Geospatial Analysis of Agriculture Land Loss in Qena City, Upper Egypt

2021 ◽  
Vol 12 (4) ◽  
pp. 40-57
Author(s):  
Mostafa Kamal Kamel Mosleh ◽  
Khaled Mohmmad Amin Hazaymeh
Keyword(s):  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Loss ◽  
Landsat Images ◽  
Index Set ◽  
Upper Egypt ◽  
Agriculture Land ◽  
Local Decision

Although urbanization presents opportunities for new urban developments, it may have serious problems on environment and land use/cover patterns. The present study aims to evaluate the performance of built‑up delineation index set (BDIS) for mapping agricultural land loss in Upper Egypt. Three Landsat images were obtained for the years 1986, 2000, and 2016 and utilized as inputs to calculate the BDIS variables. Then a supervised classification technique (i.e., support vector machine) was used to classify the images. The findings showed that urban areas have witnessed a dramatic expansion at a growing rate of 44.1% during the 30 years. As a result, the loss of the agricultural land was found to be approximately 64.83 ha, which represents -4%, during the same period because of the urban expansion and the illegal construction of settlements. These findings would support the local decision makers in urban and agriculture land management authorities to develop sustainable development plans that control the spatiotemporal urban expansion and agricultural land loss.

scholarly journals Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

2021 ◽  
Vol 13 (16) ◽  
pp. 3337
Author(s):  
Shaker Ul Din ◽  
Hugo Wai Leung Mak
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

scholarly journals AGRICULTURAL LAND USE CHANGE ANALYSIS USING REMOTE SENSING AND GIS: A CASE STUDY OF ALLAHABAD, INDIA

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 397-402 ◽  
Author(s):  
V. Kumar ◽  
S. Agrawal
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Areas ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Research Work ◽  
Landsat Images ◽  
Change Analysis ◽  
Statistical Research ◽  
Agriculture Land

<p><strong>Abstract.</strong> Urbanization is occurring at a fast rate in India. Population residing in urban areas was 11.4% according to the Census of 1901. This percentage has gradually increased to 31.16% according to the Census of 2011. Conversion of agricultural land into non-agricultural uses is the major side effect of urbanization. The objective of this paper is to identify the changes in the agriculture land and its conversion into other Land Use Land Cover (LULC) type. In order to achieve this objective, mapping of land use changes is done by using the GIS and remote sensing. This study utilizes satellite images along with field survey and statistical data to detect the change of farming land into other LULC type in different tehsils of Allahabad district. This study is carried out over the time period of 18 years that ranges from 2000 to 2018. This work provides the detail of expansion and shrinkage of agriculture and open land at tehsil level. Landsat data is used in this work which is open source and freely downloadable. Landsat images of study period i.e. from 2000 to 2018 are downloaded and then preprocessed. Supervised classification of images is performed using Gaussian maximum likelihood technique. The training samples are collected with the help of ground truth information. After this, identification of land use changes is done on pixel by pixel basis. This would find out the LULC class which is primary responsible for the shrinkage of agriculture land. This spatio-temporal and statistical research work will help to construct a base for a sustainable development model.</p>

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

Land Loss with Compensation: What Are the Determinants of Income Among Households in Central Vietnam?

2021 ◽  
Vol 12 (1) ◽  
pp. 40-55
Author(s):  
Nguyen Quang Phuc ◽  
A. C. M. (Guus) van Westen ◽  
Annelies Zoomers
Keyword(s):  
Household Income ◽  
Urban Areas ◽  
Urban Expansion ◽  
Skill Training ◽  
Land Loss ◽  
Central Vietnam ◽  
Compensation Packages ◽  
Household Members ◽  
The Government ◽  
Using Data

The purpose of this study is to investigate the determinants of household income following the loss of land owing to urban expansion in central Vietnam. Using data mainly from household surveys in the peri-urban areas of Hue city, the regression model indicates that demographic factors and livelihood strategy choices have important impacts on household income; financial compensation and support packages do not appear to be strong determinants of household income after the loss of land. This implies a failure of the current compensation programmes in the process of compulsory land acquisition, because the government believes that compensation packages make important contributions to livelihood reconstruction. This study suggests that investing in education and skill training for household members affected by land loss as well as assistance in converting compensation money into an adequate livelihood should be taken into consideration.

scholarly journals The impact of urbanization expansion on agricultural land in Ethiopia: A review

2020 ◽  
Vol 8 (4) ◽  
pp. 73-80
Author(s):  
Assefa Ayele ◽  
Kassa Tarekegn
Keyword(s):  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Rural Livelihoods ◽  
Vital Role ◽  
Rapid Urbanization ◽  
Economic Resource ◽  
House Construction ◽  
Impact Of Urbanization ◽  
The Impact

AbstractIn a country like Ethiopia where the vast majority of the populations are employed in agriculture, land is an important economic resource for the development of rural livelihoods. Agricultural land in peri-urban areas is, however, transformed into built-up regions through horizontal urban expansion that has an effect on land use value. In recent years Ethiopia has been experiencing rapid urbanization, which has led to an ever-increasing demand for land in peri-urban areas for housing and other nonagricultural activities that pervades agricultural land. There is a high demand for informal and illegal peri-urban land which has been held by peri-urban farmers, and this plays a vital role in the unauthorized and sub-standard house construction on agricultural land. This urbanization has not been extensively reviewed and documented. In this review an attempt has been made to assess the impacts of rapid urbanization on agricultural activities. Urban expansion has reduced the areas available for agriculture, which has seriously impacted upon peri-urban farmers that are often left with little or no land to cultivate and which has increased their vulnerability. Housing encroachments have been observed to be uncontrolled due to a weak government response to the trend of unplanned city expansion. This has left peri-urban farmers exposed to the negative shocks of urbanization because significant urbanization-related agricultural land loss has a positive correlation with grain production decrease. Appropriate governing bodies should control urban development in order to control the illegal and informal spread of urbanization on agricultural land that threatens food production.

scholarly journals Land Use Dynamics and Variations in Sprawl across Municipalities in the Bamenda Urban-scape from 1996-2018

2020 ◽  
Vol 13 (4) ◽  
pp. 224
Author(s):  
Fombe Lawrence F. ◽  
Acha Mildred E.
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Urban Areas ◽  
Agricultural Land ◽  
Pearson Correlation ◽  
Town Planning ◽  
Land Values ◽  
Landsat Images ◽  
Land Use Dynamics ◽  
Spatiotemporal Analyses

Worldwide urban areas are having increasing influence over the surrounding landscape. Peri-urban regions of the world are facing challenges which results from sprawl with increasing problems of social segregation, wasted land and greater distance to work. This study seeks to examine the trends in land use dynamics, urban sprawl and associated development implications in the Bamenda Municipalities from 1996 to 2018. The study made use of the survey, historical and correlational research designs. The purposive and snowball techniques were used to collect data. Spatiotemporal analyses were carried out on Landsat Images for 1996, 2008, and 2018 obtained from Earth Explorer, Erdas Image 2014 and changes detected from the maps digitized. The SPSS version 21 and MS Excel 2016 were used to analyze quantitative and qualitative data. The former employed the Pearson correlation analysis. Analysis of land use/land cover change detection reveals that built-up area has increased significantly from 1996 to 2018 at the detriment of forest, wetland and agricultural land at different rates within each municipality. These changes have led to invasion of risk zones, high land values, uncoordinated, uncontrolled and unplanned urban growth. The study suggests that proactive planning, use of GIS to monitor land use activities, effective implementation of existing town planning norms and building regulations, are invaluable strategies to sustainably manage urban growth in Bamenda.

Quantifying Urban Sprawl With Spatial Autocorrelation Techniques Using Multi-Temporal Satellite Data

2019 ◽  
pp. 1624-1644
Author(s):  
Gabriele Nolè ◽  
Rosa Lasaponara ◽  
Antonio Lanorte ◽  
Beniamino Murgante
Keyword(s):  
Remote Sensing ◽  
Spatial Autocorrelation ◽  
Urban Areas ◽  
Urban Expansion ◽  
Data Sets ◽  
Temporal Data ◽  
Landsat Images ◽  
Urban Settlements ◽  
Multi Temporal ◽  
Soil Consumption

This study deals with the use of satellite TM multi-temporal data coupled with statistical analyses to quantitatively estimate urban expansion and soil consumption for small towns in southern Italy. The investigated area is close to Bari and was selected because highly representative for Italian urban areas. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and geospatial data analysis to reveal spatial patterns. Analyses have been carried out using global and local spatial autocorrelation, applied to multi-date NASA Landsat images acquired in 1999 and 2009 and available free of charge. Moreover, in this paper each step of data processing has been carried out using free or open source software tools, such as, operating system (Linux Ubuntu), GIS software (GRASS GIS and Quantum GIS) and software for statistical analysis of data (R). This aspect is very important, since it puts no limits and allows everybody to carry out spatial analyses on remote sensing data. This approach can be very useful to assess and map land cover change and soil degradation, even for small urbanized areas, as in the case of Italy, where recently an increasing number of devastating flash floods have been recorded. These events have been mainly linked to urban expansion and soil consumption and have caused loss of human lives along with enormous damages to urban settlements, bridges, roads, agricultural activities, etc. In these cases, remote sensing can provide reliable operational low cost tools to assess, quantify and map risk areas.

Detection of Urban Expansion by Using DMSP-OLS, Landsat Data and Linear Spectral Unmixing Method

2019 ◽  
pp. 1372-1382
Author(s):  
Cihan Uysal ◽  
Derya Maktav
Keyword(s):  
Urban Growth ◽  
Urban Areas ◽  
Urban Expansion ◽  
Dynamic Structure ◽  
Spectral Unmixing ◽  
Landsat Images ◽  
Green Vegetation ◽  
Linear Mixture Model ◽  
Linear Spectral Unmixing ◽  
Spectral Mixture

Urbanization has been increasingly continuing in Turkey and in the world for the last 30 years. Especially for the developing countries, urbanization is a necessary fact for the sustainability of the urban growth. Yet, this growth should be controlled and planned; otherwise, many environmental problems might occur. Therefore, the urban areas having dynamic structure should be monitored periodically. Monitoring the changes in urban environment can be provided with land cover land use (LCLU) maps produced by the pixel based classification methods using ‘maximum likelihood' and ‘isodata' techniques. However, these thematic maps might bring about inaccurate classification results in heterogeneous areas especially where low spatial resolution satellite data is used since, in these approaches, each pixel is represented with only one class value. In this study, considering the spectral mixture analysis (SMA) each pixel is represented by endmember fractions. The earth is represented more accurately using 'substrate (S)', ‘green vegetation (V)' and ‘dark surfaces (D)' spectral endmember reflectances with this analysis based on linear mixture model. Here, the surrounding of Izmit Gulf, one of the most industrialized areas of Turkey, has been chosen as the study area. SMA has been applied to LANDSAT images of the years of 1984, 1999 and 2009. In addition, DMSP-OLS data of 1992, 1999 and 2009 has been used to detect urban areas. According to the results, the changes in LCLU and especially the urban growth areas have been detected accurately using the SMA method.

Quantifying Urban Expansion Using Landsat Images and Landscape Metrics: A Case Study of the Halton Region, Ontario

GEOMATICA ◽  
2020 ◽  
Author(s):  
Liyuan Qing ◽  
Hasti A. Petrosian ◽  
Sarah N. Fatholahi ◽  
Michael A. Chapman ◽  
Jonathan Li
Keyword(s):  
Landscape Metrics ◽  
Urban Areas ◽  
Census Data ◽  
Urban Expansion ◽  
Landsat Images ◽  
Factors Affecting ◽  
Supervised Learning Algorithms ◽  
Dramatic Rise ◽  
Multi Temporal ◽  
Gis Software

Urbanization is considered as one of the main factors affecting global change. The Halton Region as part of the Great Toronto Area (GTA), is regarded as one of the fastest growing regions in Canada, generating 20% of national GDP. It is also one of the most desirable places for living and thriving business. This research attempts to assess the urban expansion in the Halton Region, Ontario, Canada from 1989 to 2019 using satellite images, analysis approaches and landscape metrics. Multi-temporal Landsat images, and the supervised learning algorithms in GIS software were used to explore the dynamic changes, and to classify the urban and non-urban areas. The temporal urban expansion in the Halton Region experienced a dramatic rise, and mainly occurred from the centre of the area. The analysis of landscape metrics based on different methods, including Land Use in Central Indiana (LUCI) model, Vegetation-Impervious Surface-soil (V-I-S) model, and the census data of Canada was carried out to understand the transition mode of the urbanization in the Halton Region. Also, the population growth in the centre of the Halton Region was considered as one of driven forces affecting urban expansion. The results showed that most of the landscape metrics rose between 1989 and 2019, indicating leapfrog pattern of urbanization occurred over the entire period. The contribution of this research is to evaluate the urbanization in the Halton Region, and give the city managers a clear mind to make appropriate decisions in further urban planning.

scholarly journals THE STUDY OF HEAT ISLAND AND ITS RELATION WITH URBANIZATION IN GURUGRAM, DELHI NCR FOR THE PERIOD OF 1990 TO 2018

2019 ◽  
Vol XLII-5/W3 ◽  
pp. 49-56
Author(s):  
S. Kushwaha ◽  
Y. Nithiyanandam
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Urban Expansion ◽  
Large City ◽  
Capital City ◽  
Spatial Decision Support System ◽  
Heat Island ◽  
Landsat Images ◽  
Infrared Band ◽  
Major Satellite

Abstract. Rapid growth in population and land cover makes urban areas more vulnerable to Urban Heat Island. Due to which, cities experience higher mean temperature than its proximate surrounding rural or non-urban area. The relationship between UHI and urbanization is proven in previous studies. Delhi the capital city of India is well known for its extreme heat condition in summer and air pollution. In this study, an attempt has been made to understand UHI behavior in a satellite town of Delhi. Satellite town or cities are the small independent towns built in the vicinity of a large city or metropolitan city. In this paper 4 major satellite towns of Delhi, i.e. Gurugram (name changed from Gurgaon in April 2016), Noida, Faridabad and Ghaziabad has been studied to understand the changing trends in urbanization and temperature. The parameters used are rate of urban expansion, population density, GDP growth and increasing temperature over the last two decades. Gurugram showed the maximum urbanization and identified as study area. Gurugram has undergone a major growth journey from being a small town to ‘The Millennium city’ of the country in a short span. The Landsat images of past three decades ranging from different time period i.e. 1990, 1996, 2002, 2009, 2014 and 2018 were investigated by applying integrated approach of GIS and Remote sensing. The images represent the condition of UHI and urbanization in different period. The temporal change in LULC was used to study the rate of urban growth in last three decades. The results showed the increase in built-up area out of the total area of Gurugram from 10% (i.e.50.6 sq. km) in 1990 to 17.25% (80.5 sq. km) in 2002 which further increased to 45.1% (210.4 sq. km) in 2018. Thermal Infrared band of Landsat series were used to retrieve land surface temperature (LST) intensity of the study period. The results show a positive correlation (r = 0.46) between impervious surfaces and LST. The results of the study could be helpful in identifying the causative factors and level of impacts in different zones and also enable us to develop a mitigation strategy based on spatial decision support system.

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