We present two approaches that use the environmental conditions in order to exceed the classical Abbe's limit of resolution of an aperture-limited imaging system. At first we use water drops in order to improve the resolving capabilities of an imaging system using a time-multiplexing approach. The limit for the resolution improvement capabilities is equal to the size of the rain drops. The rain drops falling close to the imaged object act as a sparse and random high-resolution mask attached to it. By applying proper image processing, the center of each falling drop is located, and the parameters of the encoding grating are extracted from the captured set of images. The decoding is done digitally by applying the same mask and time averaging. In many cases urban environment includes periodic or other high-resolution objects such as fences. Actually urban environment includes many objects of this type since from an engineering point of view they are considered appealing. Those objects follow well known standards, and therefore their structure can be a priori known even without being fully capable of imaging them. We show experimentally how we use such objects in order to superresolve the contour of moving targets passing in front of them.