The dramatically increasing informal MSW dumps are endangering the urban environment. Remote sensing (RS) technologies are more efficient to monitor and manage municipal solid wastes (MSW) than traditional survey-based methods. In high spatial resolution remotely sensed images, these irregularly distributed dumps have complex compositions and strong heterogeneities, thus it is still hard to extract them automatically no matter the pixel-or object-based image analysis method is used. Therefore, based on the analysis of MSW characteristics, the present study develops a multiresolution strategy to extract MSW dumps by combining image features at both high resolution and resampled low heterogeneity images, while the high resolution images can provide detailed information and the low resolution images can suppress the strong heterogeneities of informal MSW dumps. Taking the QuickBird image covering part of Beijing as an example, this multi-resolution strategy produced a high accuracy (75%), indicating that this multi-resolution strategy is quite effective for extracting the open-air informal MSW dumps.