducted using classification and regression trees (CART), random forest (RF), and support vec tor machine (SVM). We analyzed seven independent variables, including slope (X1) , elevation (X2), main river (X3), population (X4), central business district (X 5), distance from the past settlements (X6), and accessibility (X7) using multiv ariate analysis. This research found that RF stands out as the optimal choice fo r LULC analysis over CART and SVM because it had the highest overall accuracy an d overall kappa (0.91-0.92, 0.88-0.89). Notably, there was a substantial 273.43% increase in built-up areas, coupled with significant declines in plantations and horticultures. LULC changes was more pronounced in the lower areas near Bandung City."
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