scholarly journals Analysis of Pattern and Extent of Deforestation in Akure Forest Reserve, Ondo State, Nigeria

2019 ◽  
Vol 12 (1-2) ◽  
pp. 1-11
Author(s):  
Isaac Adelakun Gbiri ◽  
Nathaniel Olugbade Adeoye
Keyword(s):  
Anthropogenic Activities ◽  
Remote Sensing Data ◽  
Satellite System ◽  
Optical Remote Sensing ◽  
Human Beings ◽  
Southwestern Nigeria ◽  
Forest Reserve ◽  
Forest Depletion ◽  
Undisturbed Forest ◽  
The Government

Abstract Forest Reserves in Southwestern Nigeria have been threatened by urbanization and anthropogenic activities and the rate of deforestation is not known. This study examined the vegetation characteristics of Akure Forest Reserve using optical remote sensing data. It also assessed the changing pattern in the forest reserve between 1986 and 2017. Global Navigation Satellite System (GNSS) receiver was used to capture the location of the prominent settlements that surrounded the Forest Reserve in order to evaluate their effects on the forest. Landsat TM 1986, Landsat ETM+ 2002 and Landsat OLI_TIRS 2017 with 30m resolution were classified to assess the spatio-temporal changing pattern of the forest reserve. The results showed different composition of vegetation, which include undisturbed forest, secondary regrowth and farmlands. The study further revealed that in 1986, 2002 and 2017, undisturbed forest constituted 63.3%, 32.4% and 32.1% of the entire land area respectively, while secondary regrowth occupied 8.3% in 1986, 9.5% in 2002 and 15.6% in 2017. The farmlands had erratic growth between 1986 and 2017. It was 16.9% in 1986, 22.1% in 2002 and 17.5% in 2017. The bare ground exhibited inconsistency in the coverage. In 1986 the areal extent was 11.5%, when it increased to 36% in 2002 and decreased to 31.9% in 2017. In conclusion, the study revealed the extent of forest depletion at Akure Forest Reserve and it is therefore important that the residents, the government and the researchers show major concern about some of the critical factors to human beings that are responsible for forest depletion.

scholarly journals Human Influences on Tree Diversity and Composition of a Coastal Forest Ecosystem: The Case of Ngumburuni Forest Reserve, Rufiji, Tanzania

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
J. Kimaro ◽  
L. Lulandala
Keyword(s):  
Species Diversity ◽  
Forest Ecosystem ◽  
Anthropogenic Activities ◽  
Coastal Forests ◽  
Useful Plants ◽  
Economic Activities ◽  
Forest Reserve ◽  
Disturbed Areas ◽  
Undisturbed Forest ◽  
Ecological Functioning

This paper reports on the findings of an ecological survey conducted in Ngumburuni Forest Reserve, a biodiversity rich forest reserve within the coastal forests of Tanzania. The main goal of this study was to determine the influence of uncontrolled anthropogenic activities on tree species diversity and composition within the forest ecosystem. It was revealed that economic activities including logging, charcoaling, and shifting cultivation were the most important disturbing activities affecting ecological functioning and biodiversity integrity of the forest. Further to this, we noted that the values of species diversity, composition, and regeneration potential within the undisturbed forest areas were significantly different from those in heavily disturbed areas. These observations confirm that the ongoing human activities have already caused size quality degradation of useful plants, enhanced species diversification impacts to the forest ecosystem, and possibly negatively affected the livelihoods of the adjacent local communities. Despite these disturbances, Ngumburuni forest reserve still holds important proportions of both endemic and threatened animal and plant species. The study suggests urgent implementation of several conservation measures in order to limit accessibility to the forest resources so as to safeguard the richness and abundance of useful biodiversity stocks in the reserve.

Determinants of Trading Decision: An Experiential Examination

GIS Business ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 1-9
Author(s):  
Gunjan Sharma ◽  
Tarika Singh ◽  
Suvijna Awasthi
Keyword(s):  
Stock Market ◽  
Capital Markets ◽  
Capital Market ◽  
Capital Mobility ◽  
Influential Factors ◽  
Herd Behavior ◽  
Human Beings ◽  
The Past ◽  
The Government ◽  
Indian Stock Market

In the midst of increasing globalization, the past two decades have observed huge inflow of outside capital in the shape of direct and portfolio investment. The increase in capital mobility is due to contact between the different economies across the globe. The growing liberalization in the capital market leads to the growth of various financial products and services. Over the past decade, the Indian capital market has witnessed numerous changes in the direction of developing the capital markets more robust. With the growing Indian economy, the larger inflow of funds has been fetched into the capital markets. The government is continuously working on investor’s education in order to increase retail participation in the Indian stock market. The habits of the risk-averse middle class have been changing where these investors started participating in the Indian stock market. It is an explored fact that human beings are irrational and considering this fact becomes imperative to investigate factors that influence the trading decisions. In this research, ‘an attempt has been made to investigate various factors that affect the individual trading decision’. The data has been collected from various stockbroking firms and from clients of those stockbroking firms their opinions were recorded by means of a questionnaire. Data collected through the structured questionnaire, 33 questions were prepared which was given to the 330 respondents on the basis of convenience sampling out of which 220 individuals filled questionnaire, the total of 200 questionnaires was included in the study after eliminating the incomplete questionnaire. Various factors are being explored from the literature and then with the help of factor analysis some of the most influential factors have been explored. Factors like overconfidence, optimism, cognitive bias, herd behavior, advisory effect, and idealism are the factors which influenced the trading decision of the investors the most. Such kind of a study is contributing in the area of behavioral finance as a trading decision is an important aspect while investing in the stock market. And this kind of study would be helping and assisting financial advisors to strategies for their clients in making the right allocation and also the policy maker and market regulators to come up with better reforms for the Indian stock markets.

Provision of Security Services in Public Secondary Schools in Enugu East L.G.A. of Enugu State.

2019 ◽  
pp. 172-176
Author(s):  
Otegbulu M. I. ◽  
Ezeagu A. Agbo ◽  
Agbo Genevieve N.
Keyword(s):  
School Environment ◽  
School Administrators ◽  
Teaching Staff ◽  
Human Beings ◽  
Security Threat ◽  
Culture Of Learning ◽  
Learning And Teaching ◽  
Security Issues ◽  
Security Services ◽  
The Government

Security is pre-requisite for the development of human beings and the society. It is a pre-condition for the survival, development and advancement of individuals and groups. The school is an organization that needs to have a planned safety rules and regulations to protect it components so that the culture of learning and teaching is enhanced. Security threat within the school environment could hamper the peaceful atmosphere in the school, and disrupt academic exercises and panic among the personnel in the school. The government, security agents, parents, school administrators and the community has a lot of role to play to make school environment safe and conducive. However, security gadgets and apparatus should be provided to nip these issues in the bud, as well as train the teaching and non-teaching staff on security issues.

Environmental Degradation in the Ikorodu Sub-Urban Lagos - Lagoon Coastal Environment, Nigeria

2018 ◽  
Vol 10 (1) ◽  
pp. 16-33 ◽  
Author(s):  
Shakirudeen Odunuga ◽  
Samuel Udofia ◽  
Opeyemi Esther Osho ◽  
Olubunmi Adegun
Keyword(s):  
Anthropogenic Activities ◽  
Public Awareness ◽  
Biodiversity Loss ◽  
Policy Formulation ◽  
Coastal Environment ◽  
Resource Exploitation ◽  
Average Growth ◽  
Awareness Campaigns ◽  
The Government ◽  
State Of The Environment

Introduction:Human activities exert great pressures on the environment which in turn cause environmental stresses of various intensities depending on the factors involved and the sensitivity of the receiving environment.Objective:This study examines the effects of anthropogenic activities along the sub-urban lagoon fragile coastal ecosystem using DPSIR framework.Results:The results show that the study area has undergone a tremendous change between 1964 and 2015 with the built up area increasing to about 1,080 ha (17.87%) in 2015 from 224 ha (1.32%) in 1964 at an average growth rate of 16.78ha per annum. The nature of the degradation includes an increasing fragility of the ecosystem through the emergence and expansion of wetlands, flooding and erosion as well as a reduction in the benefits from the ecosystem services. Population growth, between 2006 and 2015 for Ikorodu LGA, estimated at 8.84% per annum serves as the most important driving force in reducing the quality of the environment. This is in addition to Pressures emanating from anthropogenic activities. The state of the environment shows continuous resource exploitation (fishing and sand mining) with the impacts of the pressures coming from water pollution, bank erosion, biodiversity loss and flooding. Although there has been a strong policy formulation response from the government, weak implementation is a major challenge.Recommendation:The study recommends public awareness campaigns and the implementation of existing policies to ensure a sustainable sub-urban lagoon coastal environment..

Water Pollution and Its Impact on Environment of Society

2016 ◽  
Vol 3 (5) ◽  
Author(s):  
N. Thyagaraju
Keyword(s):  
Water Pollution ◽  
Pollution Prevention ◽  
Human Beings ◽  
Individual Level ◽  
The Public ◽  
The Government ◽  
Living Organisms ◽  
Set Up ◽  
Biological Entities ◽  
Micro Organisms

The present seminar paper mainly highlight  the concept of  water pollution, causes of water pollution,  Its Effects, Elements of  pollutants, Methods  used to prevent the water pollution in environment  and the mandatory initiatives taken by the concerned authorities for prevention of  water pollution. Water   is essential for survival of all living organisms on the earth. Thus for human beings and plants to survive on land, water should be easily accessible. The term “Pollution” is generally refers to addition of any foreign body either living or non – living or deletion of anything that naturally exists. The basic Sources of Water pollution causes due to Culmination into lakes, rivers, ponds, seas, oceans etc. Domestic drainage and sanitary waste, Industrial drainage and sewage, Industrial waste from factories, Dumping of domestic garbage, Immersion of Idols made of plaster of Paris, Excess use of Insecticides , pesticides, fungicides, Chemical fertilizers, Soil erosion during heavy rains and floods, Natural disasters, tsunami etc. General pollutants  which are also caused for water pollution  which include Organic, Inorganic, and Biological entities, Insecticides, Pesticides, Disinfectants ,Detergents, Industrial solvents, Acids, Ammonia fertilizers, heavy metals, Harmful bacteria, Virus, Micro –Organisms and worms, Toxic chemicals. Agricultural lands become infertile and thereby production also drops, Spread of epidemic diseases like Cholera, Dysentery, Typhoid, Diarrhea, Hepatitis, Jaundice etc. The  basic responsibility of the Government, NGOs, National Pioneer scientific Research Institutions may conduct  research oriented programs on control of water pollution by create  awareness among the public through mass media and Environmental Education on recycling units,  and  water treatment plants must be established both at domestic levels and Industry levels, Every citizen must feel responsible to control water pollution. There have been many water pollution prevention acts that have been set up by the governments of the world. But these are not enough for permanent water pollution solutions. Each of us needs to take up the responsibility and do something at an everyday at individual level. Otherwise we can’t survive in a society forever in a future. 

scholarly journals An Improved Segmentation Method for Automatic Mapping of Cone Karst from Remote Sensing Data Based on DeepLab V3+ Model

2021 ◽  
Vol 13 (3) ◽  
pp. 441
Author(s):  
Han Fu ◽  
Bihong Fu ◽  
Pilong Shi
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Guizhou Province ◽  
Training Dataset ◽  
Optical Remote Sensing ◽  
Remote Sensing Images ◽  
Karst Landscape ◽  
Heritage Site ◽  
Training Samples ◽  
Input Module

The South China Karst, a United Nations Educational, Scientific and Cultural Organization (UNESCO) natural heritage site, is one of the world’s most spectacular examples of humid tropical to subtropical karst landscapes. The Libo cone karst in the southern Guizhou Province is considered as the world reference site for these types of karst, forming a distinctive and beautiful landscape. Geomorphic information and spatial distribution of cone karst is essential for conservation and management for Libo heritage site. In this study, a deep learning (DL) method based on DeepLab V3+ network was proposed to document the cone karst landscape in Libo by multi-source data, including optical remote sensing images and digital elevation model (DEM) data. The training samples were generated by using Landsat remote sensing images and their combination with satellite derived DEM data. Each group of training dataset contains 898 samples. The input module of DeepLab V3+ network was improved to accept four-channel input data, i.e., combination of Landsat RGB images and DEM data. Our results suggest that the mean intersection over union (MIoU) using the four-channel data as training samples by a new DL-based pixel-level image segmentation approach is the highest, which can reach 95.5%. The proposed method can accomplish automatic extraction of cone karst landscape by self-learning of deep neural network, and therefore it can also provide a powerful and automatic tool for documenting other type of geological landscapes worldwide.

scholarly journals Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India

2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Praveen Kumar ◽  
Akhouri P. Krishna ◽  
Thorkild M. Rasmussen ◽  
Mahendra K. Pal
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Test Site ◽  
Forest Area ◽  
Relational Model ◽  
Biomass Estimation ◽  
Optical Remote Sensing ◽  
Ground Sample ◽  
Sensing Data

Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.

scholarly journals Some Peculiarities of Arable Soil Organic Matter Detection Using Optical Remote Sensing Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2313
Author(s):  
Elena Prudnikova ◽  
Igor Savin
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Spectral Reflectance ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Optical Remote Sensing ◽  
Test Field ◽  
Sensing Data ◽  
Sentinel 2

Optical remote sensing only provides information about the very thin surface layer of soil. Rainfall splash alters soil surface properties and its spectral reflectance. We analyzed the impact of rainfall on the success of soil organic matter (SOM) content (% by mass) detection and mapping based on optical remote sensing data. The subject of the study was the arable soils of a test field located in the Tula region (Russia), their spectral reflectance, and Sentinel-2 data. Our research demonstrated that rainfall negatively affects the accuracy of SOM predictions based on Sentinel-2 data. Depending on the average precipitation per day, the R2cv of models varied from 0.67 to 0.72, RMSEcv from 0.64 to 1.1% and RPIQ from 1.4 to 2.3. The incorporation of information on the soil surface state in the model resulted in an increase in accuracy of SOM content detection based on Sentinel-2 data: the R2cv of the models increased up to 0.78 to 0.84, the RMSEcv decreased to 0.61 to 0.71%, and the RPIQ increased to 2.1 to 2.4. Further studies are necessary to identify how the SOM content and composition of the soil surface change under the influence of rainfall for other soils, and to determine the relationships between rainfall-induced SOM changes and soil surface spectral reflectance.

scholarly journals Assessment of Impacts of Hurricane Katrina on Net Primary Productivity in Mississippi

2010 ◽  
Vol 14 (14) ◽  
pp. 1-12 ◽  
Author(s):  
Shrinidhi Ambinakudige ◽  
Sami Khanal
Keyword(s):  
Natural Disasters ◽  
Hurricane Katrina ◽  
Primary Productivity ◽  
Atmospheric Carbon Dioxide ◽  
Net Primary Productivity ◽  
Gulf Coast ◽  
Carbon Sink ◽  
Anthropogenic Activities ◽  
Remote Sensing Data ◽  
The United States

Abstract Southern forests contribute significantly to the carbon sink for the atmospheric carbon dioxide (CO2) associated with the anthropogenic activities in the United States. Natural disasters like hurricanes are constantly threatening these forests. Hurricane winds can have a destructive impact on natural vegetation and can adversely impact net primary productivity (NPP). Hurricane Katrina (23–30 August 2005), one of the most destructive natural disasters in history, has affected the ecological balance of the Gulf Coast. This study analyzed the impacts of different categories of sustained winds of Hurricane Katrina on NPP in Mississippi. The study used the Carnegie–Ames–Stanford Approach (CASA) model to estimate NPP by using remote sensing data. The results indicated that NPP decreased by 14% in the areas hard hit by category 3 winds and by 1% in the areas hit by category 2 winds. However, there was an overall increase in NPP, from 2005 to 2006 by 0.60 Tg of carbon, in Mississippi. The authors found that Pearl River, Stone, Hancock, Jackson, and Harrison counties in Mississippi faced significant depletion of NPP because of Hurricane Katrina.

Remote sensing and GIS forest landscape assessment for sustainable forest management

2021 ◽  
Vol 17 (1) ◽  
pp. 12-26
Author(s):  
A.F. Chukwuka ◽  
A. Alo ◽  
O.J. Aigbokhan
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Markov Chain Model ◽  
Remote Sensing Data ◽  
Chain Model ◽  
Spatial Metrics ◽  
Forest Reserve ◽  
Land Cover Types

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment. Keyword: Landscape, Spatial metrics, sustainable forest and Environment

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