What you see is what you get: Delineating the urban jobs-housing spatial distribution at a parcel scale by using street view imagery

The compressed package (Study_code.zip) contains the code files implemented by an under review paper ("What you see is what you get: Delineating urban jobs-housing spatial distribution at a parcel scale by using street view imagery based on deep learning technique").<br>The compressed package (input_land_parcel_with_attributes.zip) is the sampled mixed "jobs-housing" attributes data of the study area with multiple probability attributes (Only working, Only living, working and living) at the land parcel scale.<br>The compressed package (input_street_view_images.zip) is the surrounding street view data near sampled land parcels (input_land_parcel_with_attributes.zip) with the pixel size of 240*160 obtained from Tencent map (https://map.qq.com/).<br><br>The compressed package (output_results.zip) contains the result vector files (Jobs-housing pattern distribution and error distribution) and file description (Readme.txt).<br>This project uses some Python open source libraries (Numpy, Pandas, Selenium, Gdal, Pytorch and sklearn). This project complies with the GPL license.<br>Numpy (https://numpy.org/) is an open source numerical calculation tool developed by Travis Oliphant. Used in this project for matrix operation. This library complies with the BSD license.<br>Pandas (https://pandas.pydata.org/) is an open source library, providing high-performance, easy-to-use data structures and data analysis tools. This library complies with the BSD license.<br>Selenium(https://www.selenium.dev/) is a suite of tools for automating web browsers.Used in this project for getting street view images.This library complies with the BSD license.<br>Gdal(https://gdal.org/) is a translator library for raster and vector geospatial data formats.Used in this project for processing geospatial data.This library complies with the BSD license.<br>Pytorch(https://pytorch.org/) is an open source machine learning framework that accelerates the path from research prototyping to production deployment.Used in this project for deep learning.This library complies with the BSD license.<br>sklearn(https://scikit-learn.org/) is an open source machine learning tool for python.Used in this project for comparing precision metrics.This library complies with the BSD license.<br>