Brick kilns play a significant role in meeting the global demand for construction materials, but their operations have raised environmental concerns, ranging from air pollution to deforestation and soil degradation. A lack of documented inventory of their operation have created a need to map these kilns for policymakers. This review article provides a comprehensive analysis of various brick kiln mapping methods, from traditional approaches to state-of-the-art deep learning algorithms. The paper explores a wide array of mapping technologies, including aerial remote sensing, satellite imagery, machine learning, deep learning, and geographic information systems (GIS), utilized to monitor brick kiln activities and their impact on the environment. The review highlights the strengths and limitations of different techniques and discusses recent advancements in the field. Early mapping methods which relied on manual surveys and basic tools transformed into visual inspection using aerial photography and satellite imagery which introduced more efficient mapping possibilities. Remote sensing data, combined with field observations, aided in assessing the extent of brick kiln impacts. After the boost of artificial intelligence (AI), the use of machine learning and deep learning algorithms has emerged as a promising approach for accurate and automated brick kiln mapping. The review addresses comprehensive assessment of studies which have employed various deep learning architectures to detect brick kilns in different regions, showcasing their potential for scalable and automatic mapping. To enhance mapping accuracy and spatial analysis, the integration of deep learning methods with geographic information systems (GIS) has been explored. The review further addresses the environmental consequences of brick kiln emissions, such as greenhouse gases, black carbon, and particulate matter, impacting air quality and climate change. The paper also highlights the socio-economic aspect, discussing the exploitation of workers and their health risks associated with brick kiln labor. This review article is the first of its kind which aims to aid policymakers and researchers in selecting appropriate mapping techniques and promotes sustainable solutions for accurately mapping brick kilns. By critically analyzing existing methodologies and exploring the potential of emerging technologies such as remote sensing and GIS, this review contributes to the advancement of brick kiln mapping practices, benefiting the environment, labor conditions, and the brick manufacturing industry as a whole.