The invention provides an urban area detecting method based on feature position optimization and integration, prior learning is not needed, calculation is simple, and the urban area detecting method is more suitable for being implemented in practical application. The urban area detecting method includes the steps that step1, images are preprocessed, and the image processing process includes RGB color images conversion to gray level images and Gaussian pyramid generation; step2, urban position feature points are selected preliminarily; step3, the urban position feature points are screened; step4, regional integration is performed on urban areas based on Gaussian rendering weighting; step5, partition threshold values are obtained through a self-adaptive iteration method, binaryzation is performed on a weighting matrix, connected domains of binary images are marked, and the connected domains with the area smaller than the preset threshold value are rejected; step6, from the step2 to the step5 are repeated on all layers of a Gaussian pyramid generated in the step1, after results of all the layers are expanded to the size of the original images, a union set of the results is obtained to obtain an urban area candidate range, color features of the candidate range in the RGB color images, and pixel regions of which the color features do not meet the conditions are rejected to obtain a final detecting result.