Article
Economics
Daniela Figueroa, J. Mauricio Galeana-Pizana, Juan Manuel Nunez, Carlos Anzaldo Gomez, J. Roberto Hernandez-Castro, Maria del Mar Sanchez-Ramirez, Andrea Garduno
Summary: This study compared two versions of the Index of Economic Pressure for Deforestation in Mexico and found that the modified index was more sensitive to actual deforestation. However, neither of the indices' expected distributions of high and very high risk categories matched with the actual deforestation that occurred.
FOREST POLICY AND ECONOMICS
(2021)
Article
Environmental Sciences
Romario O. de Santana, Rafael C. Delgado, Alexandre Schiavetti
Summary: The study used a frequency ratio model to identify areas most susceptible to forest fires in the Central Corridor of the Atlantic Forest. The model showed good performance with an average AUC of 0.81, and susceptibility classes were distributed as low, medium, and high. The northwestern region of the CAFC was found to have the greatest susceptibility to forest fires.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Multidisciplinary Sciences
Narges Kariminejad, Hamid Reza Pourghasemi, Mohsen Hosseinalizadeh
Summary: Quantitative spatial analysis using GIS and R software has been an effective tool to study natural hazards and their interactions. This study developed multi-hazard susceptibility maps using data mining techniques, GIS tools, and unmanned aerial vehicles. By applying linear regression models and seven classifiers, the study identified the most influential morphometric parameters on collapsed pipes, gully heads, and landslides. The results showed that the majority of the study region had low susceptibility to these hazards. The validation results indicated high accuracy of the applied models. The study highlighted the importance of understanding the interrelated effects of multiple hazards for sustainable environmental management and socio-economic development.
SCIENTIFIC REPORTS
(2022)
Article
Geosciences, Multidisciplinary
Jean-Claude Maki Mateso, Charles L. Bielders, Elise Monsieurs, Arthur Depicker, Benoit Smets, Theophile Tambala, Luc Bagalwa Mateso, Olivier Dewitte
Summary: In the rift flank west of Lake Kivu in DR Congo, forest cover dynamics, roads, and mining activities have significant impacts on landslide characteristics and causes. Deforestation leads to more frequent but smaller-sized shallow landslides due to the reduction in regolith cohesion. Mining activities increase the odds of landslides, and landslides associated with roads are larger than shallow landslides but smaller than recent deep-seated instabilities.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Fisheries
Khondokar H. Kabir, Mohammed Nasir Uddin, Saifur Rahman, Dietrich Darr, MD. A. N. Zaman Siddiqi Drubo
Summary: This study investigates how rural youth in Mymensingh, Bangladesh perceive their socioeconomic circumstances as an opportunity to engage in catfish farming and what factors influence their engagement. The findings show that engagement in catfish farming by rural youth is determined by not only their perceptions about opportunities available in their social context, but also by factors such as family size, annual family income, level of knowledge, attitude toward catfish farming, catfish cultivation skills, and organisation involvement.
AQUACULTURE INTERNATIONAL
(2022)
Article
Environmental Sciences
Chongzhi Chen, Zhangquan Shen, Yuhui Weng, Shixue You, Jingya Lin, Sinan Li, Ke Wang
Summary: In this study, models were developed to evaluate landslide susceptibility in forest-covered areas in Lin'an, southeastern China. Logistic regression, decision tree, and random forest techniques were used, and key predictors were identified as forest type, understory vegetation height, normalized differential vegetation index in summer, distance to road, and maximum daily rainfall. The results showed that forest cover information is essential for predicting landslides and conversion from natural forests to plantations could increase landslide risk. The study provides valuable information for understanding landslide occurrences and designing disaster mitigation.
Article
Geosciences, Multidisciplinary
Rutilio Castro-Miguel, Gabriel Legorreta-Paulin, Roberto Bonifaz-Alfonzo, Jose Fernando Aceves-Quesada, Miguel Angel Castillo-Santiago
Summary: Little research has been done on the impact of pixel neighborhood information in modeling landslide susceptibility using multiple logistic regression (MLR). This study evaluates the precision and accuracy of the MLR landslide susceptibility model by incorporating in situ and neighborhood cartographic information. The MLR-CNSA model, which combines MLR with continuous neighborhood spatial analysis, provides a better spatial prediction of landslide susceptibility.
Article
Environmental Sciences
Oscar V. Bautista-Cespedes, Louise Willemen, Augusto Castro-Nunez, Thomas A. Groen
Summary: The Amazon rainforest in Colombia covers 40% of the territory and has been shaped by internal war. Conflict variables show positive relationships with deforestation but are not among the main variables explaining it.
REGIONAL ENVIRONMENTAL CHANGE
(2021)
Article
Geosciences, Multidisciplinary
Yongcui Lan, Jinliang Wang, Wenying Hu, Eldar Kurbanov, Janine Cole, Jinming Sha, Yuanmei Jiao, Jingchun Zhou
Summary: Wildfires are an important disturbance factor in forest ecosystems and assessing their probability is crucial for prevention and control. The logistic regression model is commonly used for predicting forest wildfires. This study developed a spatial prediction model for forest wildfire susceptibility in Central Yunnan Province, China, using logistic regression. The results showed correlations between various factors and wildfire occurrence, and the model demonstrated good fit to the data.
Article
Geography
Huu Duy Nguyen, Dinh-Kha Dang, Quang-Thanh Bui, Alexandru-Ionut Petrisor
Summary: The main objective of this study was to develop a multi-hazard susceptibility mapping framework by combining flooding and landslides in the North Central region of Vietnam. Support vector machines, random forest, and AdaBoost models were used to accomplish this. The accuracy of the models' predictions was evaluated using various statistical indices, and all models performed well with AUC values over 0.95. The multi-hazard maps can be used as a point of reference for decision makers in land-use planning and infrastructure development to effectively prevent and reduce the frequency of floods and landslides.
TRANSACTIONS IN GIS
(2023)
Article
Ecology
Tolotra Ranarilalatiana, Herisolo Andrianiaina Razafindraleva, Gustaf Granath, Rasa Bukontaite Malm, Jean Claude Rakotonirina, Victor Razafindranaivo, Lala Harivelo Raveloson Ravaomanarivo, Frank Johansson, Johannes Bergsten
Summary: Madagascar, with its high endemism, is experiencing a rapid decrease in forest cover, which can have negative impacts on aquatic insect diversity. This study focuses on the aquatic Adephaga beetle fauna in the remaining protected forests of the Central Highlands of Madagascar and discovers several undescribed species. The researchers also find significant differences in species assemblages between natural forests and surrounding grasslands, highlighting the importance of the remaining forests for unique fauna at risk of extinction.
ECOLOGY AND EVOLUTION
(2022)
Article
Chemistry, Multidisciplinary
Zhu Liang, Weiping Peng, Wei Liu, Houzan Huang, Jiaming Huang, Kangming Lou, Guochao Liu, Kaihua Jiang
Summary: Shallow landslides in the Himalayan areas pose serious threats to humans and economic development. Landslide susceptibility mapping (LSM) is an effective way to minimize the risk of landslides. This study compared the performance of conventional algorithms (information value and logistic regression) and advanced algorithms (categorical boosting and conventional neural networks) in LSM in Yadong county. The CNN model exhibited the best performance, while the LR model performed the worst. The results suggest that LSM accuracy can be further improved by utilizing advanced algorithms and identifying more representative features.
APPLIED SCIENCES-BASEL
(2023)
Article
Green & Sustainable Science & Technology
Lanqian Feng, Mingming Guo, Wenlong Wang, Yulan Chen, Qianhua Shi, Wenzhao Guo, Yibao Lou, Hongliang Kang, Zhouxin Chen, Yanan Zhu
Summary: This study evaluated the vulnerability of shallow landslides in the loess tableland area and selected the best method for assessing their vulnerability. The results showed that the change in coverage and vegetation index had a nonlinear impact on the sensitivity of shallow landslides. Using the RF model to predict the sensitivity of shallow landslides provides a scientific basis for disaster prevention in the loess tableland area.
Article
Multidisciplinary Sciences
Sujay Kumar, Augusto Getirana, Renata Libonati, Christopher Hain, Sarith Mahanama, Niels Andela
Summary: This study investigates the fires in the Pantanal wetland in 2020. The research finds that the fires were caused by a combination of multi-year drought and human activities, resulting in significant ecological and hydrological impacts on the wetland.
SCIENTIFIC REPORTS
(2022)
Article
Agronomy
David Brown, Sytze de Bruin, Kaue de Sousa, Amilcar Aguilar, Mirna Barrios, Nestor Chaves, Marvin Gomez, Juan Carlos Hernandez, Lewis Machida, Brandon Madriz, Pablo Mejia, Leida Mercado, Mainor Pavon, Juan Carlos Rosas, Jonathan Steinke, Jose Gabriel Suchini, Veronica Zelaya, Jacob van Etten
Summary: This study demonstrates the applicability of a rank-based data synthesis approach in crop variety management decisions by analyzing and modeling data from 14 trials in four countries in Central America. The results provide location-specific information to support decision making in crop variety management. The study shows that this approach can integrate data from diverse sources to provide valuable insights for crop variety evaluation.
