Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Novel Approaches in Landslide Monitoring and Data Analysis

Significant progress has been made in the last few years that has expanded the knowledge of landslide processes. It is, therefore, necessary to summarize, share and disseminate the latest knowledge and expertise. This Special Issue brings together novel research focused on landslide monitoring, modelling and data analysis

Soil-Water Conservation, Erosion, and Landslide

The predicted climate change is likely to cause extreme storm events and, subsequently, catastrophic disasters, including soil erosion, debris and landslide formation, loss of life, etc. In the decade from 1976, natural disasters affected less than a billion lives. These numbers have surged in the last decade alone. It is said that natural disasters have affected over 3 billion lives, killed on average 750,000 people, and cost more than 600 billion US dollars. Of these numbers, a greater proportion are due to sediment-related disasters, and these numbers are an indication of the amount of work still to be done in the field of soil erosion, conservation, and landslides. Scientists, engineers, and planners are all under immense pressure to develop and improve existing scientific tools to model erosion and landslides and, in the process, better conserve the soil. Therefore, the purpose of this Special Issue is to improve our knowledge on the processes and mechanics of soil erosion and landslides. In turn, these will be crucial in developing the right tools and models for soil and water conservation, disaster mitigation, and early warning systems

Remote Sensing of Natural Hazards

Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches

Geo-Information Technology and Its Applications

Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research

Forest Fire Risk Prediction

Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system.This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors.The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally

The Effect of Hydrology on Soil Erosion

This Special Issue includes manuscripts about soil erosion and degradation processes and the accelerated rates due to hydrological processes and climate change. The new research included in this issue focuses on measurements, modeling, and experiments in field or laboratory conditions developed at different scales (pedon, hillslope, and catchment). This Special Issue received investigations from different parts of the world such as Ethiopia, Morocco, China, Iran, Italy, Portugal, Greece, and Spain, among others. We are happy to see that all papers presented findings characterized as unconventional, provocative, innovative, and methodologically new. We hope that the readers of the journal Water can enjoy and learn about hydrology and soil erosion using the published material, and share the results with the scientific community, policymakers, and stakeholders to continue this amazing adventure, facing plenty of issues and challenges

Exploring the socioeconomic and environmental factors influencing smallholder macadamia production and productivity in Malawi.

Macadamia (Macadamia integrifolia Maiden & Betche) is a highly valued crop in Malawi. The crop is a vital source of food security and ecosystem services, and its high-export cash value makes it a key contributor to the country's economy. Malawi ranks seventh in global macadamia production, comprising two subsectors: smallholders and commercial estates. However, significant yield gaps have been reported between smallholder and commercial estate producers. While commercial estates achieve higher average annual tree yields (30 kg), smallholder yields remain consistently low, averaging at or below 10 kg tree-1 year-1. Improving macadamia productivity among smallholders can help reduce poverty, improve household food security, and promote economic growth in Malawi. Despite the significant contributions of smallholders in the Malawian macadamia subsector, research on the factors influencing the crop's productivity has primarily focused on commercial estate production. To address this knowledge gap, this Ph.D thesis focuses on smallholder macadamia production in Malawi. The thesis examines the socioeconomic characteristics of smallholder macadamia farmers, including demographics, cultivar preferences, and production constraints. Secondly, it evaluates the climatic factors influencing smallholder macadamia production and predicts the current and future suitable geographical areas for the crop. Lastly, it assesses the soil fertility status of smallholder macadamia farms in relation to macadamia production requirements. Results of this study reveal that the majority (62%) of macadamia smallholders are over 50 years of age and consider farming their main occupation. However, this poses significant risks to the macadamia subsector, as older farmers are risk-averse and less innovative, hindering their willingness to adopt new agricultural technologies and ability to learn. Regarding cultivar preferences, the study finds that smallholder macadamia farmers prefer high-yielding cultivars with superior nut qualities, such as large and heavy nuts, and extended flowering periods. The most preferred macadamia cultivars in descending order are Hawaiian Agricultural Experimental Station (HAES) 660, 800, 816, and 246, which are the "core" of established cultivars in Malawi. The study identifies insect pests, diseases, market availability, strong winds, and a lack of agricultural extension services as the most significant challenges affecting smallholder macadamia farmers. The study's suitability analysis reveals that the ensemble model has an excellent fit and high performance in predicting the current agro-climatically suitable areas for macadamia production (AUC = 0.90). The findings show that precipitation related variables (60.2%) are more important in determining the suitable areas for growing macadamia than temperature related variables (39.8%). The model results show that 57% (53,925 km2) of Malawi is currently suitable for macadamia cultivation, with the central region having the highest suitability (25.8%, 24,327 km2) and the southern region the lowest (10.7%, 10,257 km2). Optimal suitability (26%, 24,565 km2) is observed in the highland areas with elevations ranging from 1000–1400 metres above sea level (m.a.s.l.). Under the intermediate emission scenario (RCP 4.5) and the pessimistic scenario (RCP 8.5), the impact models predict net losses of 18% (17,015 km2) and 21.6% (20,414 km2), respectively, in the extent of suitable areas for macadamia in the 2050s. The results of the soil fertility analysis indicate suboptimal fertility among the sampled macadamia farms. The majority of the soils are strongly acidic and deficient in essential nutrients required for the healthy growth of macadamia trees. Moreover, the average cation exchange capacity (1.67 cmol (+) kg-1) and the soil organic matter content (≤ 1%) are below the minimum optimal levels required for macadamia trees. These findings indicate that soil fertility is one of the primary limiting factors to the crop's productivity, even in areas with suitable climatic conditions. Therefore, addressing the soil fertility issues is crucial to improving the land suitability of the smallholder farms for macadamia, which can lead to optimal yields. This study extends the frontiers of knowledge concerning the macadamia subsector in Malawi by providing insights into the smallholder macadamia farming systems, including demographics, cultivar preferences, and production constraints. It also provides novel empirical evidence on the climate factors that influence the suitability of rainfed macadamia cultivation and identifies current and future suitable growing areas in the country. Additionally, the study addresses the research gap on the soil fertility status of Malawian smallholder macadamia farms. Therefore, the findings of this research have practical implications for various areas such as macadamia cultivar introductions and breeding, land use planning, soil fertility management, and policy formulation for agricultural extension services, inputs, and marketing of the crop