Search results for: land sat TM

Authors: Mohammed Masum, Mohammad Omer Faruk Khan, Md. Nazwanul Haque, Anwar Sadat Md. Sayem, Md. Azhar Hossain

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The study area is the Hakaluki Haor which is the second largest wet land of Bangladesh. It spans over the districts of Moulvibazar and Sylhet in southeast Bangladesh. The study was focused in the exploration of peat reserve, reconstruction of the paleo-environment as well as the utilization of the peat resources. Peat is found randomly from 0.5 m to 7 m below the surface and 1 m to 11 m thickness at over 40 beels as well as small plain lands of 90 km2 area of Hakaluki Haor. The total reserve of peat is 282 million ton in wet condition and 112 million ton in dry condition. The peat deposits of Hakaluki Haor area is the largest peat reserves of the Bangladesh. Peat bearing Hakaluki Haor is a low-lying wet land which geological term is synclinal depression. It may be a syncline between two anticlines which was filled with sediments as well as various plant materials derived from the hilly region (anticline) on both sides (west and east) of the Haor. The transportation may be triggered by large natural disasters or any tectonic reason. On the other hand vegetation occurred in this depression as aquatic plants which might have been destroyed by large natural disasters or any tectonic reason. As environment dictates the characteristics and the source of sediments, various aspects of the sediment are indicators of the environment. Peat has mainly industrial importance as a fuel for power production, traditionally used for cooking, domestic heating and in brick fields, also used as insulator in many industries, agricultural purposes, retaining moisture in soil, raw material in horticulture and colour industries etc. Power plants of about 100 MW capacities may be established in this region based on peat of Hakaluki Haor which may be continued more than one hundred years.

Keywords: peat, pale environment, Hakaluki Haor, beel, syncline, anticline

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Authors: Umar Javed, Kristen Blann, Philip Adalikwu, Maryam Sahraei, John McMaine

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The soil conservation service curve number (SCS-CN) is a widely used method to assess direct runoff depth based on specific rainfall events. “Actual” estimated runoff depth was estimated by subtracting the change in soil moisture from the depth of precipitation for each discrete rain event during the growing seasons from 2021 to 2023. Fields under investigation were situated in a HUC-12 watershed in southeastern South Dakota selected for a common soil series (Nora-Crofton complex and Moody-Nora complex) to minimize the influence of soil texture on soil moisture. Two soil moisture probes were installed from May 2021 to October 2023, with exceptions during planting and harvest periods. For each field, “Textbook” CN estimates were derived from the TR-55 table based on corresponding mapped land use land cover LULC class and hydrologic soil groups from web soil survey maps. The TR-55 method incorporated HSG and crop rotation within the study area fields. These textbook values were then compared to actual CN values to determine the impact of tillage practices on CN and runoff. Most fields were mapped as having a textbook C or D HSG, but the HSG of actual CNs was that of a B or C hydrologic group. Actual CNs were consistently lower than textbook CNs for all management practices, but actual CNs in conventionally tilled fields were the highest (and closest to textbook CNs), while actual CNs in no-till fields were the lowest. Preliminary results suggest that no-till practice reduces runoff compared to conventional till. This research highlights the need to use CNs that incorporate agricultural management to more accurately estimate runoff at the field and watershed scale.

Keywords: curve number hydrology, hydrologic soil groups, runoff, tillage practices

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Authors: Dieudonne Mevono Mvogo

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The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES)-Intergovernmental Panel on Climate Change (IPCC) co-sponsored workshop report suggests that climate change and biodiversity loss are two of the most pressing issues of the Anthropocene. Research establishes the interconnection between climate change and biodiversity. On the one hand, the impact of climate change on biodiversity loss – 14 % over the past century – is projected to surpass other threats – land and sea use 34 % and direct exploitation of species 23 % – during the 21st century. Response measures to climate change also affect biodiversity negatively or positively. On the other hand, actions to halt or reverse biodiversity loss can enhance land and ocean capacity for carbon sequestration. These actions can also promote adaptation by ensuring adaptive capacity. This systemic interaction between climate change and biodiversity affects the human quality of life. The United Nations Secretariat's report entitled 'Gaps in international environmental law and environment-related instruments: towards a global pact for the environment,' released in 2018, states that cooperation and mutual support among agreements dealing with climate change, the protection of the marine environment, freshwater resources and hazardous waste are indispensable for the effective implementation of the Convention on the Biological Diversity (CBD). Since biodiversity is being lost at an alarming rate, this study aims to evaluate the cooperative framework for the coherence and coordination between climate change and biodiversity regimes to provide co-benefits for climate and biodiversity crises. It questions the potential improvement regarding integrating ecosystem-based approaches and nature-based solutions – promoted by the CBD – into the United Nations Framework Convention on Climate Change (UNFCCC).

Keywords: rio conventions, climate change, biodiversity, cooperative framework, ecosystem-based approaches, nature-based solutions

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Authors: Karim Ahmed

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The purpose of this study was to investigate how factoring the impact of natural disasters beyond flooding would affect managed retreat policy eligibility in the United States. For the study design, a correlation analysis method compared weighted measures of flooding and other natural disasters (e.g., wildfires, tornadoes, heatwaves, etc.) to CBSA Populated areas, the prevalence of cropland, and relative poverty on a county level. The study found that the vast majority of CBSAs eligible for managed retreat programs under a policy inclusive of non-flooding events would have already been covered by flood-only managed retreat policies. However, it is noteworthy that a majority of those counties that are not covered by a flood-only managed retreat policy have high rates of poverty and are either heavily populated and/or agriculturally active. The correlation is particularly strong between counties that are subject to multiple natural hazards and those that have both high rates of relative poverty and cropland prevalence. There is currently no managed retreat policy for agricultural land in the United States despite the environmental implications and food supply chain vulnerabilities related to at-risk cropland. The findings of this study suggest both that such a policy should be created and, when it is, that special attention should be paid to non-flood natural disasters affecting agricultural areas. These findings also reveal that, while current flood-based policies in the United States serve many areas that do need access to managed retreat funding and implementation, other vulnerable areas are overlooked by this approach. These areas are often deeply impoverished and are therefore particularly vulnerable to natural disaster; if and when those disasters do occur, these areas are often less financially prepared to recover or retreat from the disaster’s advance and, due to the limitations of the current policies discussed above, are less able to take the precautionary measures necessary to mitigate their risk.

Keywords: flood, hazard, land use, managed retreat, wildfire

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Authors: Mumtaz Ahmed Sohag, Ishaq Ahmed Sohag

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Kebbi State, located in the Nort-West of Nigeria, is rich in water resources as the major rivers viz. Niger and Rima irrigate a vast majority of land. Besides, there is significant amount of groundwater, which farmers use for agriculture purpose. The groundwater is also a major source of agricultural and domestic water as wells are installed in almost all parts of the region. Although Kebbi State is rich in water, however, there are some pertinent issues which are hampering its agricultural productivity. The low lands (locally called Fadama), has spread out to a vast area. It is inundated every year during the rainy season which lasts from June to September every year. The farmers grow rice during the rainy season when water is standing. They cannot do further agricultural activity for almost two months due to high standing water. This has resulted in widespread waterlogging problem. Besides, the impact of climate change is resulting in rapid variation in river/stream flows. The information about water bodies regarding the availability of water for agricultural and other uses and the behavior of rivers at different flows is seldom available. Furthermore, sediment load (suspended and bedload) is not measured due to which land erosion cannot be countered effectively. This study, carried out in seven different irrigation regions of Kebbi state, found that diversion structures need to be constructed at some strategic locations for the supply of surface water to the farmers. The water table needs to be lowered through an effective drainage system. The monitoring of water bodies is crucial for sound data to help efficient regulation and management of water. Construction of embankments is necessary to control frequent floods in the rivers of Niger and Rima. Furthermore, farmers need capacity and awareness for participatory irrigation management.

Keywords: water bodies, floods, agriculture, waterlogging

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Authors: Hadi Allafta, Christian Opp

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Soil erosion is a major concern in the Shatt Al-Arab basin owing to the steepness of its topography as well as the remarkable altitudinal deference between the upstream and downstream parts of the basin. Such conditions resulted in soil vulnerability to erosion; huge amounts of soil are annually transported, creating enormous implications such as land degradation, structure damage, biodiversity loss, productivity decline, etc. Thus, evaluation of soil erosion risk and its spatial distribution is crucial to build adatabase for efficient control measures. The present study used revised universal soil loss equation (RUSLE) model integrated with Geographic Information System (GIS) for depicting soil erosion hazard zones in the Shatt Al-Arab basin. The RUSLE model incorporated several parameters such as rainfall-runoff erosivity, soil erodibility, slope length and steepness, land cover and management, and conservation support practice for soil erosion zonation. High to medium soil loss of 100 to 20 ton perhectare per year represents around 25% of the basin area, while the areas of low soil loss of less than 20 ton per hectare per year occupied the rest of the total area. The high soil loss rates are linked to areas of high rainfall levels, loamy soil domination, elevated terrains/plateau margins with steep side slope, and high cultivation activities. The findings of the current study can be useful for managers and policy makers in the implementation of a suitable conservation program to reduce soil erosion or to recommend soil conservation acts if development projects are to be continued at regions of high soil erosion risk.

Keywords: geographic information system, revised universal soil loss equation, shatt Al-Arab basin, soil erosion

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Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

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Authors: Stanis Koko Nyalongomo, Benjamin Mputela Bankanza, Moise Kisempa Mahungudi

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Several areas in the Democratic Republic of Congo (DRC) experience serious problems of streaming and soil erosion. Erosion leads to degradation of soil health, and the three main causative factors of similar importance are deforestation, overgrazing, and land agricultural mismanagement. Degradation of soil health leads to a decrease in agricultural productivity and carbon dioxide (CO₂), and other greenhouse gas emissions. Agricultural productivity low, and sanitation-related diseases are a concern of a majority of DRC rural people -whose main livelihoods are conventional smallholder agriculture- due to degradation of agricultural soil health and prevalence of inappropriate sanitation in rural areas. Land management practices that increase soil carbon stocks on agricultural lands with practices including conservation agriculture and agroforestry do not only limit CO₂ emissions but also help prevent erosion while enhancing soil health and productivity. Promotion to adopt sustainable land management practices, especially conversion to well-managed agroforestry practices, is a necessity. This needs to be accompanied by incentives. Methods that incite smallholders to adopt practices that increase carbon stocks in agricultural lands and enhance soil health and productivity for social, economic, and environmental benefits, and give them the ability to get and use household dry toilets -included activities to inform and raise smallholder households awareness on the conversion of croplands to well-managed agroforestry systems through planting at least 20 fruit trees and/or acacias, soil carbon and practices that sequester it in soil and ecological sanitation; and offer smallholders technique and material supports and incentives under the form of dry toilets constructed for free for well-managed agroforestry implementation- were carried out to address problems of soil erosion as well as agricultural productivity and sanitation-related diseases. In 2018 and 2019, 19 of 23 targeted smallholder households expressed their satisfaction and converted their croplands to agroforestry through planting 374 trees, and each gotten 1 dry toilet constructed for free. Their neighbors expressed a willingness to participate in the project. Conversion to well-managed agroforestry practices offers many advantages to both farmers and the environment. The strategy of offering smallholders incentives for soil-friendly agricultural practices, especially well-managed agroforestry, is one of the solutions to prevent soil erosion. DRC rural people whose majority are smallholder households, need to be able to get and use dry toilets. So, dry toilets could be offered like incentives for well-managed agroforestry practices. Given the many advantages agroforestry and dry toilet can offer, recommendations are made for funding organizations to support such projects that promote the adoption of soil health practices.

Keywords: agroforestry, croplands, soil carbon, soil health

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Authors: Felicity Aphiwe Mkhongi, Walter Musakwa

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Smallholder crop production is a defining factor in achieving food security, particularly at the household level. However, the number of abandoned arable fields is increasing in communal areas of South Africa. While substantial efforts have been devoted to addressing food insecurity in the country, ownership of arable land has not been supplemented with sustainable food production for households. This paper analyses household food security in the context of deagrarianization in two villages, Ambros (Eastern Cape) and Maramanzhi (Limpopo). Semi-structured questionnaires were administered to acquire both qualitative and quantitative data from 106 heads of households. The IBM SPSS Statistics 28.0 computer program was applied to complete data analysis. From the findings of the study, it was evident that compared to arable fields, a greater proportion of households own home-gardens with an average size of 2100m in Ambros and 3400m in Maramanzhi village. The majority of arable fields were abandoned, particularly in Ambros village. Household food access challenges were measured using the Household Food Insecurity Access Scale (HFIAS). This food security indicator revealed that the majority of households were mildly food insecure owing to food shortages emanating from insufficient monthly income and waning household crop production. Food was rated as a very important reason for engaging in cultivation in both villages of the study, but deagrarianization has eroded opportunities for increasing household crop production. Among other possible solutions, this study recommends that the government invest more in agriculture to allow for sustainable strategies that revive abandoned arable land, such as arable fields in communal areas of South Africa, as this could increase food production for households.

Keywords: cultivation, deagrarianization, food security, rural households, smallholder farmers

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Authors: Ayla Hoeta, Holly Winton

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Maramataka is an ancestral lunar environmental knowledge system based on environmental tohu (signs, observations or indicators), that continues to impart maatauranga (knowledge) to tangata whenua, people of the land after thousands of years. Maramataka is the mauri (energy) flow between whenua (land), moana (water) and rangi (sky), experienced through tirotiro (observing), connecting and attuning to the natural environment. Tohu serve as guidance to practises of kaiawhina (protection) a key value driving Aotearoa New Zealand led research in Antarctica. Recent developments recognise the importance of including and integrating indigenous knowledge and perspectives such as maatauranga Maaori which can provide insights into the conservation of Antarctica. We use an ancient kaupapa Maaori framework of weaving, wayfinding and attunement to navigate complexities using Hautu Waka. We investigate and weave together learnings from Antarctic and western science and indigenous Maaori maatauranga and tohu of moana, whenua and rangi to provide an indigenous perspective of Antarctica taiao and Maramataka. Drawing on past and present knowledge of environmental calendars contained in maatauranga Maaori and paleoclimate knowledge bases, field observations, interviews and whakataukii (proverbs), we aim to provide a conceptual Maramataka of the southwestern Ross Sea region and area of Antarctica. A key area of interest are the tohu related to the marama which are connected to all three interweaving spheres of moana, rangi, whenua. Maatauranga Maramataka in Aotearoa has been developed over millennia and we acknowledge the mana and sacredness of this tupuna knowledge and that this conceptual Maramataka serves as the starting point of a journey to shine light on indigenous perspectives using Maaori methods and frameworks in a dominant western science paradigm.

Keywords: Maramataka, Antarctica, Aotearoa, Maaori, tohu, moon, lunar calendar

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Marilyn S. Painagan, Willie Jones B. Saliling

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This paper reports an optimized cropping calendar and land suitability for maize in North Cotabato derived from modeling crop productivity over time and space. Using Quantum GIS, eight representative soil types and 0.3o x 0.3o climate grids shapefiles were intersected to form thirty two pedoclimatic zones within the boundaries of the province. Surveys were done to ascertain crop performance and phenological properties on field. Based on these surveys, crop parameters were calibrated specific for a variety of maize. Soil properties and climatic data (daily precipitation, maximum and minimum temperatures) from pedoclimatic zones were loaded to the FAO Aquacrop Water Productivity Model along with the crop properties from field surveys to simulate yield from 1980 to 2010. The average yield per month was computed to come up with the month of planting having the highest and lowest probable yield in a year assuming that all lands were planted with maize. The yield attributes were visualized in the Quantum GIS environment. The study revealed that optimal cropping patterns varied across North Cotabato. Highest probable yield (8000 kg/ha) can be obtained when maize is planted on May and September (sandy clay-loam soils) in the northern part of the province while the lowest probable yield (1000 kg/ha) can be obtained when maize is planted on January, February and March (clay loam soils) at the northern part of the province. Yields are simulated on the basis of varieties currently planted by farmers of North Cotabato. The resulting maps suggest where and when maize is most suitable to achieve high yields. There is a need to ground truth and validate the cropping calendar on field.

Keywords: aquacrop, quantum GIS, maize, cropping calendar, water productivity

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Authors: Kittipon Chittanukul, Chayut Bureethan, Chutimon Piromyaporn

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In Thailand, the natural gas pipeline system requires the preparation of an Environmental Impact Assessment (EIA) report for approval by the relevant agency, the Office of Natural Resources and Environmental Policy and Planning (ONEP), in the pre-construction stage. As of December 2022, PTT has a lot of gas pipeline system spanning around the country. Our experience has shown that the EIA is a significant part of the project plan. In 2011, There was a catastrophic flood in multiple areas of Thailand. It destroyed lives and properties. This event is still in Thai people’s mind. Furthermore, rainfall has been increasing for three consecutive years (2020-2022). Moreover, municipalities are situated in low land river basin and tropical rainfall zone. So many areas still suffer from flooding. Especially in 2022, there will be a 60% increase in water demand compared to the previous year. Therefore, all activities will take into account the quality of the receiving water. The above information emphasizes water and wastewater management are significant in EIA report. PTT has accumulated a large number of lessons learned in water and wastewater management. Our pipeline system execution is composed of EIA stage, construction stage, and operation and maintenance phase. We provide practical Information on water and wastewater management to enhance the EIA process for the pipeline system. The examples of lessons learned in water and wastewater management include techniques to address water and wastewater impact throughout the overall pipelines systems, mitigation measures and monitoring results of these measures. This practical information will alleviate the anxiety of the ONEP committee when approving the EIA report and will build trust among stakeholders in the vicinity of the gas pipeline system area.

Keywords: environmental impact assessment, gas pipeline system, low land basin, high risk flooding area, mitigation measure

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Authors: Faith Abdul Rasak Asharaf

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Every city has a threshold known as urban carrying capacity based on which it can withstand a particular density of people, above which the city might need to resort to measures like expanding its boundaries or growing vertically. As a result of this circumstance, the number of squatter communities is growing, as is the claustrophobic feeling of being confined inside a "concrete jungle." The expansion of suburbs, commercial areas, and industrial real estate in the areas surrounding medium-sized cities has resulted in changes to their landscapes and urban forms, as well as a systematic shift in their role in the urban hierarchy when functional endowment and connections to other territories are considered. The urban carrying capacity idea provides crucial guidance for city administrators and planners in better managing, designing, planning, constructing, and distributing urban resources to satisfy the huge demands of an evergrowing urban population. An ecological footprint is a criterion of urban carrying capacity, which is the amount of land required to provide humanity with renewable resources and absorb its trash. However, as each piece of land has its unique carrying capacity, including ecological, social, and economic considerations, these metropolitan areas begin to reach a saturation point over time. Various city models have been tried throughout the years to meet the increasing urban population density by moving the zones of work, life, and leisure to achieve maximum sustainable growth. The current scenario is that of a vertical city and compact city concept, in which the maximum density of people is attempted to fit into a definite area using efficient land use and a variety of other strategies, but this has proven to be a very unsustainable method of growth, as evidenced by the COVID-19 period. Due to a shortage of housing and basic infrastructure, densely populated cities gave rise to massive squatter communities, unable to accommodate the overflowing migrants. To achieve optimum carrying capacity, planning measures such as polycentric city and diffuse city concepts can be implemented, which will help to relieve the congested city core by relocating certain sectors of the town to the city periphery, which will help to create newer spaces for design in terms of public space, transportation, and housing, which is a major concern in the current scenario. The study's goal is focused on suggesting design options and solutions in terms of placemaking for better urban quality and urban life for the citizens once city centres have been de-densified based on urban carrying capacity and ecological footprint, taking the case of Kochi as an apt example of a highly densified city core, focusing on Edappally, which is an agglomeration of many urban factors.

Keywords: urban carrying capacity, urbanization, urban sprawl, ecological footprint

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Amritansh Agarwal, Tejaswi Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Yusif Habib

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The Volta River Basin (VRB) is a transboundary resource shared by Six (6) the West African States. It’s utilization spans across irrigation, hydropower generation, domestic/household water use, transportation, industrial processing, among others. Simultaneously, mineral resources such as gold are mined within the VRB catchment. Typically, the extraction/mining operation is earth-surface excavation; known as Artisanal and Small-scale mining. We developed a conceptual framework in the context of Water-Energy-Food (WEF) Nexus to delineate the trade-offs and synergies between the mineral extractive operation’s impact on Agricultural systems, specifically, cereal crops (e.g. Maize, Millet, and Rice) and the environment (water and soil quality, deforestation, etc.) on the VRB. Thus, the study examined the trade-offs and synergies through the WEF nexus lens to explore the extent of an eventual overarching mining preference for gold exploration with high economic returns as opposed to the presumably low yearly harvest and household income from food crops production to inform intervention prioritization. Field survey (household, expert, and stakeholder consultation), bibliometric analysis/literature review, scenario, and simulation models, including land-use land cover (LULC) analyses, were conducted. The selected study area(s) in Ghana was the location where the mineral extractive operation’s presence and impact are widespread co-exist with the Agricultural systems. Overall, the study proposes mechanisms of the virtuous cycle through FEW Nexus instead of the presumably existing vicious cycle to inform decision making and policy implementation.

Keywords: agriculture, environmental sustainability, gold Mining, synergies, trade-off, water-energy-food nexus

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Marlen Acosta Alamo, Lisa Manne, Richard Veit

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Habitat loss due to land use change is one of the leading causes of biodiversity loss worldwide. This form of habitat loss is a non-random phenomenon since the same environmental factors that make an area suitable for supporting high local biodiversity overlap with those that make it attractive for urban development. We aimed to compare the effect of two non-random habitat loss predictors on the richness, abundance, and rarity of nature-affiliated and human-affiliated North American breeding birds. For each group of birds, we simulated the non-random habitat loss using two predictors: the House Price Index as a measure of the attractiveness of an area for humans and the Normalized Difference Vegetation Index as a proxy for primary productivity. We compared the results of the two non-random simulation sets and one set of random habitat loss simulations using an analysis of variance and followed up with a Tukey-Kramer test when appropriate. The attractiveness of an area for humans predicted estimates of richness loss and increase of rarity higher than primary productivity and random habitat loss for nature-affiliated and human-affiliated birds. For example, at 50% of habitat loss, the attractiveness of an area for humans produced estimates of richness at least 5% lower and of a rarity at least 40% higher than primary productivity and random habitat loss for both groups of birds. Only for the species abundance of nature-affiliated birds, the attractiveness of an area for humans did not outperform primary productivity as a predictor of biodiversity following habitat loss. We demonstrated the value of the House Price Index, which can be used in conservation assessments as an index of the risks of habitat loss for natural communities. Thus, our results have relevant implications for sustainable urban land-use planning practices and can guide stakeholders and developers in their efforts to conserve local biodiversity.

Keywords: biodiversity loss, bird biodiversity, house price index, non-random habitat loss

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Authors: Aneesh Mathew, Arunab K. S., Atul Kumar Sharma

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The uncontrolled rise in population has led to unplanned, swift, and unsustainable urban expansion, causing detrimental environmental impacts on both local and global ecosystems. This research delves into a comprehensive examination of the Urban Heat Island (UHI) phenomenon in Bengaluru and Hyderabad, India. It centers on the spatial and temporal distribution of UHI and its correlation with air pollutants. Conducted across summer and winter seasons from 2001 to 2021 in Bangalore and Hyderabad, this study discovered that UHI intensity varies seasonally, peaking in summer and decreasing in winter. The annual maximum UHI intensities range between 4.65 °C to 6.69 °C in Bengaluru and 5.74 °C to 6.82 °C in Hyderabad. Bengaluru particularly experiences notable fluctuations in average UHI intensity. Introducing the Urban Thermal Field Variance Index (UTFVI), the study indicates a consistent strong UHI effect in both cities, significantly impacting living conditions. Moreover, hotspot analysis demonstrates a rising trend in UHI-affected areas over the years in Bengaluru and Hyderabad. This research underscores the connection between air pollutant concentrations and land surface temperature (LST), highlighting the necessity of comprehending UHI dynamics for urban environmental management and public health. It contributes to a deeper understanding of UHI patterns in swiftly urbanizing areas, providing insights into the intricate relationship between urbanization, climate, and air quality. These findings serve as crucial guidance for policymakers, urban planners, and researchers, facilitating the development of innovative, sustainable strategies to mitigate the adverse impacts of uncontrolled expansion while promoting the well-being of local communities and the global environment.

Keywords: urban heat island effect, land surface temperature, air pollution, urban thermal field variance index

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Authors: Noor Abdelhamid

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Almost half of Cairo’s growing population is housed in self-built, self-governed informal settlements serving as an alternative in the absence of government-provided public housing. These settlements emerged as the spatial expression of informal practices or activities operating outside regulated, formal frameworks. A comprehensive narrative of political events, administrative decisions, and urban policies set the stage for the growth of informal expression in Egypt. The purpose of this qualitative inquiry is to portray informal self-governance practiced by residents in the Cairo region. This research argues that informal spatial practices offer an alternative urban framework for bottom-up development in the absence of government provisions. In the context of this study, informal self-governance is defined as the residents’ autonomous control and use of public urban space in informal settlements. The case study for this research is Ard al-Liwa, a semi-formal settlement representing the majority of informal settlement typologies in Egypt, which consist of the formal occupation of land through an uncontrolled land subdivision, zoning, and construction. An inductive methodological approach is adopted to first study informal practices as singular activities and then as components of a larger environment. The collected set of empirical data consists of audiovisual material and observations obtained during regular site visits and interviews with residents native to the settlement. Methods of analysis are synthesized to identify themes in the data: the static and dynamic use of sidewalks, the urban traces of informal building allocation and construction, the de facto right to urban space, and the resultant spatial patterns. The paper concludes by positioning the research in the context of the current architectural practice, questioning the role, and responsibility, of designers in these self-governed urban regions.

Keywords: Egypt, informal settlements, self-governance, urban framework

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Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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The government that declared 'de-nuclearization' pushes up renewable energy policies such as solar power and wind power as an alternative to nuclear power generation. However, local residents who are concerned about the development and natural disasters have been hit by opposition, and related businesses around the country are experiencing difficulties. There is also a voice saying that installing a large wind power generator will cause landslides, low frequencies and noise, which will have a bad influence. Renewal is only a harmful and disgusting facility for the residents. In this way, it is expected that extreme social conflicts will occur in the decision making process related to the locally unwanted land-use (LULU). The government's efforts to solve this problem have been steadily progressing, but the systematic methodology for bringing in active participation and opinion gathering of the residents has not yet been established except for the simple opinion poll or referendum. Therefore, it is time to identify the factors that concern the local residents about the wind power generation facilities, and to find ways to make policy decision-making possible. In this study, we analyze the perception of people about offshore and onshore wind power facilities through questionnaires or interviews, and examine quantitative and qualitative precedent studies to analyze them. In addition, the study evaluates what factors affect the local acceptance of wind power facilities. As a result of the factor analysis of the questionnaire items, factors affecting the residents' acceptance of the wind power facility were extracted from four factors such as environmental, economic, risk, social, and management factor. The study also found that the influence of the determinants of local acceptance on the regional acceptability differs according to the demographic characteristics such as gender and income level. This study will contribute to minimizing the conflict on the installation of wind power facilities through communication among the local residents.

Keywords: factor analysis, local acceptance, locally unwanted land-use, LULU, wind power generation facilities

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Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

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Authors: Md. Monjurul Islam, Tofael Ahamed, Ryozo Noguchi

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Progress continues in the fight against hunger, yet an unacceptably large number of people still lack food they need for an active and healthy life. Bangladesh is one of the rising countries in the South-Asia but still lots of people are food insecure. In the last few years, Bangladesh has significant achievements in food grain production but still food security at national to individual levels remain a matter of major concern. Ensuring food security for all is one of the major challenges that Bangladesh faces today, especially production of rice in the flood and poverty prone areas. Northern part is more vulnerable than any other part of Bangladesh. To ensure food security, one of the best way is to increase domestic production. To increase production, it is necessary to secure lands for achieving optimum utilization of resources. One of the measures is to identify the vulnerable and potential areas using Land Suitability Assessment (LSA) to increase rice production in the poverty prone areas. Therefore, the aim of the study was to identify the suitable sites for food grain crop rice production in the poverty prone areas located at the northern part of Bangladesh. Lack of knowledge on the best combination of factors that suit production of rice has contributed to the low production. To fulfill the research objective, a multi-criteria analysis was done and produced a suitable map for crop production with the help of Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Primary and secondary data were collected from ground truth information and relevant offices. The suitability levels for each factor were ranked based on the structure of FAO land suitability classification as: Currently Not Suitable (N2), Presently Not Suitable (N1), Marginally Suitable (S3), Moderately Suitable (S2) and Highly Suitable (S1). The suitable sites were identified using spatial analysis and compared with the recent raster image from Google Earth Pro® to validate the reliability of suitability analysis. For producing a suitability map for rice farming using GIS and multi-criteria analysis tool, AHP was used to rank the relevant factors, and the resultant weights were used to create the suitability map using weighted sum overlay tool in ArcGIS 10.3®. Then, the suitability map for rice production in the study area was formed. The weighted overly was performed and found that 22.74 % (1337.02 km2) of the study area was highly suitable, while 28.54% (1678.04 km2) was moderately suitable, 14.86% (873.71 km2) was marginally suitable, and 1.19% (69.97 km2) was currently not suitable for rice farming. On the other hand, 32.67% (1920.87 km2) was permanently not suitable which occupied with settlements, rivers, water bodies and forests. This research provided information at local level that could be used by farmers to select suitable fields for rice production, and then it can be applied to other crops. It will also be helpful for the field workers and policy planner who serves in the agricultural sector.

Keywords: AHP, GIS, spatial analysis, land suitability

Procedia PDF Downloads 240

Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

Procedia PDF Downloads 379

Authors: Enkhjargal Bat-Ochir

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The global market of electrical and electronic equipment (EEE) has increasing rapidly while the lifespan of these products has become increasingly shorter. So, e-waste is becoming the world’s fastest growing waste stream. E-waste is a huge problem when it’s not properly disposed of, as these devices contain substances that are harmful to the environment and to human health as they contaminate the land, water, and air. This paper tends to highlight e-waste problem and harmful effects and can grasp the extent of the problem and take the necessary measures to solve it in Mongolia and to improve standards and human health.

Keywords: e -waste, recycle, electrical, Mongolia

Procedia PDF Downloads 417

Authors: Zermina Q., Wasif Y., Naeem S., Urooj S., Sajid R. A.

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Land degradation, a leading environemtnal problem and a decrease in the quality of land has become a major global issue, caused by human activities. By land degradation, more than half of the world’s drylands are affected. The worldwide scope of main saline soils is approximately 955 M ha, whereas inferior salinization affected approximately 77 M ha. In irrigated areas, a total of 58% of these soils is found. As most of the vegetation types requires fertile soil for their growth and quality production, salinity causes serious problem to the production of these vegetation types and agriculture demands. This research aims to identify the salt affected areas in the selected part of Indus Delta, Sindh province, Pakistan. This particular mangroves dominating coastal belt is important to the local community for their crop growth. Object based image analysis approach has been adopted on Landsat TM imagery of year 2011 by incorporating different mathematical band ratios, thermal radiance and salinity index. Accuracy assessment of developed salinity landcover map was performed using Erdas Imagine Accuracy Assessment Utility. Rain factor was also considered before acquiring satellite imagery and conducting field survey, as wet soil can greatly affect the condition of saline soil of the area. Dry season considered best for the remote sensing based observation and monitoring of the saline soil. These areas were trained with the ground truth data w.r.t pH and electric condutivity of the soil samples. The results were obtained from the object based image analysis of Keti bunder and Kharo chan shows most of the region under low saline soil.Total salt affected soil was measured to be 46,581.7 ha in Keti Bunder, which represents 57.81 % of the total area of 80,566.49 ha. High Saline Area was about 7,944.68 ha (9.86%). Medium Saline Area was about 17,937.26 ha (22.26 %) and low Saline Area was about 20,699.77 ha (25.69%). Where as total salt affected soil was measured to be 52,821.87 ha in Kharo Chann, which represents 55.87 % of the total area of 94,543.54 ha. High Saline Area was about 5,486.55 ha (5.80 %). Medium Saline Area was about 13,354.72 ha (14.13 %) and low Saline Area was about 33980.61 ha (35.94 %). These results show that the area is low to medium saline in nature. Accuracy of the soil salinity map was found to be 83 % with the Kappa co-efficient of 0.77. From this research, it was evident that this area as a whole falls under the category of low to medium saline area and being close to coastal area, mangrove forest can flourish. As Mangroves are salt tolerant plant so this area is consider heaven for mangrove plantation. It would ultimately benefit both the local community and the environment. Increase in mangrove forest control the problem of soil salinity and prevent sea water to intrude more into coastal area. So deforestation of mangrove should be regularly monitored.

Keywords: indus delta, object based image analysis, soil salinity, thematic mapper

Procedia PDF Downloads 616

Authors: Nicolas R. Finkler, Wesley A. Saltarelli, Taison A. Bortolin, Vania E. Schneider, Davi G. F. Cunha

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Estimating the relative contribution of nonpoint or point sources of pollution in low-orders streams is an important tool for the water resources management. The location of headwaters in areas with anthropogenic impacts from urbanization and agriculture is a common scenario in developing countries. This condition can lead to conflicts among different water users and compromise ecosystem services. Water pollution also contributes to exporting organic loads to downstream areas, including higher order rivers. The purpose of this research is to preliminarily assess nutrients and solids loads exported by water bodies located in watersheds with different types of land uses in São Carlos - SP (Latitude. -22.0087; Longitude. -47.8909) and Caxias do Sul - RS (Latitude. -29.1634, Longitude. -51.1796), Brazil, using regression analysis. The variables analyzed in this study were Total Kjeldahl Nitrogen (TKN), Nitrate (NO3-), Total Phosphorus (TP) and Total Suspended Solids (TSS). Data were obtained in October and December 2015 for São Carlos (SC) and in November 2012 and March 2013 for Caxias do Sul (CXS). Such periods had similar weather patterns regarding precipitation and temperature. Altogether, 11 sites were divided into two groups, some classified as more pristine (SC1, SC4, SC5, SC6 and CXS2), with predominance of native forest; and others considered as impacted (SC2, SC3, CXS1, CXS3, CXS4 and CXS5), presenting larger urban and/or agricultural areas. Previous linear regression was applied for data on flow and drainage area of each site (R² = 0.9741), suggesting that the loads to be assessed had a significant relationship with the drainage areas. Thereafter, regression analysis was conducted between the drainage areas and the total loads for the two land use groups. The R² values were 0.070, 0.830, 0.752 e 0.455 respectively for SST, TKN, NO3- and TP loads in the more preserved areas, suggesting that the loads generated by runoff are significant in these locations. However, the respective R² values for sites located in impacted areas were respectively 0.488, 0.054, 0.519 e 0.059 for SST, TKN, NO3- and P loads, indicating a less important relationship between total loads and runoff as compared to the previous scenario. This study suggests three possible conclusions that will be further explored in the full-text article, with more sampling sites and periods: a) In preserved areas, nonpoint sources of pollution are more significant in determining water quality in relation to the studied variables; b) The nutrient (TKN and P) loads in impacted areas may be associated with point sources such as domestic wastewater discharges with inadequate treatment levels; and c) The presence of NO3- in impacted areas can be associated to the runoff, particularly in agricultural areas, where the application of fertilizers is common at certain times of the year.

Keywords: land use, linear regression, point and non-point pollution sources, streams, water resources management

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Authors: Kita R. Ashman, Anthony R. Rendall, Matthew R. E. Symonds, Desley A. Whisson

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Forest cover is decreasing globally, chiefly due to the conversion of forest to agricultural landscapes. In contrast, the area under plantation forestry is increasing significantly. For wildlife occupying landscapes where native forest is the dominant land cover, plantations generally represent a lower value habitat; however, plantations established on land formerly used for pasture may benefit wildlife by providing temporary forest habitat and increasing connectivity. This study investigates the influence of landscape, site, and climatic factors on koala population density in far south-west Victoria where there has been extensive plantation establishment. We conducted koala surveys and habitat characteristic assessments at 72 sites across three habitat types: plantation, native vegetation blocks, and native vegetation strips. We employed a hierarchical modeling framework for estimating abundance and constructed candidate multinomial N-mixture models to identify factors influencing the abundance of koalas. We detected higher mean koala density in plantation sites (0.85 per ha) than in either native block (0.68 per ha) or native strip sites (0.66 per ha). We found five covariates of koala density and using these variables, we spatially modeled koala abundance and discuss factors that are key in determining large-scale distribution and density of koala populations. We provide a distribution map that can be used to identify high priority areas for population management as well as the habitat of high conservation significance for koalas. This information facilitates the linkage of ecological theory with the on-ground implementation of management actions and may guide conservation planning and resource management actions to consider overall landscape configuration as well as the spatial arrangement of plantations adjacent to the remnant forest.

Keywords: abundance modelling, arboreal mammals plantations, wildlife conservation

Procedia PDF Downloads 115

Authors: My Hachem Aouragh, Hind Ragragui, Abdellah El-Hmaidi, Ali Essahlaoui, Abdelhadi El Ouali

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This study investigates soil erosion susceptibility in the Oued Mikkes watershed, located in the Meknes-Fez region of northern Morocco, utilizing advanced techniques such as deep learning algorithms and remote sensing integrated within Geographic Information Systems (GIS). Spanning approximately 1,920 km², the watershed is characterized by a semi-arid Mediterranean climate with irregular rainfall and limited water resources. The waterways within the watershed, especially the Oued Mikkes, are vital for agricultural irrigation and potable water supply. The research assesses the extent of erosion risk upstream of the Sidi Chahed dam while developing a spatial model of soil loss. Several important factors, including topography, land use/land cover, and climate, were analyzed, with data on slope, NDVI, and rainfall erosivity processed using deep learning models (DLNN, CNN, RNN). The results demonstrated excellent predictive performance, with AUC values of 0.92, 0.90, and 0.88 for DLNN, CNN, and RNN, respectively. The resulting susceptibility maps provide critical insights for soil management and conservation strategies, identifying regions at high risk for erosion across 24% of the study area. The most high-risk areas are concentrated on steep slopes, particularly near the Ifrane district and the surrounding mountains, while low-risk areas are located in flatter regions with less rugged topography. The combined use of remote sensing and deep learning offers a powerful tool for accurate erosion risk assessment and resource management in the Mikkes watershed, highlighting the implications of soil erosion on dam siltation and operational efficiency.

Keywords: soil erosion, GIS, remote sensing, deep learning, Mikkes Watershed, Morocco

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