/tags/land-use-and-land-cover/Land Use and Land CoverSource Themes Academic (https://sourcethemes.com/academic/)en-usWed, 13 Nov 2019 00:00:00 +0000/img/my.jpg/tags/land-use-and-land-cover//project/lulc/Wed, 13 Nov 2019 00:00:00 +0000/project/lulc/<h2 id="abstract">Abstract</h2> <p>This project aims to develop an algorithm that can accurately predict land cover changes across large regions that include both urban and rural areas. Existing land cover prediction models are typically tailored to urban characteristics, which limits their effectiveness in regions where urban and rural areas are mixed. To address this, our project seeks to create a new predictive algorithm that incorporates the unique features of both urban and rural environments. The first step involves using multi-temporal satellite imagery to create land cover maps at various time points. We then perform a time-series analysis to identify patterns of land cover change over time. Based on this data, we are developing the BPLE (Bayesian-based Probability Land cover Estimation) algorithm, which is designed to detect and predict land cover changes while accounting for the different characteristics of urban and rural regions. This algorithm applies Bayesian probability theory to capture the spatiotemporal regularities in land cover change, enabling us to forecast future changes. To validate the accuracy and utility of our model, we will compare its predictions with actual observed changes in both urban and rural areas. By providing a precise tool for predicting land cover change, this project aims to support a range of applications, including national land management, natural disaster risk assessment, and water cycle management. The resulting model will offer a versatile approach for studying and managing large, mixed urban-rural regions.</p>