Article
Green & Sustainable Science & Technology
Imane Mahjoubi, Lisa Bossenbroek, Elisabeth Berger, Oliver Froer
Summary: This study analyzes stakeholder perceptions of water-related ecosystem services (WESs) in the Draa Valley in Morocco. The results show that stakeholders have different perceptions of WES in terms of provisioning, regulating, and cultural services, which are influenced by their roles and activities in the region. Socio-demographic, biophysical, and spatial aspects also shape their perceptions.
Article
Environmental Sciences
Luis Miguel Silva-Novoa Sanchez, Lisa Bossenbroek, Janpeter Schilling, Elisabeth Berger
Summary: Since the UN Water Conference in 1977, global attention has been focused on addressing global water scarcity and achieving sustainable development. This article examines the case of Morocco's water policy to shed light on the challenges it faces in achieving sustainable development and implementing integrated water resource management. The study reveals that the policy has unintentionally led to sustainability and social-inequality issues, which can be attributed to the disciplinary approach used in policy formulation, compartmentalization of government sectors, and the neglect of social, economic, and political factors affecting water access.
Article
Environmental Sciences
Yu Ren, Xiangjun Liu, Bo Zhang, Xidong Chen
Summary: Desertification is a serious environmental problem globally, and it has extensively affected China with an area of about 1.72 million km(2) being desertified. This study assessed the sensitivity of land desertification in China using the MEDALUS model, which integrated natural and human factors. The principal driving forces of desertification in China were found to be erosion protection, drought resistance, and land use.
Article
Environmental Sciences
Maria Teresa Melis, Luca Pisani, Jo De Waele
Summary: This study focuses on the morphometric analysis of numerous collapse dolines on the Quaternary basaltic plateau of Azrou, in the Middle Atlas of Morocco, utilizing remote sensing techniques. By using tri-stereo Pleiades satellite images, accurate morphometric datasets were automatically generated, showcasing the potential of such images for rugged terrains and steep depressions.
Article
Environmental Sciences
Omar Skakni, Rachid Hlila, Amin Beiranvand Pour, Manuel Martin Martin, Ali Maate, Soufian Maate, Aidy M. Muslim, Mohammad Shawkat Hossain
Summary: This study uses an integrated approach of GIS and remote sensing techniques for structural mapping in an inaccessible zone of the North-Western Rif belt in Morocco. The study demonstrates that the integration of remote sensing imagery and GIS techniques is a reliable and low-cost method for fracture extraction and structural mapping in remote and inaccessible regions.
GEOCARTO INTERNATIONAL
(2022)
Article
Geosciences, Multidisciplinary
Jihad Bouaida, Omar Witam, Mounsif Ibnoussina, Abd El Fettah Delmaki, Myriam Benkirane
Summary: This paper focuses on the mapping and modelling of flood increase process in the Zat watershed. It identifies factors causing floods and analyzes rainfall data to illustrate precipitation trends. The study shows that the geomorphological and rainfall context of the basin makes it vulnerable to torrential floods, with a trend towards drought along with extreme events like floods.
Article
Engineering, Marine
Denis Krivoguz, Liudmila Bondarenko, Evgenia Matveeva, Anton Zhilenkov, Sergei Chernyi, Elena Zinchenko
Summary: The study aimed to develop a machine learning algorithm for detecting water overgrowth with Phragmites australis using Sentinel-2 data. The results showed that the area covered by reeds increased from 0.37 km(2) in 2020 to 0.51 km(2) in 2021. The rapid growth of Phragmites australis was primarily attributed to eutrophication and changes in water flows.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Nilufar Karimli, Mahmut Oguz Selbesoglu
Summary: This study investigated the limitations and capabilities of remote sensing data application in the field of planning Food Security, and used Sentinel 2 and Shuttle Radar Topography Mission (SRTM) data to estimate winter wheat yields with a high degree of accuracy (98.03%). This method makes it possible to predict the productivity of newly created crop fields without the need for regression models or field studies.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2023)
Article
Engineering, Marine
Raisa Borovskaya, Denis Krivoguz, Sergei Chernyi, Efim Kozhurin, Victoria Khorosheltseva, Elena Zinchenko
Summary: This study used machine learning techniques to evaluate the salinity level in a hypersaline lake and built eight salinity evaluation models. It was found that with an increase in salinity, the wavelength of absorbing light shifts from the ultraviolet part to the infrared part, which enables continuous monitoring of hypersaline water bodies using remote sensing data.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Ge Liu, Sijia Li, Kaishan Song, Xiang Wang, Zhidan Wen, Tiit Kutser, Pierre-Andrew Jacinthe, Yingxin Shang, Lili Lyu, Chong Fang, Ying Yang, Qian Yang, Baohua Zhang, Shuai Cheng, Junbin Hou
Summary: As important components of dissolved organic matter (DOM) in an aquatic environment, colored DOM (CDOM) and dissolved organic carbon (DOC) play an essential role in the carbon cycle of inland aquatic systems. This study used optical satellite remote sensing to examine the relationships between CDOM and DOC in lakes on the Qinghai-Tibet Plateau and showed strong correlations between CDOM absorption coefficient at 350 nm and Sentinel-2A Multi Spectral Instrument (MSI) imagery reflectance data. The study also revealed significant differences in CDOM and DOC concentrations between fresh and saline waters in the Tibetan Plateau, emphasizing the importance of combining salinity and remote sensing data for estimating lake DOC.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Environmental Sciences
Ting Wang, Wei Zhou, Jieyun Xiao, Haoran Li, Li Yao, Lijuan Xie, Keming Wang
Summary: Climate change is connected to changes in soil organic carbon (SOC) content, making accurate prediction of SOC content crucial for carbon accounting and sustainable soil management. This study used soil samples, environmental covariates, and optical remote sensing variables to build SOC content prediction models. Three machine learning models were applied across different land use classes in karst areas, and the results showed that RF and XGBoost outperformed SVM in prediction accuracy. The models based on individual land use types achieved higher simulation accuracy than the model based on the entire study area. These findings provide new insights for estimating SOC content with high precision in karst areas.
Article
Environmental Sciences
Adil Moumane, Jamal Al Karkouri, Adnane Benmansour, Fatima Ezzahra El Ghazali, Jamie Fico, Ahmed Karmaoui, Mouhcine Batchi
Summary: Using Landsat time-series data, this study examines the land use and cover changes in the Ternata oasis over the past thirty years. The results show a significant expansion of desertified lands and a decrease in cultivated lands. The analysis also reveals a strong correlation between land use changes in the oasis and the stored water in the upstream reservoir. To mitigate the effects of desertification and conserve the natural resources in the Ternata oasis, local efforts are being implemented.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)
Article
Environmental Studies
Shuhang Li, Mohamed Abdelkareem, Nassir Al-Arifi
Summary: Groundwater is an important resource that meets daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. Remote sensing data can predict potential water resources. A study was conducted in China's Yellow River region, using a GIS-based frequency ratio machine learning technique to generate and integrate nine layers of evidence influenced by remote sensing data. The study identified different groundwater prospective zones and validated the maps using well data. Combining different data sets through GIS can reveal promising areas of water resources. Rating: 8/10
Article
Remote Sensing
Igor Klein, Soner Uereyen, Christina Eisfelder, Vladimir Pankov, Natascha Oppelt, Claudia Kuenzer
Summary: Negative impacts of locust species on agriculture have always been a major threat to food security and livelihoods, especially for local communities. Locust management and control have reduced the frequency and intensity of plagues and outbreaks. However, political insecurity, armed conflicts, changing climate, and land use management can contribute to new outbreaks. Geospatial and remote sensing data are important for locust research and management, but their practical usage is still limited.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Guo Yu, Yafeng Zhong, Sihai Liu, Qibin Lao, Chunqing Chen, Dongyang Fu, Fajin Chen
Summary: This study developed an algorithm for retrieving coastal particulate organic carbon (POC) sources using remote sensing and geochemical isotope technology. The algorithm showed good performance in calculating the proportion of POC sources and revealed the spatiotemporal variations in POC sources and their underlying causes.
Article
Computer Science, Artificial Intelligence
Rabin Chakrabortty, Subodh Chandra Pal, Manoranjan Ghosh, Alireza Arabameri, Asish Saha, Paramita Roy, Biswajeet Pradhan, Ayan Mondal, Phuong Thao Thi Ngo, Indrajit Chowdhuri, Ali P. Yunus, Mehebub Sahana, Sadhan Malik, Biswajit Das
Summary: This study investigates the impact of the COVID-19 lockdown on air quality in India and the relationship between climate variables and the spread of the virus. The results show that the lockdown has improved air quality across the country, but there is no clear connection between climate parameters and the outbreak and mortality of the virus.
Article
Biology
Hendrik Klein, Gerard D. Gierlinski, Mostafa Oukassou, Hafid Saber, Jens N. Lallensack, Abdelouahed Lagnaoui, Abdelkbir Hminna, Andre Charriere
Summary: Tridactyl theropod and ornithischian dinosaur tracks have been discovered in the Imilchil and Isli formations in the central High Atlas region of Morocco. These tracks are similar to those found in Lower-Middle Jurassic deposits in China. The presence of these tracks, along with other dinosaur tracks and plants, suggests the existence of a flourishing ecosystem and dinosaur habitat during the Middle Jurassic. Remarkably, the presence of Changpeipus theropod tracks suggests an exchange of dinosaur faunas between East Asia and northern Africa during this time.
HISTORICAL BIOLOGY
(2023)
Article
Biology
Tariq Zouheir, Abdelkbir Hminna, Hafid Saber, Hendrik Klein, Abdelouahed Lagnaoui, Sebastian Voigt, Aziz Rmich, Joerg W. Schneider, Spencer G. Lucas
Summary: This study focuses on the Middle-Late Triassic continental deposits in the Argana Basin, Morocco. It identifies 17 lithofacies, including alluvial fan, fluvial, floodplain, and lacustrine associations. Invertebrate traces and rhizoliths were also observed. Six ichnoassemblages were distinguished, reflecting different environments and climatic shifts. The study provides insights into the geological history and climate changes of the region.
HISTORICAL BIOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Reza Ghezelbash, Abbas Maghsoudi, Mehdi Shamekhi, Biswajeet Pradhan, Mehrdad Daviran
Summary: In this study, unsupervised clustering and supervised machine learning methods were used to construct mineral prospectivity maps and genetic algorithm was incorporated to optimize model performance. The results showed that the genetic-based SVM model outperformed other models in detecting favorable areas associated with porphyry-type Cu mineralization.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Environmental Sciences
Anjar Dimara Sakti, Tania Septi Anggraini, Kalingga Titon Nur Ihsan, Prakhar Misra, Nguyen Thi Quynh Trang, Biswajeet Pradhan, I. Gede Wenten, Pradita Octoviandiningrum Hadi, Ketut Wikantika
Summary: Air pollution has significant impacts on human life, causing three million deaths annually. This study developed a multi-air pollution risk index product using remote sensing data, considering hazard, vulnerability, and exposure analyses.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Meteorology & Atmospheric Sciences
Sunil Saha, Barnali Kundu, Anik Saha, Kaustuv Mukherjee, Biswajeet Pradhan
Summary: Drought is a natural and complex climatic hazard with consequences for both natural and socio-economic contexts. This study used deep learning algorithms to assess drought vulnerability and developed a drought vulnerability map (DVM) for the monsoon climate dominant region of West Bengal, India. The results show that nearly 24% of the study area is highly vulnerable to drought.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Editorial Material
Physics, Multidisciplinary
Irasema Alcantara-Ayala, Eric Josef Ribeiro Parteli, Biswajeet Pradhan, Sabatino Cuomo, Bianca Carvalho Vieira
FRONTIERS IN PHYSICS
(2023)
Article
Geosciences, Multidisciplinary
Minu Treesa Abraham, Manjunath Vaddapally, Neelima Satyam, Biswajeet Pradhan
Summary: The number of rainfall-induced landslides and resulting casualties is increasing worldwide. A new data-driven approach for spatio-temporal landslide forecasting on a regional scale is proposed, integrating Landslide Susceptibility Maps (LSMs) using RF algorithm and probabilistic hydro-meteorological thresholds. The proposed method is compared with two deterministic process-based approaches and shows better performance.
Article
Environmental Sciences
Wahyu Luqmanul Hakim, Muhammad Fulki Fadhillah, Sungjae Park, Biswajeet Pradhan, Joong-Sun Won, Chang-Wook Lee
Summary: Global sea-level rise is a critical problem for coastal cities. Semarang, a coastal city in Indonesia, is at risk of being submerged due to flooding and land subsidence. This study used improved combined scatterers interferometry with optimized point scatterers to increase the density of measurement points. Comparison between support vector regression and convolutional neural network algorithms showed that the ICOPS-CNN method had better model performance and measurement point density. Land subsidence analysis using susceptibility mapping showed that a hybrid deep learning algorithm with grey wolf optimizer had the highest accuracy. This research can be used by local governments to improve urban development planning in Semarang.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Farzaneh Soltani, Saman Javadi, Abbas Roozbahani, Ali Reza Massah Bavani, Golmar Golmohammadi, Ronny Berndtsson, Sami Ghordoyee Milan, Rahimeh Maghsoudi
Summary: Assessing water resources status is crucial for long-term planning. This study focuses on evaluating the effects of climate change on water resources in the Shazand plain in Iran, which has experienced significant declines in streamflow and groundwater levels. The results predict a substantial decrease in river discharges and groundwater levels in this region under future climate conditions, emphasizing the need for sustainable management methods to mitigate these effects.
Article
Environmental Sciences
Michael James Horry, Subrata Chakraborty, Biswajeet Pradhan, Nagesh Shulka, Mansour Almazroui
Summary: This study introduces a novel staggered training approach that combines a high-accuracy vision transformer and a low-parameter-count convolutional neural network in an ensemble model. The ensemble model efficiently incorporates new data and allows for continuous improvement through a staggered training schedule.
EARTH SYSTEMS AND ENVIRONMENT
(2023)
Article
Geology
Tariq Zouheir, Adrian P. Hunt, Abdelkbir Hminna, Hafid Saber, Joerg W. Schneider, Spencer G. Lucas
Summary: A large collection of vertebrate coprolites from the Upper Triassic Irohalene Member in northern Argana Basin, Morocco, shows a great variety of morphotypes, suggesting the presence of diverse terrestrial and aquatic carnivorous producers. Most of the coprolites were produced by semi-aquatic and terrestrial tetrapods, with only a small percentage produced by fish. The discovery of similar coprofaunas in the Chinle Group of the western United States indicates a late Carnian age for the Irohalene Member and close Laurussian relationships for this Moroccan coprofauna from Gondwana.
Review
Environmental Sciences
Abhasha Joshi, Biswajeet Pradhan, Shilpa Gite, Subrata Chakraborty
Summary: Reliable and timely crop-yield prediction and mapping are crucial for food security and decision making. Remote sensing data and deep learning algorithms have been effective tools for crop mapping and yield prediction. This study provides a thorough systematic review of the important scientific works related to state-of-the-art deep learning techniques and remote sensing in crop mapping and yield estimation.
Article
Engineering, Multidisciplinary
Smita Khade, Shilpa Gite, Sudeep D. Thepade, Biswajeet Pradhan, Abdullah Alamri
Summary: Contactless verification using iris biometric identification is effective in preventing the spread of infections like COVID-19. The study introduces a novel iris liveness detection approach using fragmental coefficients of Haar transformed iris images as signatures, which effectively prevents spoofing attacks. Multiple feature creation methods and machine learning classifiers are evaluated, achieving a high accuracy of 99.18%.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Review
Engineering, Multidisciplinary
Sneha Basak, Himanshi Agrawal, Shreya Jena, Shilpa Gite, Mrinal Bachute, Biswajeet Pradhan, Andmazen Assiri
Summary: This paper reviews the development journey of speech recognition systems and provides a modern approach to the topic. It presents a step-by-step rundown of the fundamental stages, discusses various modern-day developments and applications, and serves as a starting point for researchers in the field.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
