scholarly journals An Assessment of Changes the Land Use Land Cover and Impact of the It Park at Talwade Pune On the Nearby Villages

2020 ◽  
pp. 172-179
Author(s):  
Ujjwala Khare ◽  
Prajakta Thakur
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rapid Growth ◽  
Urban Areas ◽  
Satellite Images ◽  
Ground Truth ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Tertiary Sector ◽  
Land Cover Maps

<p>The expansion of urban areas is common in metropolitan cities in India. Pune also has experienced rapid growth in the fringe areas of the city. This is mainly on account of the development of the Information Technology (IT) Parks. These IT Parks have been established in different parts of Pune city. They include Hinjewadi, Kharadi, Talwade and others like the IT parks in Magarpatta area. The IT part at Talwade is located to close to Pune Nashik Highway has had an impact on the villages located around it. The surrounding area includes the villages of Talwade, Chikhli, Nighoje, Mahalunge, Khalumbre and Sudumbre.</p> <p>The changes in the land use that have occurred in areas surrounding Talwade IT parks during the last three decades have been studied by analyzing the LANDSAT images of different time periods. The satellite images of the 1992, 2001 and 2011 were analyzed to detect the temporal changes in the land use and land cover.</p> <p>This paper attempts to study the changes in land use / land cover which has taken place in these villages in the last two decades. Such a study can be done effectively with the help of remote sensing and GIS techniques. The tertiary sector has experienced a rapid growth especially during the last decade near the IT Park. The occupation structure of these villages is also related to the changes due to the development of the IT Park.</p> <p>The land use of study area has been analysed using the ground truth applied to the satellite images at decadal interval. Using the digital image processing techniques, the satellite images were then classified and land use / land cover maps were derived. The results show that the area under built-up land has increased by around 14 per cent in the last 20 years. On the contrary, the land under agriculture, barren, pasture has decreased significantly.</p>

scholarly journals Drivers and dynamics of land use land cover in Ambung VDC of Tehrathum district, Nepal

2016 ◽  
Vol 26 (1) ◽  
pp. 90-96 ◽  
Author(s):  
D Pandey ◽  
B P Heyojoo ◽  
H Shahi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Group Discussion ◽  
Household Survey ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Severe Problem ◽  
Training Samples ◽  
Land Cover Maps

Land use and land cover change has immense impact on the global environment and ecosystem. Geospatial technologies are very important for monitoring these changes. This research aims to find out the land use land cover dynamics and drivers of Ambung VDC, Tehrathum district. The Landsat images of the year 1990 and 2013 were used for quantifying the changes. Household survey, key informant interview, focus group discussion, training samples collection and direct field observations were carried out to gather socio-economic and bio-physical data. Supervised classification was performed to prepare land cover maps. Change on land use was calculated by using post classification change detection. During 1990–2013, forest cover was found to have increased by 6.6%, agriculture decreased by 5.9% and others (barren, settlement, grass, rock and water bodies) decreased by 0.7%. The VDC was found to have severe problem of rapid drying of water resources in spite of the increase in forest cover, and so research should be carried out to find out the reason and solve the problem before it is too late.Banko JanakariA Journal of Forestry Information for NepalVol. 26, No. 1, Page:90-96, 2016

scholarly journals ASSESSMENT OF LAND USE AND LAND COVER CHANGE DETECTION BY USING REMOTE SENSING AND GIS TECHNIQUES IN THE COASTAL DESERTS, SOUTH OF IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 489-492
Author(s):  
S. A. R. Hosseini ◽  
H. Gholami ◽  
Y. Esmaeilpoor
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Urban Areas ◽  
Ground Truth ◽  
Landsat Images ◽  
Ground Truth Data ◽  
Sensing Technology ◽  
Time Period

Abstract. Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Due to the large expanse of land change detection by the traditional methods is not sufficient and efficient; therefore, using of new methods such as remote sensing technology is necessary and vital This study evaluates LULC change in chabahar and konarak Coastal deserts, located in south of sistan and baluchestan province from 1988 to 2018 using Landsat images. Maximum likelihood classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. Then, taking ground truth data, the classified maps accuracy were assessed by calculating the Kappa coefficient and overall accuracy. The results for the time period of 1988–2018 are presented. Based on the results of the 30-year time period, vegetation has been decreased in area while urban areas have been developed. The area of saline and sandy lands has also increased.

scholarly journals A New Approach to High-Resolution Urban Land Use Classification Using Open Access Software and True Color Satellite Images

2019 ◽  
Vol 11 (19) ◽  
pp. 5266 ◽  
Author(s):  
Fernando Chapa ◽  
Srividya Hariharan ◽  
Jochen Hack
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Urban Areas ◽  
Google Earth ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Wide Range ◽  
True Color ◽  
Land Cover Maps

Urbanization nowadays results in the most dynamic and drastic changes in land use/land cover, with a significant impact on the environment. A detailed analysis and assessment of this process is necessary to take informed actions to reduce its impact on the environment and human well-being. In most parts of the world, detailed information on the composition, structure, extent, and temporal changes of urban areas is lacking. The purpose of this study is to present a methodology to produce high-resolution land use/land cover maps by the use of free software and satellite imagery. These maps can help to understand dynamic urbanizations processes to plan, design, and coordinate sustainable urban development plans, especially in areas with limited resources and advancing environmental degradation. A series of high-resolution true color images provided by Google Earth Pro were used to do initial classifications with the Semi-Automatic Classification Plug-in in QGIS. Afterwards, a new methodology to improve the classification by the elimination of shadows and clouds, and a reduction of misclassifications through superimposition was applied. The classification was carried out for three urban areas in León, Nicaragua, with different degrees of urbanization for the years 2009, 2015, and 2018. Finally, the accuracy of the classification was analyzed using randomly defined validation polygons. The results are three sets of high-resolution land use/land cover maps of the initial and the improved classification, showing the detailed structures and temporal dynamics of urbanization. The average accuracy of classification reaches 74%, but up to 85% for the best classification. The results clearly identify advancing urbanization, the loss of vegetation and riparian zones, and threats to urban ecosystems. In general, the level of detail and simplicity of our methodology is a valuable tool to support sustainable urban management, although its application is not limited to these areas and can also be employed to track changes over time, providing therefore, relevant information to a wide range of decision-makers.

scholarly journals Land-Use/Land-Cover Change Analysis and Urban Growth Modelling in the Greater Accra Metropolitan Area (GAMA), Ghana

Urban Science ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 26 ◽  
Author(s):  
Bright Addae ◽  
Natascha Oppelt
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Urban Growth ◽  
Urban Areas ◽  
City Planning ◽  
Land Use Land Cover ◽  
Vegetative Cover ◽  
Landsat Images ◽  
Urban Extent

A rapid increase in the world’s population over the last century has triggered the transformation of the earth surface, especially in urban areas, where more than half of the global population live. Ghana is no exception and a high population growth rate, coupled with economic development over the last three decades, has transformed the Greater Accra region into a hotspot for massive urban growth. The urban extent of the region has expanded extensively, mainly at the expense of the vegetative cover in the region. Although urbanization presents several opportunities, the environmental and social problems cannot be underestimated. Therefore, the need to estimate the rate and extent of land use/land cover changes in the region and the main drivers of these changes is imperative. Geographic Information Systems (GIS) and remote sensing techniques provide effective tools in studying and monitoring land-use/land-cover change over space and time. A post classification change detection of multiple Landsat images was conducted to map and analyse the extent and rate of land use/land cover change in the region between 1991 and 2015. Subsequently, the urban extent of the region was forecasted for the year 2025 using the Markov Chain and the Multi-Layer Perceptron neural network, together with drivers representing proximity, biophysical, and socio-economic variables. The results from the research revealed that built-up areas increased by 277% over the 24-year study period. However, forest areas experienced massive reduction, diminishing from 34% in 1991 to 6.5% in 2015. The 2025 projected land use map revealed that the urban extent will massively increase to cover 70% of the study area, as compared to 44% in 2015. The urban extent is also anticipated to spill into the adjoining districts mainly on the western and eastern sides of the region. The success of this research in generating a future land-use map for 2025, together with the other significant findings, demonstrates the usefulness of spatial models as tools for sustainable city planning and environmental management, especially for urban planners in developing countries.

scholarly journals Monitoring of Changes in Land Use/Land Cover in Syria from 2010 to 2018 Using Multitemporal Landsat Imagery and GIS

Land ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 226 ◽  
Author(s):  
Mohamed Mohamed ◽  
Julian Anders ◽  
Christoph Schneider
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Large Scale ◽  
Management Practices ◽  
Landsat Imagery ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Climate Trend ◽  
Lulc Change

Understanding the effects of socio-ecological shocks on land use/land cover (LULC) change is essential for developing land management strategies and for reducing adverse environmental pressures. Our study examines the impacts of the armed conflict in Syria, which began in mid-2011, and the related social and economic crisis on LULC between 2010 and 2018. We used remote sensing for change detection by applying a supervised maximum likelihood classification to Landsat images of the three target years 2010, 2014, and 2018. Based on the computed extent of our LULC classes and accuracy assessment, we calculated area-adjusted estimates and 95% confidence intervals. Our classification achieved an overall accuracy of 86.4%. Compared to 2010, we found an increase in spatial extent for bare areas (40,011 km2), forests (2576 km2), and urban and peri-urban areas (3560 km2), whereas rangelands (37,005 km2) and cultivated areas (9425 km2) decreased by 2018. It is not possible to determine whether the changes in LULC in Syria will be permanent or temporary. Natural conditions such as climate fluctuations had an impact on the uses of the natural environment and cultivated areas during the study period, especially in regions suffering from water stress. Although seasonal precipitation patterns and temperature affect LULC change, however, we could not identify a prevailing climate trend towards more drought-prone conditions. Our analysis focuses on (potential) direct and indirect implications of the Syrian conflict on LULC change, which most notably occurred between 2014 and 2018. Conflict-related main drivers were human activities and demographic changes, which are mainly attributable to large-scale population displacement, military operations, concomitant socio-economic status, and control of local resources. As the study provides quantitative and qualitative information on the dynamics of LULC changes in Syria, it may serve as a framework for further relevant conflict-related research and support planning, management practices, and sustainable development.

scholarly journals Remote Sensing-Based Quantification of the Relationships between Land Use Land Cover Changes and Surface Temperature over the Lower Himalayan Region

2019 ◽  
Vol 11 (19) ◽  
pp. 5492 ◽  
Author(s):  
Ullah ◽  
Tahir ◽  
Akbar ◽  
Hassan ◽  
Dewan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Linear Regression Analysis ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Total Study Area

Population growth and population inflow from other regions has caused urbanization which altered land use land cover (LULC) in the lower Himalayan regions of Pakistan. This LULC change increased the land surface temperature (LST) in the region. LULC and LST changes were assessed for the period of 1990–2017 using Landsat data and the support vector machine (SVM) method. A combined cellular automata and artificial neural network (CA-ANN) prediction model was used for simulation of LULC changes for the period of 2032 and 2047 using transition potential matrix obtained from the data years of 2002 and 2017. The accuracy of the CA-ANN model was validated using simulated and classified images of 2017 with correctness value of 70% using validation modules in QGIS. The thermal bands of Landsat images from the years 1990, 2002 and 2017 were used for LST derivation. LST acquired for this period was then modeled for 2032 and 2047 using urban indices (UI) and linear regression analysis. The SVM land cover classification results showed a 5.75% and 4.22% increase in built-up area and bare soil respectively, while vegetation declined by 9.88% during 1990–2017. The results of LST for LULC classes showed that the built-up area had the highest mean LST as compared to other classes. The future projection of LULC and LST showed that the built-up area may increase by 12.48% and 14.65% in 2032 and 2047, respectively, of the total LULC area which was ~11% in 2017. Similarly, the area with temperature above 30 °C could be 44.01% and 58.02% in 2032 and 2047, respectively, of the total study area which was 18.64% in 2017. This study identified major challenges for urban planners to mitigate the urban heat island (UHI) phenomenon. In order to address the UHI in the study area, an urban planner might focus on urban plantation and decentralization of urban areas.

scholarly journals Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

2013 ◽  
Vol 8 (1) ◽  
pp. 084596 ◽  
Author(s):  
Zhongchang Sun ◽  
Xinwu Li ◽  
Wenxue Fu ◽  
Yingkui Li ◽  
Dongsheng Tang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Surface Runoff ◽  
Urban Areas ◽  
Land Use Land Cover ◽  
Long Term Effects ◽  
Effects Of Land Use ◽  
Beijing China

scholarly journals Multi-Temporal Landsat8 Satellite Data Based Crops and Other Land Use Spatial Estimation in Okara District of Pakistan

2018 ◽  
Author(s):  
Ibrar ul Hassan Akhtar ◽  
Athar Hussain ◽  
Kashif Javed ◽  
Hammad Ghazanfar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Urban Areas ◽  
Integrated Approach ◽  
Kappa Statistics ◽  
Digital Information ◽  
Land Use Land Cover ◽  
Land Utilization ◽  
Cropping Patterns

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land.&nbsp;

scholarly journals Analysis of land use/land cover change in Adei watershed, Central Highlands of Ethiopia

2019 ◽  
Vol 41 (1) ◽  
pp. 146-153 ◽  
Author(s):  
Megersa Olumana Dinka ◽  
Degefa Dhuga Chaka
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Supervised Classification ◽  
Landsat Imagery ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Post Processing ◽  
Ancillary Data ◽  
The Stability ◽  
Land Cover Maps

Abstract Land use/land cover changes (LULCC) at Adei watershed (Ethiopia) over a period of 23 years (1986–2009) has been analysed from LANDSAT imagery and ancillary data. The patterns (magnitude and direction) of LULCC were quantified and the final land use/land cover maps were produced after a supervised classification with appropriate post-processing. Image analysis results revealed that the study area has undergone substantial LULCC, primarily a shift from natural cover into managed agro-systems, which is apparently attributed to the increasing both human and livestock pressure. Over the 23 years, the aerial coverage of forest and grass lands declined by 8.5% and 4.3%, respectively. On the other hand, agricultural and shrub lands expanded by 9.1% and 3.7%, respectively. This shows that most of the previously covered by forest and grass lands are mostly shifted to the rapidly expanding farm land use classes. The findings of this study suggested that the rate of LULCC over the study period, particularly deforestation due to the expansion of farmland need to be given due attention to maintain the stability and sustainability of the ecosystem.

Spatiotemporal Pattern Analysis of Rapid Urban Expansion Using GIS and Remote Sensing

2010 ◽  
Vol 1 (2) ◽  
pp. 55-70 ◽  
Author(s):  
Hyun Joong Kim
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Urban Areas ◽  
Temporal Dynamics ◽  
Urban Expansion ◽  
Local Scale ◽  
Spatiotemporal Pattern ◽  
Land Use Land Cover ◽  
Modeling Studies

Rapidly growing urban areas tend to reveal distinctive spatial and temporal variations of land use/land cover in a locally urbanized environment. In this article, the author analyzes urban growth phenomena at a local scale by employing Geographic Information Systems, remotely sensed image data from 1984, 1994, and 2004, and landscape shape index. Since spatial patterns of land use/land cover changes in small urban areas are not fully examined by the current GIS-based modeling studies or simulation applications, the major objective of this research is to identify and examine the spatial and temporal dynamics of land use changes of urban growth at a local scale. Analytical results demonstrate that sizes, locations, and shapes of new developments are spatio-temporally associated with their landscape variations and major transportation arteries. The key findings from this study contribute to GIS-based urban growth modeling studies and urban planning practices for local communities.

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