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 MAPPING OF LAND-COVER CHANGE ANALYSIS IN MA’RIB AT YEMEN USING REMOTE SENSING AND GIS TECHNIQUES

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 1-10
Author(s):  
S. Al-Akad ◽  
Y. Akensous ◽  
M. Hakdaoui ◽  
F. Al-Nahmi ◽  
S. Mahyoub ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Supervised Classification ◽  
Satellite Images ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Rate Of Change ◽  
Change Analysis ◽  
Remote Sensing Techniques

<p><strong>Abstract.</strong> Studies on the change in occupation and land-use are of great importance in order to understand landscape dynamics in the process of agricultural land degradation, urbanization, desertification, deforestation and all change in the landscape global of a region. The most effective procedure to measure the degree of land-cover and land-use changes is the multi-date study. For this purpose, the aim of this work is to analyze the current evolution of land-use and land-cover (LULC) using remote sensing techniques, in order to better understand this evolution. For this purpose, a diachronic approach is applied to satellite images acquired in 1987 to 2018 of Ma’rib city Yemen. The LULC maps we obtained were produced from different image analysis procedures (non-supervised classification and recode technique) to map the land-use and land-cover. The objective of this study is to apply reproducibly and generalizable a predefined nomenclature to different scenes of satellite images. The first step consists in interpreting the radiometric classes obtained by non-supervised classification so as to form the classes of the thematic nomenclature. An improvement of the classification is then obtained by using the recode technique which makes it possible to correctly reassign the previously badly classified pixels of the satellite images classification. Land-cover maps obtained from remote sensing were used to quantify the rate of change (Tc) and (Tg) of area occupied by each class. The results will indicate the most changeable period and the percentage of overall change in the study area (Ma’rib Yemen), and helped to identify and characterize the spatial and temporal evolution of land use in the district over a period of thirty-one years (1987 to 2018). They reveal that annual average rates of decline for the water body is &amp;minus;83.5% and &amp;minus;9.96% for the sandy land. However, it was observed an increase in built-up area 365.52% and farm land 324.52% classes.</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.

scholarly journals Effects of Land-Related Policies on Deforestation in a Protected Area: The Case Study of Rema-Kalenga Wildlife Sanctuary, Bangladesh

Conservation ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 168-181
Author(s):  
Mohammad Ismail Hossain ◽  
Shinya Numata
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Interactive Effect ◽  
Forest Policy ◽  
Land Policy ◽  
Wildlife Sanctuary ◽  
Landsat Images ◽  
Change Analysis ◽  
Management Plans ◽  
Total Forest Area

In protected areas (PAs) in Bangladesh, as policies shift from net deforestation, conservation initiatives and various management plans have been implemented to reduce deforestation and include public participation at multiple levels. However, the interactive effect of land-related policies on deforestation in PAs is poorly understood. In this study, land-use change analysis using geographic information system data was performed to investigate how policies affected land use and land cover change in Rema-Kalenga Wildlife Sanctuary (RKWS), particularly the National Forest Policy (1979~), National Land Policy (2001~), and Agricultural Land Policy (1999~), using a series of Landsat images captured at different times. Our analyses showed that the total forest area increased in the 1994–2005 period when a plantation program was implemented, and also that many forest areas were replaced with noncommercial agricultural land areas in the 2005–2013 and 2013–2018 periods, when land zoning and co-management programs were implemented under different land-related policies. Commercial and non-commercial agricultural land expansions were the main drivers of deforestation, suggesting that several programs under the different land-related policies could have had synergetic effects on deforestation even in PAs. Our findings emphasize the importance of considering the undesirable effects of land-related policies in Pas, and the need to support the community for forest conservation.

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.

scholarly journals Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

2019 ◽  
Vol 8 (10) ◽  
pp. 454 ◽  
Author(s):  
Junfeng Kang ◽  
Lei Fang ◽  
Shuang Li ◽  
Xiangrong Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Markov Model ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing Images ◽  
Mapreduce Framework ◽  
Construction Land ◽  
Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

scholarly journals Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

2018 ◽  
Vol 10 (11) ◽  
pp. 4287 ◽  
Author(s):  
Yantao Xi ◽  
Nguyen Thinh ◽  
Cheng Li
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Urban Areas ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Local Level ◽  
Land Use Changes ◽  
Landscape Patterns ◽  
Rapid Urbanization ◽  
Barren Land

Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

Urban Land Use Changes by the Integration of Remote Sensing, GIS, and Dynamics Modeling

2013 ◽  
Vol 726-731 ◽  
pp. 4645-4649
Author(s):  
Jia Hua Zhang ◽  
Cui Hao ◽  
Feng Mei Yao
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Areas ◽  
Logistic Model ◽  
Land Use Changes ◽  
Urban Land ◽  
Urban Land Use ◽  
Ratio Test ◽  
Multinomial Logistic Model ◽  
The Impact

We developed an approach to assess urban land use changes that incorporates socio-economic and environmental factors with multinomial logistic model, remote sensing data and GIS, and to quantify the impact of macro variables on land use of urban areas for the years 1990, 2000 and 2010 in Binhai New Area, China. The Markov transition matrix was designed to integrate with multinomial logistic model to illustrate and visualize the predicted land use surface. The multinomial logistic model was evaluated by means of Likelihood ratio test and Pseudo R-Square and showed a relatively good simulation. The prediction map of 2010 showed accurate rates 78.54%, 57.25% and 70.38%, respectively.

scholarly journals Application of the SWAT model in the Pinios river basin under different land-use scenarios

2013 ◽  
Vol 5 (2) ◽  
pp. 71-79 ◽  
Keyword(s):  
Land Use ◽  
Urban Areas ◽  
Agricultural Land ◽  
Swat Model ◽  
Land Use Changes ◽  
Time Step ◽  
Pinios River ◽  
Monthly Runoff ◽  
The One ◽  
Main Components

This paper investigates the hydrological effects of specific land use changes in a catchment of the river Pinios in Thessaly (Ali Efenti catchment), through the application of the Soil and Water Assessment Tool (SWAT) on a monthly time step. The model's calibration efficiency is verified by comparing the simulated and observed discharge time series at the outlet of the watershed, where long series of hydrometrical data exist. The model is used to simulate the main components of the hydrologic cycle, in order to study the effects of land use changes. Three land use change scenarios are examined, namely (A) expansion of agricultural land, (B) complete deforestation of the Trikala sub-basin and (C) expansion of urban areas in the Trikala sub-basin. All three scenarios resulted in an increase in discharge during wet months and a decrease during dry periods. The deforestation scenario was the one that resulted in the greatest modification of total monthly runoff.

Reviewing the Pertinence of Sentinel-1 SAR for Urban Land Use Land Cover Classification

2020 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Dan Abudu ◽  
Nigar Sultana Parvin ◽  
Geoffrey Andogah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Cover Classification ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Sensing Technology

Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets.

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