Urbanization together with climate change is imposing growing stresses on the sustainable development of major coastal cities around the world, particularly in developing countries. Thus, the need for regular monitoring of coastal water quality is becoming increasingly vital, and remote sensing is deemed to be a viable approach particularly due to its cost-effectiveness. Over the past two decades, remote sensing using satellite imaging has already been adopted in various tasks related to the monitoring of coastal hydro-enviro nment, including the detection of oil spills, identification of turbid plumes, mapping of marine ecosystems, etc. Despite their usefulness, space-borne sensors are subjected to constraints such as low spatial resolution, clouds and atmospheric interference, sparse frequency, and inflexible scheduling. Recently, remote sensing with portable Unmanned Aerial Vehicles (pUAVs) is emerging as a promising alternative for high spatial-resolution monitoring of coastal hydro-environment, with the key advantages that they can minimize the effects of atmospheric disruptions and be implemented with a frequent schedule to perform on-demand monitoring. In addition, with the technological advances in the sensor's design, UAVs are now capable of capturing data with fine spectral resolutions, ranging from several (multispectral) to hundreds (hyperspectral) of spectral bands. Data analytic is also improving rapidly with the advancement in artificial intelligence (AI) and deep learning algorithms. In this paper, we present a systematic review of the recent developments in the utilization of UAV-based remote sensing for the sustainable development of the coastal hydro-environment, particularly with pUAVs. The key technical issues, including the design of UAV systems and the processing of data, are examined for specific applications. Future prospects for implementation are also discussed.