Search results for: floodplain vegetation

Authors: Huynh Viet Khai, Mitsuyasu Yabe

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The study investigated the economic value of biodiversity attributes that could provide policy-makers reliable information to estimate welfare losses due to biodiversity reductions and analyse the trade-off between biodiversity and economics. In order to obtain the non-market benefits of biodiversity conservation, an indirect utility function and willingness to pay for biodiversity attributes were applied using the approach of choice modelling with the analysis of conditional logit model. The study found that Mekong Delta residents accepted their willingness to pay for VND 913 monthly for a one percent increase in healthy vegetation, VND 360 for an additional mammal species and VND 2,440 to avoid the welfare losses of 100 local farmers.

Keywords: choice modelling, genetic resources, wetland conservation, marginal willingness to pay

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Authors: Bo Wang

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This paper proposes a method that can estimate PM2.5 by the images of GF-1 Satellite that called WFOV images (Wide Field of View). AOD (Aerosol Optical Depth) over land surfaces was retrieved in Shanghai area based on DDV (Dark Dense Vegetation) method. PM2.5 information, gathered from ground monitoring stations hourly, was fitted with AOD using different polynomial coefficients, and then the correlation coefficient between them was calculated. The results showed that, the GF-1 WFOV images can meet the requirement of retrieving AOD, and the correlation coefficient between the retrieved AOD and PM2.5 was high. If more detailed and comprehensive data is provided, the accuracy could be improved and the parameters can be more precise in the future.

Keywords: remote sensing retrieve, PM 2.5, GF-1, aerosol optical depth

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Authors: Elaine Cristina Barboza, Antonio Jaschke Machado

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This paper discusses micrometeorological aspects of the urban climate in three cities in Western São Paulo State: Presidente Prudente, Assis, and Iepê. Particular attention is paid to the method used to estimate the components of the energy balance at the surface. Estimates of convective fluxes showed that the Bowen ratio was an indicator of the local climate and that its magnitude varied between 0.3 and 0.7. Maximum values for the Bowen ratio occurred earlier in Iepê (11:00 am) than in Presidente Prudente (4:00 pm). The results indicate that the Bowen ratio is modulated by the radiation balance at the surface and by different clusters of vegetation.

Keywords: Bowen ratio, medium-sized cities, surface energy balance, urban climate

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Authors: An-Shik Yang, Chih-Yung Wen, Chiang-Ho Cheng, Yu-Hsuan Juan

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The objective of this study is to conduct computational fluid dynamic (CFD) simulations for evaluating the cooling efficacy from vegetation implanted in a public park in the Taipei, Taiwan. To probe the impacts of park renewal by means of adding three pavilions and supplementary green areas on urban microclimates, the simulated results have revealed that the park having a higher percentage of green coverage ratio (GCR) tended to experience a better cooling effect. These findings can be used to explore the effects of different greening modifications on urban environments for achieving an effective thermal comfort in urban public spaces.

Keywords: CFD simulations, Green Coverage Ratio, Urban heat island, Urban Public Park

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Authors: Xiyue Wang, Shaoning Yan

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Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

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Authors: Talal Alharigi, Kawther Alshlash, Mariska Weijerman

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The government of Saudi Arabia has developed an ambitious “Vision 2030”, which includes a Green Initiative (i.e., the planting of 10 billion trees) and the establishment of seven Royal Reserves as protected areas that comprise 13% of the total land area. The main objective of the reserves is to restore ecosystem balance and reconnect people with nature. Two royal reserves are managed by The Imam Abdulaziz bin Mohammed Royal Reserve Development Authority, including Imam Abdulaziz bin Mohammed Royal Reserve and King Khalid Royal Reserve. The authority has developed a management plan to enhance the habitat through seed dispersal and the planting of 10 million trees, and to restock wildlife that was once abundant in these arid ecosystems (e.g., oryx, Nubian ibex, gazelles, red-necked ostrich). Expectations are that with the restoration of the native vegetation, soil condition and natural hydrologic processes will improve and lead to further enhancement of vegetation and, over time, an increase in biodiversity of flora and fauna. To evaluate the management strategies in reaching these expectations, a comprehensive monitoring and evaluation program was developed. The main objectives of this program are to (1) monitor the status and trends of indicator species, (2) improve desert ecosystem understanding, (3) assess the effects of human activities, and (4) provide science-based management recommendations. Using a random stratified survey design, a diverse suite of survey methods will be implemented, including belt and quadrant transects, camera traps, GPS tracking devices, and drones. Data will be gathered on biotic parameters (plant and animal diversity, density, and distribution) and abiotic parameters (humidity, temperature, precipitation, wind, air, soil quality, vibrations, and noise levels) to meet the goals of the monitoring program. This case study intends to provide a detailed overview of the management plan and monitoring program of two royal reserves and outlines the types of data gathered which can be made available for future research projects.

Keywords: camera traps, desert ecosystem, enhancement, GPS tracking, management evaluation, monitoring, planting, restocking, restoration

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Authors: Miriam Eduful

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The Electricity Company of Ghana (ECG) is under obligation, demanded by the Public Utility and Regulation Commission to meet set performance indices. However, in certain parts of the country, bamboo related power interruptions have become a challenge. Growth rate of the bamboo is such that the cost of regular vegetation maintenance along route of the overhead power lines has become prohibitive. To address the problem, several methods and techniques of bamboo eradication have being used. Some of these methods involved application of chemical compounds that are considered inimical and dangerous to the environment. In this paper, three methods of bamboo eradication along the route of the ECG overhead power lines have been investigated. A hybrid method has been found to be very effective and ecologically friendly. The method is locally available and comparatively inexpensive to apply.

Keywords: bamboo, eradication, hybrid method, gly gold

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Authors: Ayhan Aydoğdu, Ercan Ceyhan, Ali Kahraman, Nursel Çöl

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This research was conducted to determine effects of plant densities on seed yield and some agricultural characteristics of pea variety- Jofs in Konya ecological conditions during 2012 vegetation period. The trial was set up according to “Randomized Blocks Design” with three replications. The material “Jofs” pea variety was subjected to 3-row spaces (30, 40 and 50 cm) and 3-row distances (5, 10 and 15 cm). According to the results, difference was shown statistically for the effects of row spaces and row distances on seed yield. The highest seed yield was 2582.1 kg ha-1 on 30 cm of row spaces while 2562.2 kg ha-1 on 15 cm of distances. Consequently, the optimum planting density was determined as 30 x 15 cm for Jofs pea variety growing in Konya.

Keywords: pea, row space, row distance, seed yield

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Authors: Timothy Garvey, Don Driscoll

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Within Tasmania, the growling grass frog (Litoria raniformis) has experienced a rapid contraction in distribution. This decline is primarily attributed to habitat loss through landscape modification and improved land drainage. Reductions in seasonal water-sources have placed increasing importance on permanent water bodies for reproduction and foraging. Tasmanian agricultural and commercial forestry landscapes often feature small artificial ponds, utilized for watering livestock and fighting wildfires. Improved knowledge of how L. raniformis may be exploiting anthropogenic ponds is required for improved conservation management. We implemented telemetric tracking in order to evaluate the spatial ecology of L. raniformis (n = 20) within agricultural and managed forestry sites, with tracking conducted periodically over the breeding season (November/December, January/February, March/April). We investigated (1) potential differences in habitat utilization between agricultural and plantation sites, and (2) the post-breeding dispersal of individual frogs. Frogs were found to remain in close proximity to ponds throughout November/December, with individuals occupying vegetative depauperate water bodies beginning to disperse by January/February. Dispersing individuals traversed exposed plantation understory and agricultural pasture land in order to enter patches of native scrubland. By March/April all individuals captured at minimally vegetated ponds had retreated to adjacent scrub corridors. Animals found in ponds featuring dense riparian vegetation were not recorded to disperse. No difference in behavior was recorded between sexes. Rising temperatures coincided with increased movement by individuals towards native scrub refugia. The patterns of movement reported in this investigation emphasize the significant contribution of manmade water-bodies towards the conservation of L. raniformis within modified landscapes. The use of natural scrubland as cyclical retreats between breeding seasons also highlights the importance of the continued preservation of remnant vegetation corridors. Loss of artificial dams or buffering scrubland in heavily altered landscapes could see the breakdown of the greater L. raniformis meta-population further threatening their regional persistence.

Keywords: habitat loss, modified landscapes, spatial ecology, telemetry

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Authors: Lujain Khraiba

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Recently, there is a broad recognition that micro-climate conditions contribute to the quality of life in urban spaces outdoors, both from economical and social viewpoints. The consideration of urban micro-climate and outdoor thermal comfort in urban design and planning processes has become one of the important aspects in current related studies. However, these aspects are so far not considered in urban planning regulations in practice and these regulations are often poorly adapted to the local climate and culture. Therefore, there is a huge need to adapt the existing planning regulations to the local climate especially in cities that have extremely hot weather conditions. The overall aim of this study is to point out the complexity of the relationship between urban planning regulations, urban design, micro-climate and outdoor thermal comfort in the hot dry city of Damascus, Syria. The main aim is to investigate the temporal and spatial effects of micro-climate on urban surface temperatures and outdoor thermal comfort in different urban design patterns as a result of urban planning regulations during the extreme summer conditions. In addition, studying different alternatives of how to mitigate the surface temperature and thermal stress is also a part of the aim. The novelty of this study is to highlight the combined effect of urban surface materials and vegetation to develop the thermal environment. This study is based on micro-climate simulations using ENVI-met 3.1. The input data is calibrated according to a micro-climate fieldwork that has been conducted in different urban zones in Damascus. Different urban forms and geometries including the old and the modern parts of Damascus are thermally evaluated. The Physiological Equivalent Temperature (PET) index is used as an indicator for outdoor thermal comfort analysis. The study highlights the shortcomings of existing planning regulations in terms of solar protection especially at street levels. The results show that the surface temperatures in Old Damascus are lower than in the modern part. This is basically due to the difference in urban geometries that prevent the solar radiation in Old Damascus to reach the ground and heat up the surface whereas in modern Damascus, the streets are prescribed as wide spaces with high values of Sky View Factor (SVF is about 0.7). Moreover, the canyons in the old part are paved in cobblestones whereas the asphalt is the main material used in the streets of modern Damascus. Furthermore, Old Damascus is less stressful than the modern part (the difference in PET index is about 10 °C). The thermal situation is enhanced when different vegetation are considered (an improvement of 13 °C in the surface temperature is recorded in modern Damascus). The study recommends considering a detailed landscape code at street levels to be integrated in urban regulations of Damascus in order to achieve a better urban development in harmony with micro-climate and comfort. Such strategy will be very useful to decrease the urban warming in the city.

Keywords: micro-climate, outdoor thermal comfort, urban planning regulations, urban spaces

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Authors: Kadi-Hanifi Halima, Amghar Fateh

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Steppes of arid Mediterranean zones are deeply threatened by desertification. To stop or alleviate ecological and economic problems associated with this desertification, management actions have been implemented since the last three decades. The struggle against desertification has become a national priority in many countries. In Algeria, several management techniques have been used to cope with desertification. This study aims at investigating the effect of exclosure on floristic diversity and chemical soil properties after four years of implementation. 167 phyto-ecological samples have been studied, 122 inside the exclosure and 45 outside. Results showed that plant diversity, composition, vegetation cover, pastoral value and soil fertility were significantly higher in protected areas.

Keywords: desertification, arid, pastoral management, plant community soil fertility, gestation of environment, Algeria

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Authors: Md Y. Reja, Samuel D. Brody, Wesley E. Highfield, Galen D. Newman

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Historically, wetlands in the United States have been lost due to agriculture, anthropogenic activities, and rapid urbanization along the coast. Such losses of wetlands have resulted in high flooding risk for coastal communities over the period of time. In addition, alteration of wetlands via the Section 404 Clean Water Act permits can increase the flooding risk to future hurricane events, as the cumulative impact of this program is poorly understood and under-accounted. Further, recovery after hurricane events is acting as an encouragement for new development and reconstruction activities by converting wetlands under the wetland alteration permitting program. This study investigates the degree to which hurricane recovery activities in coastal communities are undermining the ability of these places to absorb the impacts of future storm events. Specifically, this work explores how and to what extent wetlands are being affected by the federal permitting program post-Hurricane Ike in 2008. Wetland alteration patterns are examined across three counties (Harris, Galveston, and Chambers County) along the Texas Gulf Coast over a 10-year time period, from 2004-2013 (five years before and after Hurricane Ike) by conducting descriptive spatial analyses. Results indicate that after Hurricane Ike, the number of permits substantially increased in Harris and Chambers County. The vast majority of individual and nationwide type permits were issued within the 100-year floodplain, storm surge zones, and areas damaged by Ike flooding, suggesting that recovery after the hurricane is compromising the ecological resiliency on which coastal communities depend. The authors expect that the findings of this study can increase awareness to policy makers and hazard mitigation planners regarding how to manage wetlands during a long-term recovery process to maintain their natural functions for future flood mitigation.

Keywords: ecological resiliency, Hurricane Ike, recovery, Section 404 Permitting, wetland alteration

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Authors: Amina Naidja, Zedira Khammar, Ines Soltani

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This study investigates the impact of urban development on the urban heat island (UHI) effect in the semi-arid Aures region of Algeria, integrating remote sensing data with statistical analysis and community surveys to examine the interconnected environmental and social dynamics. Using Landsat 8 satellite imagery, temporal variations in the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and land use/land cover (LULC) changes are analyzed to understand patterns of urbanization and environmental transformation. These environmental metrics are correlated with land surface temperature (LST) data derived from remote sensing to quantify the UHI effect. To incorporate the social dimension, a structured questionnaire survey is conducted among residents in selected urban areas. The survey assesses community perceptions of urban heat, its impacts on daily life, health concerns, and coping strategies. Statistical analysis is employed to analyze survey responses, identifying correlations between demographic factors, socioeconomic status, and perceived heat stress. Preliminary findings reveal significant correlations between built-up areas (NDBI) and higher LST, indicating the contribution of urbanization to local warming. Conversely, areas with higher vegetation cover (NDVI) exhibit lower LST, highlighting the cooling effect of green spaces. Social survey results provide insights into how UHI affects different demographic groups, with vulnerable populations experiencing greater heat-related challenges. By integrating remote sensing analysis with statistical modeling and community surveys, this study offers a comprehensive understanding of the environmental and social implications of urban development in semi-arid climates. The findings contribute to evidence-based urban planning strategies that prioritize environmental sustainability and social well-being. Future research should focus on policy recommendations and community engagement initiatives to mitigate UHI impacts and promote climate-resilient urban development.

Keywords: urban heat island, remote sensing, social analysis, NDVI, NDBI, LST, community perception

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Authors: Hadj Miloua, Abbes Azzi

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The objective of the present paper is to understand, predict and modeled the fire behavior in confined and open area in different conditions and diverse fuels such as liquid pool fire and the vegetative materials. The distinctive problems are a ventilated road tunnel used for urban transport, by the characterization installations of ventilation and his influence in the mode of smoke dispersion and the flame shape. A general investigation is relatively traditional, based on the modeling and simulation the scenario of the pool fire interacted with wind ventilation by the use of numerical software fire dynamic simulator FDS ver.5 to simulate the fire in ventilated tunnel. The second simulation by WFDS.5 is Wildland fire which is always occurs in forest and rangeland fire environments and will thus have an impact on people, property and resources.

Keywords: fire, road tunnel, simulation, vegetation, wildland

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Authors: Ali Razmi, Saeed Golian

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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: Kruti Jaruriya

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Distribution of arsenic (As) and its compound and related toxicology are serious concerns. This is particularly so since millions worldwide are suffering from toxicity due to drinking of As-contaminated groundwater. The Bengal delta plain, formed by the Ganga– Padma–Meghna–Brahmaputra river basin, covering several districts of West Bengal, India and Bangladesh is considered as the worst As affected alluvial basin. However, some equally affected, if not more, areas are emerging in upper Brahmaputra plains. The present study was carried out to examine As contamination trends in the worst affected part of Assam, India. Arsenic (As) mobilization to the groundwater of Brahmaputra floodplains was investigated in Titabor, Jorhat District, located in the North Eastern part of India. The groundwater and the aquifer geochemistry were characterized. The groundwater is characterized by high dissolved Fe, Mn, and HCO-3 and low concentrations of NO-3 and SO2-4 indicating anoxic conditions prevailing in the groundwater. Fifty groundwater samples collected from shallow and deep tubewells of Titabor, Jorhat district (Assam) were examined. Along with total As, examination of concentration levels of other key parameters, viz., pH, EC, Fe, Mn , Mg2+, Ca2+, Na+, K+, PO43- , HCO-3 , NO3- ,Cl - and SO42- was also carried out. In respect to the permissible guideline of World Health Organization (WHO: As 0.01 ppm, Fe 1.0 ppm, and Mn 0.3 ppm for potable water), the range of As concentration in the groundwater varied from 0.014 to 0.604 mg/L with mean concentration 0.184 mg/L. The present study showed that out of the 50 groundwater samples,100%, 54%, and 42% were found contaminated with higher metal contents (for total As, Fe, and Mn, respectively). The results of hydrogeochemical study revealed that the reductive dissolution of MnOOH and FeOOH represents an important mechanism of arsenic release in the study area along with major cations playing an important role in leaching of As into the groundwater. Arsenic released by oxidation of pyrite, as water levels are drawn down and air enters the aquifer, contributes negligibly to the problem of As pollution. Identification of the mechanism of As release to groundwater helps to provide a framework to guide the placement of new water wells so that they will have acceptable concentrations of As.

Keywords: arsenic, assam, brahmaputra floodplain, groundwater, hydrogeochemistry

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Authors: Amit Kumar Verma

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The present study deals with fire prediction model in Terai Arc Landscape, one of the most dramatic ecosystems in Asia where large, wide-ranging species such as tiger, rhinos, and elephant will thrive while bringing economic benefits to the local people. Forest fires cause huge economic and ecological losses and release considerable quantities of carbon into the air and is an important factor inflating the global burden of carbon emissions. Forest fire is an important factor of behavioral cum ecological habit of tiger in wild. Post fire changes i.e. micro and macro habitat directly affect the tiger habitat or land. Vulnerability of fire depicts the changes in microhabitat (humus, soil profile, litter, vegetation, grassland ecosystem). Microorganism like spider, annelids, arthropods and other favorable microorganism directly affect by the forest fire and indirectly these entire microorganisms are responsible for the development of tiger (Panthera tigris) habitat. On the other hand, fire brings depletion in prey species and negative movement of tiger from wild to human- dominated areas, which may leads the conflict i.e. dangerous for both tiger & human beings. Early forest fire prediction through mapping the risk zones can help minimize the fire frequency and manage forest fires thereby minimizing losses. Satellite data plays a vital role in identifying and mapping forest fire and recording the frequency with which different vegetation types are affected. Thematic hazard maps have been generated by using IDW technique. A prediction model for fire occurrence is developed for TAL. The fire occurrence records were collected from state forest department from 2000 to 2014. Disciminant function models was used for developing a prediction model for forest fires in TAL, random points for non-occurrence of fire have been generated. Based on the attributes of points of occurrence and non-occurrence, the model developed predicts the fire occurrence. The map of predicted probabilities classified the study area into five classes very high (12.94%), high (23.63%), moderate (25.87%), low(27.46%) and no fire (10.1%) based upon the intensity of hazard. model is able to classify 78.73 percent of points correctly and hence can be used for the purpose with confidence. Overall, also the model works correctly with almost 69% of points. This study exemplifies the usefulness of prediction model of forest fire and offers a more effective way for management of forest fire. Overall, this study depicts the model for conservation of tiger’s natural habitat and forest conservation which is beneficial for the wild and human beings for future prospective.

Keywords: fire prediction model, forest fire hazard, GIS, landsat, MODIS, TAL

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Authors: Benmessaoud Hassen

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The sensitivity to the desertification map of the south of Aurès region has been elaborated by the crossing of four thematic layers capable to have an impact on the process of desertification. The following step is inspired of MEDALUS (Mediterranean desertification and land Use), which use qualitative index to define the environment zones sensitive to the desertification. The cartographical information of vegetation, the climate, the soil and the socioeconomic state descended from cartographic data transformed to numerical data then seized on, structured and managed by an algorithm dedicated to a geographical information system. In step with information, each layer makes object of 3 or 4 classes, the geometrical median of the four layers used are leaded to sensitivity classes (ISD) of different mapped environment.

Keywords: information systems, thematic layers, the sensitivity to the desertification map, concept MEDALUS, South of Aurès

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Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

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Authors: Refilwe Moeletsi

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Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

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Authors: F. Pal-Fam, S. Keszthelyi

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Phytosanitary condition of sunflower (Helianthus annuus L.) was endangered by several phytopathogenic agents, mainly microfungi, such as Sclerotinia sclerotiorum, Diaporthe helianthi, Plasmopara halstedtii, Macrophomina phaseolina and so on. There are more agrotechnical and chemical technologies against them, for instance, tolerant hybrids, crop rotations and eventually several in-crop chemical treatments. There are different fungicide treatment methods in sunflower in Hungarian agricultural practice in the quest of obtaining healthy and economic plant products. Besides, there are many choices of useable active ingredients in Hungarian sunflower protection. This study carried out into the examination of the effect of five different fungicide active substances (found on the market) and three different application modes (early; late; and early and late treatments) in a total number of 9 sample plots, 0.1 ha each other. Five successive vegetation periods have been investigated in long term, between 2013 and 2017. The treatments were: 1)untreated control; 2) boscalid and dimoxystrobin late treatment (July); 3) boscalid and dimoxystrobin early treatment (June); 4) picoxystrobin and cyproconazole early treatment; 5) picoxystrobin and cymoxanil and famoxadone early treatment; 6) picoxystrobin and cyproconazole early; cymoxanil and famoxadone late treatments; 7) picoxystrobin and cyproconazole early; picoxystrobin and cymoxanil and famoxadone late treatments; 8) trifloxystrobin and cyproconazole early treatment; and 9) trifloxystrobin and cyproconazole both early and late treatments. Due to the very different yearly weather conditions different phytopathogenic fungi were dominant in the particular years: Diaporthe and Alternaria in 2013; Alternaria and Sclerotinia in 2014 and 2015; Alternaria, Sclerotinia and Diaporthe in 2016; and Alternaria in 2017. As a result of treatments ‘infection frequency’ and ‘infestation rate’ showed a significant decrease compared to the control plot. There were no significant differences between the efficacies of the different fungicide mixes; all were almost the same effective against the phytopathogenic fungi. The most dangerous Sclerotinia infection was practically eliminated in all of the treatments. Among the single treatments, the late treatment realised in July was the less efficient, followed by the early treatments effectuated in June. The most efficient was the double treatments realised in both June and July, resulting 70-80% decrease of the infection frequency, respectively 75-90% decrease of the infestation rate, comparing with the control plot in the particular years. The lowest yield quantity was observed in the control plot, followed by the late single treatment. The yield of the early single treatments was higher, while the double treatments showed the highest yield quantities (18.3-22.5% higher than the control plot in particular years). In total, according to our five years investigation, the most effective application mode is the double in-crop treatment per vegetation time, which is reflected by the yield surplus.

Keywords: fungicides, treatments, phytopathogens, sunflower

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Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

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One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

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Authors: Antti Nurminen, Avleen Malhi

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Significant progress in intelligent systems in combination with exceedingly wide application domains having machine learning as the core technology are usually opaque, non-intuitive, and commonly complex for human users. We use innovative IoT technology which monitors and analyzes moisture, humidity, luminosity and temperature levels to assist end users for optimization of environmental conditions for their houseplants. For plant health monitoring, we construct a system yielding the Normalized Difference Vegetation Index (NDVI), supported by visual validation by users. We run the system for a selected plant, basil, in varying environmental conditions to cater for typical home conditions, and bootstrap our AI with the acquired data. For end users, we implement a web based user interface which provides both instructions and explanations.

Keywords: explainable artificial intelligence, intelligent agent, IoT, NDVI

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Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Luana Guerra, Silvio C. Sampaio, Vladimir Pavan Margarido, Ralpho R. Reis

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Brazil is the world's largest consumer of pesticides. The excessive use of these compounds has negative impacts on animal and human life, the environment, and food security. Bees, crucial for pollination, are exposed to pesticides during the collection of nectar and pollen, posing risks to their health and the food chain, including honey contamination. Aquatic sediments are also affected, impacting water quality and the microbiota. Therefore, the analysis of aquatic sediments and bee honey is essential to identify environmental contamination and monitor ecosystems. The aim of this study was to use samples of honey from honeybees (Apis mellifera) and aquatic sediment as bioindicators of environmental contamination by pesticides and their relationship with agricultural use in the surrounding areas. The sample collections of sediment and honey were carried out in two stages. The first stage was conducted in the Bituruna municipality region in the second half of the year 2022, and the second stage took place in the regions of Laranjeiras do Sul, Quedas do Iguaçu, and Nova Laranjeiras in the first half of the year 2023. In total, 10 collection points were selected, with 5 points in the first stage and 5 points in the second stage, where one sediment sample and one honey sample were collected for each point, totaling 20 samples. The honey and sediment samples were analyzed at the Laboratory of the Paraná Institute of Technology, with ten samples of honey and ten samples of sediment. The selected extraction method was QuEChERS, and the analysis of the components present in the sample was performed using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The pesticides Azoxystrobin, Epoxiconazole, Boscalid, Carbendazim, Haloxifope, Fomesafen, Fipronil, Chlorantraniliprole, Imidacloprid, and Bifenthrin were detected in the sediment samples from the study area in Laranjeiras do Sul, Paraná, with Carbendazim being the compound with the highest concentration (0.47 mg/kg). The honey samples obtained from the apiaries showed satisfactory results, as they did not show any detection or quantification of the analyzed pesticides, except for Point 9, which had the fungicide tebuconazole but with a concentration Keywords: contamination, water research, agrochemicals, beekeeping activity

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Authors: Nadeem Munawar, Tariq Mahmood, Paula Rivadeneira, Ali Akhter

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In this paper, we review on rodent species which are common inhabitants of agricultural landscapes where they are an important prey source for a wide variety of avian, reptilian, and mammalian predators. Agricultural fields are surrounded by fallow land, which provide suitable sites for shelter and breeding for rodents, while shrubs, grasses, annual weeds and forbs may provide supplementary food. The assemblage of rodent’s fauna in the cropland habitats including cropped fields, meadows and adjacent field structures like hedgerows, woodland and field margins fluctuates seasonally. The mature agricultural crops provides good source of food and shelter to the rodents and these factors along with favorable climatic factors/season facilitate breeding activities of these rodent species. Changes in vegetation height and vegetative cover affect two important aspects of a rodent’s life: food and shelter. In addition, during non-crop period vegetation can be important for building nests above or below ground and it provides thermal protection for rodents from heat and cold. The review revealed that rodents form a very diverse group of mammals, ranging from tiny pigmy mice to big capybaras, from arboreal flying squirrels to subterranean mole rats, from opportunistic omnivores (e.g. Norway rats) to specialist feeders (e.g. the North African fat sand rats that feed on a single family of plants only). It is therefore no surprise that some species thrive well under the conditions that are found in agricultural fields. The review on the population dynamics of the rodent species indicated that they are agricultural pests probably due to the heterogeneous landscape and to the high rotativity of vegetable crop cultivation. They also cause damage to various crops, directly and indirectly, by gnawing, spoilage, contamination and hoarding activities, besides this behavior they have also significance importance in agricultural habitat. The burrowing activities of rodents alter the soil properties around their burrows which improve its aeration, infiltration, increase the water holding capacity and thus encourage plant growth. These properties are beneficial for the soil because they affect absorption of phosphorus, absorption zinc, copper, other nutrients and the uptake of water and thus rodents are known as indicator species in agricultural fields. Our review suggests that wide crop field’s borders, particularly those contiguous to various cropland fields, should be understood as priority sites for nesting, feeding, and cover for the rodent’s fauna. The goal of this review paper is to provide a comprehensive synthesis of understanding regarding rodent habitat and biodiversity in agricultural landscapes.

Keywords: agricultural landscapes, food, indicator species, shelter

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: Sushmita Chaudhuri, Parthiba Basu

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Urbanization leads to habitat degradation and is responsible for the fast disappearance of native butterfly species. Random sampling of rural, suburban and urban sites in an around Kolkata metropolis revealed the presence of 28 species of butterfly belonging to 5 different families in winter (February-March). Butterfly diversity, species richness and abundance decreased with increase in urbanization. Psyche (Leptosia nina of family Pieridae) was the most predominant butterfly species found everywhere in Kolkata during the winter period. The most dominant family was Nymphalidae (11species), followed by Pieridae (6 species), Lycaenidae (5 species), Papilionidae (4 species) and Hesperiidae (2 species). The rural and suburban sites had butterfly species that were unique to those sites. Vegetation cover and flowering shrub density were significantly related to butterfly diversity.

Keywords: butterfly, Kolkata metropolis, Shannon-Weiner diversity index, species diversity

Procedia PDF Downloads 290

Authors: Evans V. Mauda, Stefan H. Foord, Thinandavha C. Munyai

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The greatest threat to biodiversity is a loss of habitat through landscape fragmentation and attrition. Land use changes are therefore among the most immediate drivers of species diversity. Urbanization and agriculture are the main drivers of habitat loss and transformation in the Savanna biomes of South Africa. Agricultural expansion and the intensification in particular, take place at the expense of biodiversity and will probably be the primary driver of biodiversity loss in this century. Arthropods show measurable behavioural responses to changing land mosaics at the smallest scale and heterogeneous environments are therefore predicted to support more complex and diverse biological assemblages. Ants are premier soil turners, channelers of energy and dominate insect fauna, while spiders are a mega-diverse group that can regulate other invertebrate populations. This study aims to quantify the response of these two taxa in a rural-urban mosaic of a rapidly developing communal area. The study took place in and around two villages in the north-eastern corner of South Africa. Two replicates for each of the dominant land use categories, viz. urban settlements, dryland cultivation and cattle rangelands, were set out in each of the villages and sampled during the dry and wet seasons for a total of 2 villages × 3 land use categories × 2 seasons = 24 assemblages. Local scale variables measured included vertical and horizontal habitat structure as well as structural and chemical composition of the soil. Ant richness was not affected by land use but local scale variables such as vertical vegetation structure (+) and leaf litter cover (+), although vegetation complexity at lower levels was negatively associated with ant richness. However, ant richness was largely shaped by regional and temporal processes invoking the importance of dispersal and historical processes. Spider species richness was mostly affected by land use and local conditions highlighting their landscape elements. Spider richness did not vary much between villages and across seasons and seems to be less dependent on context or history. There was a considerable amount of variation in spider richness that was not explained and this could be related to factors which were not measured in this study such as temperature and competition. For both ant and spider assemblages the constrained ordination explained 18 % of variation in these taxa. Three environmental variables (leaf litter cover, active carbon and rock cover) were important in explaining ant assemblage structure, while two (sand and leaf litter cover) were important for spider assemblage structure. This study highlights the importance of disturbance (land use activities) and leaf litter with the associated effects on ant and spider assemblages across the study area.

Keywords: ants, assemblages, biosphere, diversity, land use, spiders, urbanization

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