Field Observation Data Research Articles

The role of women in the blue swimming crab fisheries supply chain from gender perspective in Pamekasan

Abstract The blue swimming crab (Portunus pelagicus) fishery industry bring positive impact onwomen in coastal areas by providing livelihood opportunities through active involvement in various gender roles, both in preparation and post-capture processes as well as in the production chain. This study aimed to analyze the roles of women in the crab fishing supply chain. This study was conducted in June 2023 at Pagagan Village, Pademawu District, Pamekasan Regency. The research employed interview methods, field observation, and secondary data sources, including articles and journals. Six respondents participated in the study, representing fishermen’s wives, mini-plant owners, crab pickers, and crab suppliers. Results showed that fishermen’s wives play a significant role in marketing and selling the crab catch, as well as assisting their husbands in making and repairing fishing gear. In the case of crab suppliers, women or housewife contributed in weighing and boiling the crabs. At the mini-plant level, women play the main role as pickers in sorting and stripping process, while the mini-plant owner supervises the overall process. The study highlighted the substantial contribution of women in coastal areas to the local community, demonstrating a strong reliance on marine resources, which fluctuate with the seasons. Additionally, the income earned by coastal women significantly contributes to their families finances, thereby enhancing their household’s economic condition.

Evolutionary diversity impacts tropical forest biomass and productivity through disturbance‐mediated ecological pathways

Abstract Significant research efforts have been made to uncover links between biodiversity and biomass productivity in forest ecosystems. However, the causal link between these two ecosystem components, and the underlying mediation role of disturbance, are yet poorly understood for hyper‐diverse tropical forests, because multiple ecological mechanisms are sequentially or simultaneously in play, leading to contradictory results in observational studies. Here, we introduce a novel framework for inferring the expected effects of evolutionary diversity on biomass stocks and productivity within forest ecosystems using observational field data. This framework involves an analytical decomposition of stand biomass into three key components: the number of trees, the mean size of trees and the mean wood density. Through this approach, we can distinguish structure‐ and compositional‐based diversity effects, which likely have distinct ecological origins. We tested this framework in one of the oldest tropical forest experiments, where different levels of silvicultural disturbances were applied in the 1980s, with regular monitoring since then. Our results revealed that disturbance history mediates the effect of evolutionary diversity on forest biomass dynamics and that several Biodiversity Ecosystem Function (BEF) relationships may be hidden behind the composite biomass variable. We specifically found an overall significant negative relationship between evolutionary diversity and biomass productivity soon after disturbances (~5–8 years), mostly via mean tree size, despite a positive evolutionary diversity effect on mean wood density. This result reflects that the productivity of disturbed forests is driven by a few dominant and disturbance‐prone species with low wood density and large potential stature, and not by niche complementarity among species. However, these effects rapidly vanished with time, with non‐significant overall effect of evolutionary diversity on productivity both ~30 years after disturbance and in the undisturbed plots. Synthesis. By disentangling the effects of evolutionary diversity on the different components of forest biomass, our framework unveiled how evolutionary diversity impacts forest productivity through different ecological mechanisms, and suggests that it plays a major role, albeit mainly negative, only soon after a disturbance.

Shoaling Internal Tides Propagating From a Shallow Ridge Modulated by the Kuroshio

AbstractThis study presents remotely generated internal tides that propagate into shallow regions and are modulated by background flows using numerical simulations and field observation data. Numerical results indicate that strongly enhanced semi‐diurnal (∼M2) internal tide energy is generated over a shallow ridge, the Izu‐Ogasawara Ridge. The generated internal tides propagates toward the Kuroshio upstream and shoal toward shallow regions near Cape Shiono‐Misaki. The intensified internal tide energy flux toward the cape is explained by two mechanisms: (a) intensified internal tide generation over the ridge due to the interaction between tides and the Kuroshio and (b) wave energy convergence along the Kuroshio due to wave refractions. A 13‐year field data set obtained from the cape was used to investigate shoaling internal tides influenced by the Kuroshio. The observed results reveal a significant positive correlation between the kinetic energy of semi‐diurnal internal tides and the background flows caused by the Kuroshio, which evidently supports the intensified internal tides attributed to the interaction between background flows and tides, as proposed by recent studies. The intensity of shoaling internal tides is also largely influenced by the path of the Kuroshio and seasonal effects. The magnitude of shoaling internal tides is clearly weaken as the Kuroshio meander occurs. Shoaling internal tides modulated by the Kuroshio can provide new insights into energy transport and mixing processes in coastal oceans.

Effect of mulched drip irrigation on crop biomass and carbon fluxes in maize field

The agroecosystem, a critical component of the terrestrial carbon cycle, plays an indispensable role in maintaining the balance of carbon pools and ensuring global food security. Investigating the interplay between crop yield and carbon cycle is essential for the advancement of sustainable agricultural practices. In the quest for water-efficient agricultural solutions, mulched drip irrigation emerges as a promising technique to mitigate water scarcity in agriculture. In the arid regions of northwest China, where water is a precious resource, understanding the impact of irrigation methods on the productivity and carbon dynamics of crops like spring maize is critical. Our study aimed to evaluate the influence of two irrigation methods—mulched drip irrigation (DI) and mulched border irrigation (BI)—on the biomass accumulation and carbon fluxes of spring maize by field observation and DNDC model simulation for comparative analysis. The findings based on field and flux observation data, underscore the transformative potential of shifting from BI to DI. DI was found to significantly enhance the soil's hydrothermal environment, which is crucial for fostering optimal conditions for crop growth. This improvement is instrumental in promoting the allocation of photosynthetic products to the aboveground biomass, ultimately leading to a substantial increase in grain yield. Our results indicated that the DI treatment not only bolstered the gross primary productivity (GPP) but also elevated the ecosystem respiration (RE) compared to the BI treatment. Finally, DI can increase the net ecosystem productivity (NEP) of maize fields by 6.08 %. The Denitrification-Decomposition (DNDC) model, after calibration and validation, proved to be a reliable tool for estimating ecosystem respiration under the two irrigation systems. A thorough analysis of the simulated data revealed that DI's enhancement of the soil's hydrothermal environment also led to an increase in soil heterotrophic respiration. This insight is vital as it sheds light on the complex interactions between irrigation practices and soil microbial processes, which are integral to the carbon cycle. These findings contribute to the growing body of knowledge on sustainable agricultural practices and provide a theoretical foundation for strategies aimed at achieving carbon neutrality. By adopting data-driven approaches and leveraging advanced models, we can pave the way for a more sustainable and resilient agricultural future that harmoniously balances productivity and environmental stewardship.

Simple Python-Based Application for Transforming Apparent Resistivity Data from Schlumberger Configuration to Wenner Configuration Using the Linear Filter Method

Research has been conducted regarding the design of a simple Python-based application to transform apparent resistivity values ​​from the Schlumberger configuration into apparent resistivity values ​​from the Wenner configuration using the linear filter method. The application developed was then validated using field data measurements from two different locations, namely Nendali Village in the East Sentani district and Buper Waena in the Heram Jayapura district. At each measurement point, two Vertical Electrical Sounding (VES) measurements were performed using Schlumberger and Wenner configurations. The apparent resistivity values ​​from the Schlumberger configuration were transformed using the application created, and the results were compared with observational data from the Wenner configuration. Field data were taken for as many as six samples per logarithmic cycle, with the Schlumberger AB/2 configuration electrode spacing equal to the Wenner configuration electrode spacing. The maximum stretch lengths in Nendali and Buper villages were 26 m and 40 m, respectively. The research results show a match between the apparent resistivity values ​​of the Wenner configuration obtained from field observations and the transformation results. This suitability was demonstrated qualitatively through the similarity of the apparent resistivity curve trend between the transformed and field observation data. Quantitatively, this suitability is shown by the slope value of the comparison curve of field observation data and transformed data, which in Nendali and Buper Villages is 0.75 and 0.98, respectively. The conclusion of this study is that a simple application that has been designed and created can be used to transform apparent resistivity values ​​from the Schlumberger configuration to the Wenner configuration. A comparison between the transformed data and field observation data shows that suitability is highly dependent on the quality of the field data.

Seasonal microplastic ingestion by carnivorous chaetognaths in Jiaozhou Bay, China: Field evidence revealing microplastic trophic transfer

Microplastics (MPs) are widely distributed in marine environments and ingested by marine organisms, especially zooplankton. Chaetognaths, typical carnivorous zooplankton, are pivotal in the food chain from secondary producers, such as copepods, to higher trophic level species. However, little is known about their MP ingestion. In this study, based on field observation data, for the first time, we studied seasonal characteristics and risks of MPs ingested by chaetognaths in Jiaozhou Bay and assessed effects of key prey copepods on MP ingestion by chaetognaths. MP/chaetognath values in February, May, August, and November were 0.19, 0.17, 0.15, and 0.39, respectively, showing no significant seasonal variation. Chaetognaths predominantly ingested MPs that were fiberous in shape, 101–400 µm in size and polyester in polymer type, with no significant seasonal variations. The risk of MP load in chaetognaths was low, but there are higher polymeric hazards and potential ecological risks. MP/chaetognath values were positively correlated with the copepod abundance and MP/copepod values. The characteristics of MPs ingested by chaetognaths were also highly similar to those of MPs ingested by copepods. However, the overall risk of biomagnification in the copepod-chaetognath food chain was low. This study provided field evidence for MP transfer in the planktonic food chain.

Prediction of thermal regime and frost heave deformations of subgrade soils during non-stationary heat and moisture transfer

In order to ensure the safe operation of high-speed trains in cold regions, frost heave is one of the basic problems in the research for prediction and control roadbed deformation in such regions. In this paper, based on the classical hydrodynamic model we developed a method of studying thermal regime of soils and predicting frost heave deformations of subgrade soils. Our coupling model takes into account the mutual influence of temperature and soil moisture during non-stationary processes of heat and moisture transfer, calculation of frost heave deformation based on calculated result of the temperature and moisture fields of the roadbed. We have also observed the change of the soil temperatures and frost heave deformation in a freezing-thawing cycle at the geodesic center of PGUPS. The field observation results show that the soil temperature variations amplitude decreases with depth. The simulation verification results and the field observation data show good reproducibility, thus the reliability of the model is confirmed. At last, the paper presents the application of the method in improving high speed railway lines (HSRL) subgrade design in order to reduce frost heave deformations. Based on the results of calculations, it is recommended to lay a thermal insulation layer at the depth of 0.2 m below the subgrade and on the slopes to reduce frost depth and frost heave deformations of subgrade soils.

Missed or misused opportunity? Social cohesion, national dialogue and peacebuilding in Cameroon

ABSTRACT This paper uses the multidimensional aspects of social cohesion which comprises different elements of trust, equality, inclusion, and participation, to show how political actors can impede efforts to foster social cohesion in conflict affected societies. It identifies key opportunities that were either missed or misused by elites during the national dialogue process intended to resolve Cameroon's Anglophone crisis. Historically, the relationship between elites and the Anglophone population in Cameroon has been characterised by fragile social cohesion due to marginalisation experienced in Anglophone communities. The actions and power-preserving efforts of elites have exacerbated inequalities, political exclusion and mistrust, thereby affecting social cohesion. Based on field observation, semi-structured interviews and secondary data, this paper identifies and analyses five scenarios where Anglophone elites could have acted differently to enhance social cohesion, but failed to do so. Rather, their actions towards the population further weakened social cohesion and facilitated the instrumentalisation of the 2019 national dialogue in Cameroon. Considering the unique characteristics of this case, future dialogue processes, especially those addressing marginalisation concerns, should prioritize strengthening social cohesion and refrain from overlooking its relevance by merely treating it as a desired outcome of a dialogue process.

Calibration of Polarization Data for Vector Magnetographs at the Huairou Solar Observing Station over the Past Four Decades

The Huairou Solar Observing Station (HSOS) has conducted solar vector magnetic field observations for 40 years and developed multiple vector magnetographs (including one space magnetic field observation instrument). Using these accumulated magnetic field observation data, HSOS has achieved significant progress in solar physics research, including important advancements in the helicity sign rule of solar active regions, the helicity characteristics of strong and weak magnetic fields in active regions, the chromospheric magnetic field characteristics of the Sun, the evolution of magnetic fields in active regions, and the extraction of magnetic field characteristics for flare precursors. However, due to historical reasons, the calibration of vector magnetic field data in HSOS are not standardized. Therefore, this paper summarizes past historical experiences and introduces the standardized calibration procedure for vector magnetic field processing in detail. These calibration procedures are the basic steps of the calibration process for the space vector magnetograph (Full-Disk Vector MagnetoGraph, abbreviated as FMG) observation data, and are also applicable to the calibration of other instrument observation data at HSOS. They mainly include basic processing of polarization data and in-depth processing of vector magnetic fields. We believe that such calibration processing of the historical data collected by HSOS over the past 40 years will help us to accurately measure and analyze the solar magnetic field, further revealing the laws of solar activity and its impact on the Earth’s environment.

Environmental Monitoring of Changes in the Flooded Areas of the Marshes and Their Relationship to Water Quality Using GIS Techniques

This study aims to examine the relationship between the flooded areas of the marshes in southern Iraq and their water quality, as well as their relationship with climatic factors such as temperatures and rainfall amounts and their impact on the water discharge into the marshes of southern Iraq in the provinces (Basra, Maysan, and Dhi Qar) through the interpretation of maps with remote sensing tools of the wet cover (water and vegetation), descriptive and quantitative analysis of the flooded areas comparing them with the values of salt concentrations and clarifying the monitoring sites of the water quality and water discharge into the marshes through GIS, as well as the relationship of the wet cover with temperatures, rainfall amounts, and evaporation. The data of this study were obtained from environmental field observation data at climate monitoring stations, incoming water discharge stations, and water quality measurement sites in the three southern governorates. As for the areas of vegetation, the data was obtained through the interpretation of the satellites’ visuals (Sentinel-2 satellite) with a resolution of 15 m using GIS programs through a temporal and spatial comparison of the marshland for April -June-October for ten years (2010-2015-2020) respectively, The results showed that there is a direct relationship between the water quality and the wet cover (vegetation and water) through classification as well as the effect of climatic elements in the marshes.

Evolution of Secondary Periglacial Environment Induced by Thawing Permafrost near China–Russia Crude Oil Pipeline Based on Airborne LiDAR, Geophysics, and Field Observation

The China–Russia crude oil pipeline (CRCOP) operates at a temperature that continuously thaws the surrounding permafrost, leading to secondary periglacial phenomena along the route. However, the evolution and formation mechanisms of these phenomena are still largely unknown. We used multi-temporal airborne light detection and ranging (LiDAR), geophysical, and field observation data to quantify the scale of ponding and icing, capture their dynamic development process, and reveal their development mechanisms. The results show that the average depth of ponding within 5 m on both sides of the pipeline was about 31 cm. The volumes of three icings (A–C) above the pipeline were 133 m3, 440 m3, and 186 m3, respectively. Icing development can be divided into six stages: pipe trench settlement, water accumulation in the pipe trench, ponding pressure caused by water surface freezing, the formation of ice cracks, water overflow, and icing. This study revealed the advantages of airborne LiDAR in monitoring the evolution of periglacial phenomena and provided a new insight on the development mechanisms of the phenomena by combining LiDAR with geophysics and field observation. The results of our study are of great significance for developing disaster countermeasures and ensuring the safe operation of buried pipelines.

Spatial Distribution of Cropping Systems in South Asia Using Time-Series Satellite Data Enriched with Ground Data

A cropping system practice is the sequential cultivation of crops in different crop seasons of a year. Cropping system practices determine the land productivity and sustainability of agriculture in regions and, therefore, information on cropping systems of different regions in the form of maps and statistics form critical inputs in crop planning for optimal use of resources. Although satellite-based crop mapping is widely practiced, deriving cropping systems maps using satellites is less reported. Here, we developed moderate-resolution maps of the major cropping systems of South Asia for the year 2014–2015 using multi-temporal satellite data together with a spectral matching technique (SMT) developed with an extensive set of field observation data supplemented with expert-identified crops in high-resolution satellite images. We identified and mapped 27 major cropping systems of South Asia at 250 m spatial resolution. The rice-wheat cropping system is the dominant system, followed by millet-wheat and soybean-wheat. The map showing the cropping system practices of regions opens up many use cases related to the agriculture performance of the regions. Comparison of such maps of different time periods offers insights on sensitive regions and analysis of such maps in conjunction with resources maps such as climate, soil, etc., enables optimization of resources vis-à-vis enhancing land productivity. Thus, the current study offers new opportunities to revisit the cropping system practices and redesign the same to meet the challenges of food security and climate resilient agriculture.

Spatial Pattern of Forest Age in China Estimated by the Fusion of Multiscale Information

Forest age is one of most important biological factors that determines the magnitude of vegetation carbon sequestration. A spatially explicit forest age dataset is crucial for forest carbon dynamics modeling at the regional scale. However, owing to the high spatial heterogeneity in forest age, accurate high-resolution forest age data are still lacking, which causes uncertainty in carbon sink potential prediction. In this study, we obtained a 1 km resolution forest map based on the fusion of multiscale age information, i.e., the ninth (2014–2018) forest inventory statistics of China, with high accuracy at the province scale, and a field-observed dataset covering 6779 sites, with high accuracy at the site scale. Specifically, we first constructed a random forest (RF) model based on field-observed data. Utilizing this model, we then generated a spatially explicit forest age map with a 1 km resolution (random forest age map, RF map) using remotely sensed data such as tree height, elevation, meteorology, and forest distribution. This was then used as the basis for downscaling the provincial-scale forest inventory statistics of the forest ages and retrieving constrained maps of forest age (forest inventory constrained age maps, FIC map), which exhibit high statistical accuracy at both the province scale and site scale. The main results included the following: (1) RF can be used to estimate the site-scale forest age accurately (R2 = 0.89) and has the potential to predict the spatial pattern of forest age. However, (2) owing to the impacts of sampling error (e.g., field-observed sites are usually located in areas exhibiting relatively favorable environmental conditions) and the spatial mismatch among different datasets, the regional-scale forest age predicted by the RF model could be overestimated by 71.6%. (3) The results of the downscaling of the inventory statistics indicate that the average age of forests in China is 35.1 years (standard deviation of 21.9 years), with high spatial heterogeneity. Specifically, forests are older in mountainous and hilly areas, such as northeast, southwest, and northwest China, than in southern China. The spatially explicit dataset of the forest age retrieved in this study encompasses synthesized multiscale forest age information and is valuable for the research community in assessing the carbon sink potential and modeling carbon dynamics.

Diagnosis of The State and Changes in The Ecosystem of Lake Onego and Watershed Based on The Information-Analytical System

The results of the diagnosis of the state and changes in the ecosystem of Onegskoe Lake (Lake Onego) and the watershed are presented using the developed information and analytical system “Lake Onego-watershed” (IAS), consisting of a comprehensive database (DB), a combined database of Roshydromet and Northern water problems institute/Karelian Research Center of the Russian Academy of Sciences on the nutrient load for the modern period 1995–2022, the ILLM mathematical model for assessing the removal of nutrients from the watershed and the formation of the nutrient load on the lake and the 3D-mathematical model SPLEM, developed for Lake Onego. Information was collected on the main sources of nutrient load in the Lake Onego catchment area, as well as available field observation data on the flow of nitrogen and phosphorus into the lake. The contribution of different nutrient sources coming from river runoff, diffuse sources, urban discharges and from trout farms was calculated for the lake and the main limnic areas. Based on data from field observations over the past 30 years and the results of numerical experiments using the SPLEM model with a grid resolution of 1 km it is shown that the ecosystem of the lake not only did not restored after the reduction in anthropogenic load after 1991, but eutrophication of waters in the lips and bays continues due to the influence of industrial and agricultural enterprises, trout farms and noticeable climate warming. Functional for the IAS “Lake Onego-catchment” to visualize the main modeling results on a 1 km grid was developed, and a web application interface has been created.

Developing a habitat suitability index with field data and hydraulic models

AbstractLinking habitat availability with hydraulic models integrates river engineering in the ecological field. Field observation for species presence and physical habitat availability mapping is inherently limited due to time and access constraints for field data collection. This study leverages hydraulic modeling to supplement larval fish population monitoring data, effectively expanding mapped physical habitat and allowing for monitoring bias analysis. The inundation extents and character of streamflow from hydraulic modeling were used to refine habitat suitability indices relative to total habitat availability from discrete fish monitoring events. Given the flexibility in hydraulic modeling to simulate a range of flows, the habitat suitability index is then translated to an effective habitat curve according to areal inundation and hydrologic frequency. With this framework, forecasting the impacts of long‐term trends, such as geomorphic or hydrologic change, can be reasonably and quantitatively assessed. This manuscript uses a case study of Rio Grande silvery minnow monitoring at restoration sites where the floodplain has been lowered via earthwork. Comparisons are made for habitat suitability indices developed from field observation data alone and field observation supplemented by hydraulic modeling. Known biases of field sampling data (targeting slow, shallow areas where fish are most often found) were confirmed based on simulated hydraulic conditions across entire restoration sites. In the case of Rio Grande silvery minnow, a heavily studied species, such field monitoring biases are an effective use of resources. However, this framework may be helpful for assessing alternative management approaches and monitoring strategies of species that are less studied.

Mapping Topsoil Behavior to Compaction at National Scale from an Analysis of Field Observations

Soil compaction is one of the most important and readily mitigated threats to soil health. Digital Soil Mapping (DSM) has emerged as an efficient method to provide broad-scale maps by combining soil information with environmental covariates. Until now, soil information input to DSM has been mainly composed of point-based quantitative measurements of soil properties and/or of soil type/horizon classes derived from laboratory analysis, point observations, or soil maps. In this study, we used field estimates of soil compaction to map soil behavior to compaction at a national scale. The results from a previous study enabled clustering of six different behaviors using the in situ field observations. Mapping potential responses to soil compaction is an effective land management tool for preventing future compaction. Random forest was used to make spatial predictions of soil behavior to compaction over cultivated soils of mainland France (about 210,000 km2). Modeling was performed at 90 m resolution. The map enabled us to spatially identify clusters of possible responses to compaction. Most clusters were consistent with known geographic distributions of some soil types and properties. This consistency was checked by comparing maps with both national and local-scale external sources of soil information. The best spatial predictors were available digital maps of soil properties (clay, silt, sand, organic carbon (SOC) content, and pH), some indicators of soil structural quality using SOC and clay content, and environmental covariates (T °C and relief-related covariates). Predicted maps were interpretable to support management recommendations to mitigate soil compactness at the soil–scape scale. Simple observational field data that are usually collected by soil surveyors, then stored and available in soil databases, provide valuable input data for digital mapping of soil behavior to compaction and assessment of inherent soil sensitivity to compaction.

Secondary production and biomass in mussel assemblages relate to species richness and stream size but not life history

AbstractIncreases in species richness with habitat area (species–area relationship, or SAR) and increases in ecosystem function with species richness (biodiversity–ecosystem functioning, or BEF) are widely studied ecological patterns. Incorporating functional trait analysis into assemblage datasets may help clarify interpretations of SAR and BEF relationships in natural ecological systems. For example, life history theory can be used to make predictions about what species are most important in generating ecosystem function given a certain set of environmental conditions. We used quantitative assemblage data for freshwater mussels at nine sites in western Alabama, USA, to test for SAR and BEF relationships. At each site, we calculated species richness, mussel assemblage density, and two fundamental metrics of ecosystem function: biomass and secondary production. We also tested whether the proportional biomass and production contributions from species belonging to each of three life history strategies—opportunistic strategists adapted to unstable or frequently disturbed habitats, periodic strategists adapted to habitats subject to predictable large‐scale disturbances, and equilibrium strategists adapted to stable habitats—varied longitudinally with stream drainage area, a proxy for habitat area. Species richness increased with stream size (SAR), and both biomass and production increased with species richness (BEF) and mussel density. There were few longitudinal changes in the proportional contributions of the different life history strategy classifications that we used, but the invasive clam Corbicula fluminea contributed proportionally more biomass and production at sites that had smaller drainage areas. This study provides further evidence for a clear longitudinal SAR in stream‐dwelling taxa. It also suggests BEF relationships for biomass and secondary production in natural assemblages but underscores the importance of assemblage density in BEF studies that use observational field data. Variation in proportional biomass and production contributions by different life history strategies was likely limited by the size of the stream size gradient in our study, as contributions were uniformly high for species with life history traits better adapted to stable and productive habitats such as mid‐sized rivers with low or predictable hydrologic disturbance frequencies. This highlights the need to understand how organisms' functional traits govern their relationships to the environment at different scales.

Seismic modeling using pseudo-impedance derived from physical models

Building accurate numerical models of the earth for simulation is both challenging and time consuming. The subsurface complexity must be captured in sufficient detail for the results to be of practical use for geophysical analysis. Physical models provide an efficient way to add realistic detail to numerical models. Physical models, for example, are scaled simulations of large-scale geologic systems that provide great insight into understanding the interplay between sedimentation, salt tectonics, and faulting. The integration of geophysical workflows with sandbox models has been the subject of previous research, primarily to create synthetic data to compare with observed field data. However, capturing the detail from the physical model is challenging. A novel workflow is presented that uses pixel intensity values from photographic images of the analogue model to create a pseudo-impedance perturbation, mimicking the acoustic impedance contrasts that are encountered in the earth. This solution enables the detailed sedimentary architecture from the sandbox to be transferred to the digital earth model. Acoustic wave equation forward modeling and reverse time migration imaging have been applied using the generated pseudo-impedance model for a Gulf of Mexico-style salt canopy model. The images produced show clear definition of the salt/sediment interface and capture the sedimentary stratigraphy and faulting observed in the original sandbox model.

Effect of Boko Haram Insurgency on Irrigation Activities Using Field and Earth Observation Data in Part of Northeastern Nigeria

The Boko HaramInsurgency in Nigeria has affected the socio-economic activities in most parts of the northeastern part of the country, leading to a low supply of food from agricultural output and increased poverty. Therefore, the main objective of this paper is to analyse the effect of the Boko Haram insurgency on irrigation activities in Kukuwa village. Data was sourced for interviews of 240 respondents and Landsat8_OLI for 2014 and Sentinel 2 for 2015 to 2019. The images were converted to NDVI and used to determine the spectral signatures for each crop using Spectral Matching Techniques (SMTs). The result indicated the majority of the farmers irrigated their farms as > 2 ha (69%) before the crisis, 2 ha (87%) during the crises and > 2 ha (62%) after the crisis, and the majority hired farmers for labour. The intensity of the irrigation was reduced during the crises and it increased after the crises. The result of the SMTs in 2014 indicated a high spectral signature for irrigation activities, with 227.07ha (29.6%) for tomatoes. In 2015 and 2016, low spectral signatures for crops were observed for 541.69ha (69.80%) and 519.5ha (66.94%), respectively. While the spectral result in 2017, 2018, and 2019 indicates a good appreciation of irrigation activities, which shows an increase in most of the dominant crops cultivated in the area, such as tomato, onion, watermelon, and pepper. Among the breakthroughs of this paper is the analysing the reflected signatures from the classified image for different crops through irrigation activities during and after the insurgency in the area. The accuracy assessment indicated fairly good with Landsat but very good with the sentinel images. The study suggests further research into the effect of boko haram insurgency on irrigation activities using field and earth observation data in part of northeastern Nigeria.

Assessment of forest cover change, key drivers of change and perception of locals in Birendranagar Municipality, Surkhet District, Nepal

Land use and land cover change has an immense impact on the global environment and ecosystem and is mostly connected with human activities such as conversion of forest into agricultural land and settlements. Forests are changing globally in quantity and quality, and in both increasing and decreasing trends. For the Birendra Nagar Municipality, this study evaluated LULC dynamics, the conversion of forest cover from 2000 to 2020, as well as community perceptions on forest cover change, its drivers. Landsat images of 2000 and 2020 were used for LULC dynamics and for forest cover change detection Using software GIS 10.8. Questionnaire survey, key informant survey, field observation and secondary data were acquired from journal articles, reports, District Forest office, books, and various other sources to find out drivers of forest cover change and perception of locals. It was found that 1146 ha of forest area, 280.53 ha of water bodies, 752.62 ha of barren land were lost between 2000 and 2020. However, 1147.74 ha of settlement area and 1032.40 ha of agricultural land was gained.Net forest cover decreased overall by 4.67%, however, some areas within the municipality experienced an increase in forest cover namely Ward 11 and ward 16 of Municipality shows Highest positive and Negative Forest cover change in terms of Area. Expansion of agriculture land and settlements with the encroachment of forest area, haphazard infrastructure development, illegal timber harvesting and low regeneration capacity of land responsible for the reduction of forest, along with Community forestry approach, plantations programs, promotion of agroforestry practices, fuel transition were responsible drivers for improvements of forest cover. Water cycle disruption, Increases Natural hazard, Temperature rises, shortage of wood for fuel, extinction of indigenous species were the most perceived negative impacts of the forest cover reduction whereas income generation Activities, support biodiversity, easy to collect fuel wool and fodder and others including purifying air quality, increasing aesthetic beauty were the most perceived positive impacts of the forest cover improvement in the study area. Most of the locals have a holistic understanding of forest cover change. Strengthening forest protection, improving soil and water conservation structures, awareness creation, enrichment planting, Promote Alternate Energy Resources and Equitable benefit-sharing mechanism are possible solutions perceived by locals.