Neural Network for Travel Demand Forecast Using GIS and Remote Sensing
نویسندگان
چکیده
This paper describes an application of Neural Networks in the development of a travel forecast model for transportation planning. The model intends to quantify trips within the urban area through the representation of the land use-transportation system interaction. The data to express such a complex interaction is mainly obtained from Remote Sensing images that are processed in a Geographical Information System. We present, in this paper, model’s basic formulation and the results of a case study conducted in Boston metropolitan area.
منابع مشابه
Integration of remote sensing and meteorological data to predict flooding time using deep learning algorithm
Accurate flood forecasting is a vital need to reduce its risks. Due to the complicated structure of flood and river flow, it is somehow difficult to solve this problem. Artificial neural networks, such as frequent neural networks, offer good performance in time series data. In recent years, the use of Long Short Term Memory networks hase attracted much attention due to the faults of frequent ne...
متن کاملIdentification of Groundwater Potential Zones in Moalleman, Iran by Remote Sensing and Index Overlay Technique in GIS
Water plays a vital role in the development of activities in an area. The surface water resources are inadequate to fulfill the water demand. Productivity through groundwater is quite high as compared to surface water, but groundwater resources have not yet been properly exploited. Keeping this view, the present study attempts to select and delineate various groundwater potential zones for the ...
متن کاملPrediction of Soil Salinity Using Neural Network and Multivariate Regression Based on Remote Sensing Indices and Comparison: A Case Study of Qazvin plain's Salt Marsh
Introduction: The spatial and temporal distribution of salts in the soil, the great extent of the Iranian deserts, and the adverse climatic conditions prevailing over them make it difficult to accurately determine the parameters and field measurements in some cases. In the last two decades, the use of field techniques and their combination with remote sensing data has contributed significantly ...
متن کاملThe application of artificial neural network and multiple linear regression in modeling the volume of residual stand using environmental data and remote sensing
In order to manage the forests and optimal and sustainable utilization of the forest, it seems necessary to know the information on the volume of the residual stand. In this study, a systematic randomized inventory was carried out in 186 circular 10-acre plots in the educational and research forest of Darabkola, Sari, Golestan, Iran and the volume of each plot was obtained. In the next step, th...
متن کاملThe Impact of Land Use/Land Cover Changes on Groundwater Resources Using Remote Sensing & GIS (Case Study: Khan-Mirza Plain)
Hydrological status and water table fluctuations are directly related to land use and/or land cover (LULC) changes in each area. In this research, the impact of LULC changes on groundwater quantity and quality of Khan-Mirza Plain, in the northern Karun watersheds, was investigated. For this purpose, Landsat 5, 7 and 8 satellite images and ETM and OLI sensors were employed to prepare the L...
متن کامل