scholarly journals Analysis of Land use and Land cover Characteristics of Kanke, Pankshin, and Langtang Local Government Areas, Plateau State, Nigeria

2020 ◽  
Vol 3 (3a) ◽  
pp. 53-67
Author(s):  
YA Andesikuteb ◽  
WW Musa ◽  
LV Ezra ◽  
MT Obasi ◽  
RG Rogers ◽  
...  
Keyword(s):  
Local Government ◽  
Land Cover ◽  
Large Scale ◽  
Survey Design ◽  
Adaptation Strategy ◽  
Primary Data ◽  
Rock Outcrops ◽  
Plateau State ◽  
Productive Land

This study assessed landuse and landcover changes and how they affect the agrarian production in Kanke, Pankshin and Langtang North Local Government Areas of plateau state, Nigeria. The study adopted the survey design. The primary data was obtained through field observations, interview of stakeholders, satellite (landsat8 and shuttle radar terrain mission) and questionnaire administration which asked questions on socioeconomic status of respondents, constraints to farmers and the respondents’ perception on the existing adaptation strategies in place. ArcGIS10.6version software was employed for the classification of land cover types while supervised classification method was adopted using maximum likelihood algorithm for the classification of feature types. Data generated by Landsat8 and ArcGIS10.6 version software were subjected to Pan-Sharpening processing for clarity of terrain features. The study findings revealed that 66.13% of the earth’s surface in the study area is covered by rock outcrops while water body; one of man’s most precious resources occupied less than 1% (0.15%). The distribution of farmers based on constraints to farming indicated that poor soils and small farm land sizes constituted the most severe challenges to farming activities in the study area. As an adaptation strategy to inadequate farm lands, terrace farming practice and dry season farming, large scale quarrying activities is recommended to serve as a source of employment and income to authorities and a means of surface leveling to convert the dominant rock outcrops to productive land and prioritizing farming in the limited plains.

scholarly journals Land Cover Classification of Nine Perennial Crops Using Sentinel-1 and -2 Data

2019 ◽  
Vol 12 (1) ◽  
pp. 96 ◽  
Author(s):  
James Brinkhoff ◽  
Justin Vardanega ◽  
Andrew J. Robson
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Satellite Image ◽  
Resource Planning ◽  
Support Vector ◽  
Perennial Crop ◽  
Perennial Crops ◽  
Object Based ◽  
Rbf Kernel

Land cover mapping of intensive cropping areas facilitates an enhanced regional response to biosecurity threats and to natural disasters such as drought and flooding. Such maps also provide information for natural resource planning and analysis of the temporal and spatial trends in crop distribution and gross production. In this work, 10 meter resolution land cover maps were generated over a 6200 km2 area of the Riverina region in New South Wales (NSW), Australia, with a focus on locating the most important perennial crops in the region. The maps discriminated between 12 classes, including nine perennial crop classes. A satellite image time series (SITS) of freely available Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imagery was used. A segmentation technique grouped spectrally similar adjacent pixels together, to enable object-based image analysis (OBIA). K-means unsupervised clustering was used to filter training points and classify some map areas, which improved supervised classification of the remaining areas. The support vector machine (SVM) supervised classifier with radial basis function (RBF) kernel gave the best results among several algorithms trialled. The accuracies of maps generated using several combinations of the multispectral and radar bands were compared to assess the relative value of each combination. An object-based post classification refinement step was developed, enabling optimization of the tradeoff between producers’ accuracy and users’ accuracy. Accuracy was assessed against randomly sampled segments, and the final map achieved an overall count-based accuracy of 84.8% and area-weighted accuracy of 90.9%. Producers’ accuracies for the perennial crop classes ranged from 78 to 100%, and users’ accuracies ranged from 63 to 100%. This work develops methods to generate detailed and large-scale maps that accurately discriminate between many perennial crops and can be updated frequently.

COMPARATIVE ALLOCATIVE EFFICIENCY AND PROFITABILITY OF DIFFERENT SCALES OF POULTRY-EGG PRODUCTION IN JOS METROPOLIS, PLATEAU STATE, NIGERIA

2021 ◽  
Vol 4 (4) ◽  
pp. 259-273
Author(s):  
Solomon T. Folorunso ◽  
T. Omosebi ◽  
D. A. Agbonika
Keyword(s):  
Egg Production ◽  
Large Scale ◽  
Allocative Efficiency ◽  
Sampling Technique ◽  
Primary Data ◽  
Small Scale ◽  
Stochastic Production Frontier ◽  
Stochastic Production ◽  
Plateau State ◽  
The Government

The study compared the allocative efficiency and profitability of poultry-egg farmers in Jos metropolis of Plateau State, Nigeria, across different scales. To select 143 respondents, a two-stage sampling technique was used.   Using well-structured questionnaire and interview schedules, primary data on socioeconomic variables were collected. Collected data were analyzed using budgetary technique and stochastic production frontier model. Result of allocative efficiency showed the following: The mean allocative efficiency of the small, medium and large scales was 0.68, 0.12 and 0.11 respectively; the minimum allocative efficiency for small, medium and large scales was 0.30, 0.10 and 0.10 respectively. The maximum allocative efficiency was 0.59, 0.18 and 0.11 respectively for small, medium and large scale farmers. The profitability result indicated that egg production for small, medium and large-scale farms was profitable in the study area with N675, 671.79, N4, 897,236.09 and N16, 327,633.66 per farmer. The rate of return on investment per bird was found to be 19.51%, 31.21% and 83.13% respectively for small, medium and large farm sizes. For small, medium and large-scale farmers respectively, the capital turnover per bird was N 1.20, N1.31 and N1.83. Also, the profitability indices for the small, medium and large scales are N0.16, N0.24 and N0.45. The study recommends that; Farmers should be advised to increase production from small scale to large scale through policies that will promote such, special intervention is needed from the government at all levels through farmers’ cooperatives in the area of inputs subsidy, price efficiency of the farmers could

scholarly journals Geo-spatial Assessment of Land Use/Land Cover (LU/LC) Dynamics in Akoko South West Local Government, Ondo State, Nigeria

2021 ◽  
pp. 46-54
Author(s):  
Dada Ibilewa ◽  
Mustapha Aliyu ◽  
Usman O. Alalu ◽  
Taiwo Hassan Abdulrasheed
Keyword(s):  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Landsat Images ◽  
Rock Outcrops ◽  
Forest Reserve ◽  
Spatial Assessment ◽  
South West ◽  
Moderate Change ◽  
Microsoft Office

Geo-spatial assessment of land use/cover dynamics in Akoko South West Local Government was instigated to bridge the knowledge gap created by data deficiency on the nature, scope and magnitude of land use/cover change in the area. This was done through the analysis of Landsat images of three epochs from 2000 through 2010 to 2020. The processing of the satellite images was done in ArcGIS 10.8 while the analysis and 2030 projection was done in Microsoft office excel using the result from the analysis. QGIS was used to remove the scan lines error on the 2010 image. The result showed increasing built-up area, reducing vegetation and farmlands and diminishing rock outcrops. The changes vary among the different classification characteristics. The increasing change in the second epoch was higher in built up areas while rock outcrops increased in the first epoch. Farmland and vegetation were on reducing trend throughout the study period. However, the moderate change observed in the second epoch for the two land cover classes were not as significant as the first epoch. Government policies on forest reserve should strictly be adhered to in order to preserve the vegetation in the area. People of the area should be advised to diversify their economy in order to avoid total dependence on the forest reserve.

scholarly journals Cost and Returns Analysis of Groundnut Production in Qua’an Pan Local Government Area of Plateau State, Nigeria

2020 ◽  
pp. 31-40
Author(s):  
A. A. Dalla ◽  
S. K. Vihi ◽  
B. Jesse ◽  
L. G. Tor
Keyword(s):  
Local Government ◽  
Land Tenure ◽  
Function Analysis ◽  
Local Government Area ◽  
Farm Size ◽  
Primary Data ◽  
Farm Income ◽  
Selling Price ◽  
Gross Margin ◽  
Plateau State

This study assessed cost and returns analysis of groundnut production in Qua’an Pan Local Government Area of Plateau State, Nigeria. The specific objectives were to determine the socio economic characteristics of groundnut producers in the study area, estimate the cost and returns of groundnut production, determine the input and output relationship in groundnut production and identify the constraints faced by groundnut farmers in the study area. Multistage sampling technique was used in selecting 150 respondents for the study. Primary data were collected through the use of structured questionnaires and interview technique and were subjected to both descriptive and inferential statistics. The results obtained from the study revealed that the mean age of the respondents was 38 years with males dominating (82%) the groundnut production enterprise in the study area. Greater (85%) percentages of respondents were married with majority (64%) of them having primary school education. The respondents had an average household size of nine (9) persons, a mean farming experience of 9.3 years and an average farm size of 3.0 hectares. The result also revealed that majority (72%) of the respondents did not belong to any cooperative/ farming association. The result indicates that majority (79%) of the groundnut farmers acquired their farmland by inheritance. Groundnut production in the study area is profitable. The average output obtained per hectare was 696 kg at the prevailing selling price of ₦280/kg. The total revenue (TR), gross margin (GM) and, net farm income (NFI) per hectare obtained were ₦194880, ₦139380 and ₦123730 respectively. The return on naira invested (RNI) by farmers in the study area was ₦1.70 indicating that for every one naira invested, ₦1.70 profit was gained. The result of the double log production function analysis shows that farm size, cost of fertilizer and cost of labour were statistically significant and influenced the profitability of groundnut production.  Major constraints to groundnut production in the study area include; high cost of inputs (64 %), high cost of labour (49 %), lack of organized market system (47%), land tenure (42%) among others. The study recommends that groundnut stakeholders and research institutes should work more on introducing new improved groundnut varieties. Government should subsidize groundnut inputs like recommended fertilizer and herbicides so as to motivate farmers to grow groundnut. Government should establish organized marketing systems where farmers will have proper and reliable linkages with buyers thereby reducing the undue exploitative tendencies of the middlemen.  Improved storage facilities should be provided so that farmers could store their produce to avoid spoilage and for sale during times of scarcity.

scholarly journals Long-term vegetation monitoring in Great Britain – the Countryside Survey 1978–2007 and beyond

2017 ◽  
Vol 9 (2) ◽  
pp. 445-459 ◽  
Author(s):  
Claire M. Wood ◽  
Simon M. Smart ◽  
Robert G. H. Bunce ◽  
Lisa R. Norton ◽  
Lindsay C. Maskell ◽  
...  
Keyword(s):  
Great Britain ◽  
Land Cover ◽  
Survey Design ◽  
Ecological Data ◽  
Vegetation Monitoring ◽  
Environmental Classification ◽  
Freshwater Habitats ◽  
Vegetation Surveys

Abstract. The Countryside Survey (CS) of Great Britain provides a globally unique series of datasets, consisting of an extensive set of repeated ecological measurements at a national scale, covering a time span of 29 years. CS was first undertaken in 1978 to monitor ecological and land use change in Britain using standardised procedures for recording ecological data from representative 1 km squares throughout the country. The same sites, with some additional squares, were used for subsequent surveys of vegetation undertaken in 1990, 1998 and 2007, with the intention of future surveys. Other data records include soils, freshwater habitats and invertebrates, and land cover and landscape feature diversity and extents. These data have been recorded in the same locations on analogous dates. However, the present paper describes only the details of the vegetation surveys. The survey design is a series of gridded, stratified, randomly selected 1 km squares taken as representative of classes derived from a statistical environmental classification of Britain. In the 1978 survey, 256 one-kilometre sample squares were recorded, increasing to 506 in 1990, 569 in 1998 and 591 in 2007. Initially each square contained up to 11 dispersed vegetation plots but additional plots were later placed in different features so that eventually up to 36 additional sampling plots were recorded, all of which can be relocated where possible (unless the plot has been lost, for example as a consequence of building work), providing a total of 16 992 plots by 2007. Plots are estimated to have a precise relocation accuracy of 85 %. A range of plots located in different land cover types and landscape features (for example, field boundaries) are included. Although a range of analyses have already been carried out, with changes in the vegetation being related to a range of drivers at local and national scales, there is major potential for further analyses, for example in relation to climate change. Although the precise locations of the plots are restricted, largely for reasons of landowner confidentiality, sample sites are intended to be representative of larger areas, and many potential opportunities for further analyses remain. Data from each of the survey years (1978, 1990, 1998, 2007) are available via the following DOIs: Countryside Survey 1978 vegetation plot data (https://doi.org/10.5285/67bbfabb-d981-4ced-b7e7-225205de9c96), Countryside Survey 1990 vegetation plot data (https://doi.org/10.5285/26e79792-5ffc-4116-9ac7-72193dd7f191), Countryside Survey 1998 vegetation plot data (https://doi.org/10.5285/07896bb2-7078-468c-b56d-fb8b41d47065), Countryside Survey 2007 vegetation plot data (https://doi.org/10.5285/57f97915-8ff1-473b-8c77-2564cbd747bc).

scholarly journals Identification of Potential Zones for Solid Waste Disposal in Jos South Local Government Area of Plateau State, Nigeria

2021 ◽  
pp. 21-32
Author(s):  
Kulokom Stephen ◽  
Balogun Bolarinwa Olutayo ◽  
Fagbeja Mofoluso
Keyword(s):  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Waste Disposal ◽  
Secondary Data ◽  
Land Use Land Cover ◽  
Solid Waste Disposal ◽  
Plateau State

Disposal is a critical phase in the management of municipal solid waste, due to unavailability of suitable facilities to treat and dispose of the large amount of municipal solid waste generated daily in metropolitan cities. Improper municipal solid waste disposal locally, cause environmental impacts such as contamination of soil, water pollution, and increase methane emissions. In this study, an attempt has been made to use GIS and remote sensing to identify high potential zones for solid waste disposal in Jos South Local Government Area of Plateau State between 2019 and 2020. Primary data and secondary data were used for this study. The position data of the existing dumpsites in the study area were acquired in-situ with a handheld Global Positioning System (GPS) receiver. The secondary data consists of NigeriaSAT-X, geological, administrative maps, Google map, hydro-geophysical data and Shuttle Radar Topographic Mission (SRTM) images. Thematic layers considered in this study include drainage, road and land use/land cover, lithology and geology. The dumpsite point (X, Y) was imported as shapefile and superimposed on the study area boundary to show the existing location. Digital image segmentation of NigeriaSAT-X and geology dataset was carried out to derive the land use/ land cover and geology classifications of the study area. Lithological analysis was carried out using Kriging Method to interpolate the hydro-geophysical data. The slope, land/use, geology, drainage, road, waterbody, built-up and lithology were reclassified and overlaid using Weighted Sum Overlay Method a Spatial Analyst tool in ArcGIS 10.4 to generate the potential zones for solid waste disposal. The result shows the potential zones for solid waste disposal and characterized into unsuitable, less suitable, moderately suitable, suitable and highly suitable.

scholarly journals Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning

2020 ◽  
Author(s):  
Zhongling Huang
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Transfer Learning ◽  
Large Scale ◽  
Target Area ◽  
Sar Images ◽  
Label Noise ◽  
Deep Model ◽  
Imbalanced Classes

<div> <div> <div> <p>The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with expertise, changing data characteristics due to varying imaging parameters or regional target area differences, and complex scattering mechanisms being different from optical imaging. Given a large-scale SAR land cover dataset collected from TerraSAR-X images with a hierarchical three-level annotation of 150 categories and comprising more than 100,000 patches, three main challenges in automatically interpreting SAR images of highly imbalanced classes, geographic diversity, and label noise are addressed. In this letter, a deep transfer learning method is proposed based on a similarly annotated optical land cover dataset (NWPU-RESISC45). Besides, a top-2 smooth loss function with cost-sensitive parameters was introduced to tackle the label noise and imbalanced classes’ problems. The proposed method shows high efficiency in transferring information from a similarly annotated remote sensing dataset, a robust performance on highly imbalanced classes, and is alleviating the over-fitting problem caused by label noise. What’s more, the learned deep model has a good generalization for other SAR-specific tasks, such as MSTAR target recognition with a state-of-the-art classification accuracy of 99.46%. </p> </div> </div> </div>

scholarly journals Urban Growth and Its Impact on Urban Land Cover Change in Akure South Local Government, Ondo State, Nigeria

2021 ◽  
pp. 32-40
Author(s):  
Dada Ibilewa ◽  
Mustapha Aliyu ◽  
Usman O. Alalu ◽  
Taiwo Hassan Abdulrasheed
Keyword(s):  
Local Government ◽  
Land Cover ◽  
Land Cover Change ◽  
Urban Growth ◽  
Agricultural Land ◽  
Urban Land ◽  
Landsat Images ◽  
Rock Outcrops ◽  
Urban Land Cover ◽  
Urban Land Cover Change

Urban Growth and its Impact on Urban land cover change in Akure South Local Government area was investigated to bridge the knowledge gap created by data deficiency on the nature, scope, and magnitude of urban threat on the land use/land cover type, most especially the agricultural land in the area. This was done through the analysis of Landsat images of three epochs from 2000 through 2010 to 2020. The processing of the satellite images was done in ArcGIS 10.8, while the analysis and 2030 projection were done in Microsoft office excel using the result from the analysis. QGIS was used to remove the scan lines error on the 2010 image. The result showed increasing urban growth (built-up area), reducing vegetation and farmlands, and increasing rock outcrops. The changes vary among the different classification characteristics. Both farmlands and vegetation increased in the first epoch and reduced in the second epoch due to man's urbanization and other socio-economic activities. The increasing change in the second epoch was higher in built-up areas while rock outcrops increased throughout the study period. The research was able to assess the magnitude of farmland and vegetation that have been converted for urban uses over time. It also proved the efficiency of Remote Sensing and GIS technology in urban growth studies.

scholarly journals Prairie Gardening

2012 ◽  
pp. 21-44
Author(s):  
Katherine Taylor
Keyword(s):  
Large Scale ◽  
Primary Data ◽  
Prairie Restoration ◽  
Ecological Features ◽  
Native North American ◽  
Wide Range ◽  
The Usa ◽  
The Uk ◽  
North American Prairie

The paper attempts to unpick the real meaning of the term ‘prairie gardening’ and to explore its popularity in a European context. Establishment and maintenance techniques are also considered. The term is, however, applied without discrimination to a wide range of styles, from large-scale traditional prairie restoration or re-creation projects through to highly stylised prairie interpretations. Research included a literature review to assess the main ecological features of, and threats to, native North American Prairie and an examination of the origins of contemporary ‘prairie gardening’ in both the USA and Europe. Primary data was gathered from eight UK gardens associated with this planting style. The evidence suggests that the spectrum of styles encompassed by this term is broad even within the UK, a clear indication that its usage is over-simplistic and potentially ambiguous. The author offers her own classification of the genre under the umbrella term ‘prairie-style gardening’ in the hope of further clarification. The paper is a summary of a project which was carried out as part of the second-year project of the HND in Horticulture with Plantsmanship at Royal Botanic Garden Edinburgh.

Large-Scale Classification of Land Cover Using Retrospective Satellite Data

2016 ◽  
Vol 52 (1) ◽  
pp. 127-138 ◽  
Author(s):  
M. S. Lavreniuk ◽  
S. V. Skakun ◽  
A. Ju. Shelestov ◽  
B. Ya. Yalimov ◽  
S. L. Yanchevskii ◽  
...  
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Large Scale ◽  
Scale Classification
Sign in / Sign up

Export Citation Format

Share Document