Landuse/Landcover (LULC) change modeling of Old Woman Creek (OWC)Watershed using Remote Sensing and GIS

This study employs Markov chain model and Cellular Automation analysis to analyze the land use/land cover change of Old Woman Creek watershed in Ohio from 1992 to 2018 and to predict same for 2022 and 2026. Supervised classification was carried out on preprocessed 1992, 2003, 2013 and 2018 Landsat images to produce four main LULC categories namely; Agriculture, Urban, Forest/wetland and Water. Different GIS layers needed as input for Markov chain were produced with the same scale and spatial resolution. Data analysis showed that road is a major driver of urbanization in OWC watershed with farthest distances from road being about 1470m. Change detection analysis was conducted between 2 different time period namely 1992-2003 and 2003- 2013 to study the rate and pattern of urban growth. Urban growth rate was found to be less than 1% of the watershed per annum in both time period. Transition probability matrix was generated to show the rate of conversion of one LULC class to another after a period. Initial simulation was validated with 2103 and 2018 LULC map with the accuracy ranging from 95% to 99% for all the LULC classes. LULC will be simulated for 2022 and 2026 and the projected area and percentage change in each of the LULC classes will be discussed with emphasis to loss and growth. This study provides a good strategy for LULC monitoring for management practices and assesses the efficacy of the modeling method