With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, geographic information system (GIS)-based multi-criteria evaluation (MCE) methods have emerged as the most widely utilized approach to identifying potential aquaculture sites. Following the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA), this paper presents a systematic review and meta-analysis of GIS-based MCE methods used in aquaculture sites selection. The objective of this study is to offer a comprehensive overview of existing research in this field and develop a general model for selecting sites for fish and shellfish aquaculture. The main findings indicate a growing number of studies utilizing GIS-based MCE in aquaculture site selection in recent years, with Asia being the leading continent in terms of publications in this domain. Among the journals publishing in this field, the Aquaculture journal stands out as the top publisher. Using consistent criteria across the reviewed studies, two models have been generated, each consisting of four sub-models: water quality, soil quality, infrastructure, and socioeconomic factors; and topography, environment, and physical parameters. These models can aid future researchers and assist decision-makers in identifying optimal locations for aquaculture development.

Forest fires have become a major concern in the northern parts of Morocco, particularly in the Tangier-Tetouan-Al Hoceima (TTA) region, causing significant damage to the environment and human lives. To address this pressing issue, this study proposes an approach that utilizes remote sensing (RS) and machine learning (ML) techniques to detect burned areas in the TTA region within the Google Earth Engine platform. The study focuses on burned areas resulting from forest fires in three specific locations in the TTA region that have experienced such fires in recent years, namely Tangier-Assilah in 2017, M’diq Fnideq in 2020, and Chefchaouen in 2021. In our study, we extensively explored multiple combinations of spectral indices, such as normalized burn ratio (dNBR), normalized difference vegetation index (dNDVI), soil-adjusted vegetation index (dSAVI), and burned area index (dBAI), in conjunction with Sentinel-2 (S2) satellite images. These combinations were employed within the Random Forest (RF) algorithm, allowing us to draw important conclusions. Initially, we assess the individual effectiveness of the dNBR index, which yields accuracy rates of 83%, 90%, and 82% for Tangier-Assilah, Chefchaouen, and M’diq Fnideq, respectively. Recognizing the need for improved outcomes, we expand our analysis by incorporating spectral indices and S2 bands. However, the results obtained from this expanded combination lack consistency and stability across different locations. While Tangier-Assilah and M’diq Fnideq experience accuracy improvements, reaching 95% and 88%, respectively, the inclusion of Sentinel bands has an adverse effect on Chefchaouen, resulting in a decreased accuracy of 87%. To achieve optimal accuracy, our focus shifted towards the combination of dNBR and the other spectral indices. The results were truly remarkable, with accuracy rates of 96%, 97%, and 97% achieved for Tangier-Assilah, Chefchaouen, and M’diq Fnideq, respectively. Our decision to prioritize the spectral indices was based on the feature importance method, which highlights the significance of each feature in the classification process. The practical implications of our study extend to fire management and prevention in the TTA region. The insights gained from our analysis can inform the development of effective policies and strategies to mitigate the impact of forest fires. By harnessing the potential of RS and ML techniques, along with the utilization of spectral indices, we pave the way for enhanced fire monitoring and response capabilities in the region.

Climate change poses a major challenge in terms of urban planning management for the sake of a sustainable future. It is affecting the hydrological cycle around the world, leading to extreme weather conditions. Floods rank as the most frequent and widespread disaster in the world, they adversely...

Coastal zones, as highly dynamic and complex environments, have substantial ecological and territorial implications for both government authorities and coastal managers. This research study investigates the impacts of port construction on shoreline dynamics along the coastal region of Ksar...