scholarly journals LAND COVER CHANGE DETECTION ANALYSIS ON URBAN GREEN AREA LOSS USING GIS AND REMOTE SENSING TECHNIQUES

2013 ◽  
Vol 11 ◽  
Author(s):  
Noorzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mohd Nasrul Hanis Manzahani
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Kuala Lumpur ◽  
Gis And Remote Sensing ◽  
Detection Analysis ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Erdas Imagine ◽  
Remote Sensing Techniques

The loss of green area has been rising all over the world particularly in big cities. For a number of decades, urban sprawl and developments have changed the natural landscapes of urban areas where areas with green areas have been converted into built up developments and other land uses. Thus this research intends to study the changes of green areas in Kuala Lumpur based on land use detection analysis approach where 3 series of remote sensing images namely SPOT2, SPOT4 and IKONOS for year 1990, 2001 and 2010 have been used to acquire the data on the green area changes aided by ERDAS IMAGINE 2011 and ARGIS 9.2. The finding of the study shows that there is a decrease in the size of green area in Kuala Lumpur from year 1990-2010 due to pressure of urban developments. Two significant factors which contribute to the changes of green area in Kuala Lumpur have been identified in the study, which are the increase in built up areas and sprawl development pattern.

LAND COVER CHANGE DETECTION ANALYSIS ON URBAN GREEN AREA LOSS USING GIS AND REMOTE SENSING TECHNIQUES

2013 ◽  
Vol 11 (3) ◽  
Author(s):  
Norzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mohd Nasrul Hanis Manzahani
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Kuala Lumpur ◽  
Gis And Remote Sensing ◽  
Detection Analysis ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Erdas Imagine ◽  
Remote Sensing Techniques

The loss of green area has been rising all over the world particularly in big cities. For a number of decades, urban sprawl and developments have changed the natural landscapes of urban areas where areas with green areas have been converted into built up developments and other land uses. Thus this research intends to study the changes of green areas in Kuala Lumpur based on land use detection analysis approach where 3 series of remote sensing images namely SPOT2, SPOT4 and IKONOS for year 1990, 2001 and 2010 have been used to acquire the data on the green area changes aided by ERDAS IMAGINE 2011 and ARGIS 9.2. The finding of the study shows that there is a decrease in the size of green area in Kuala Lumpur from year 1990-2010 due to pressure of urban developments. Two significant factors which contribute to the changes of green area in Kuala Lumpur have been identified in the study, which are the increase in built up areas and sprawl development pattern.

scholarly journals Applying remote sensing techniques to monitor green areas in Tashkent Uzbekistan

2021 ◽  
Vol 258 ◽  
pp. 04012
Author(s):  
Ilhomjon Aslanov ◽  
Uzbekkhon Mukhtorov ◽  
Rahimjon Mahsudov ◽  
Umida Makhmudova ◽  
Saida Alimova ◽  
...  
Keyword(s):  
Accuracy Assessment ◽  
Ground Truth ◽  
Population Increase ◽  
Visual Interpretation ◽  
Ground Truth Data ◽  
Capital Cities ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Remote Sensing Techniques

Land use and land cover (LULC) change are one of the most important signals of regional environmental monitoring and study. Recently, the pull of capital cities has snowballed, an increasing number of people moving to the cities, especially in developing countries. Consequently, as more people arrive at cities, the more pressure will be on land. Land price getting high and constructions try using open green areas. A wide variety of green areas of different sizes will be solve many urban diseases and ecological problems at the same time improve the quality and life of urban residents, as urban green area provides various ecosystem services. The green area includes parks, woodlands, nature reserves and bare lands. With the population increase and expansion of cities, an increasing amount of open area, woodland and bare land has been converted into construction land, buildings due to the increasing demands and residential land. For the accuracy assessment, we applied an automatically supervised classification using the software QGIS 3.18. The reference values were based on ground truth data and visual interpretation.

scholarly journals Mapping summer SUHI and its impact on the environment using GIS and Remote Sensing techniques: A case study on Municipality of Prishtina (Kosovo)

2021 ◽  
Vol 12 (3) ◽  
pp. 113-129
Author(s):  
Albert Berila ◽  
◽  
Florim Isufi ◽  
Keyword(s):  
Remote Sensing ◽  
Rural Areas ◽  
Urban Areas ◽  
Satellite Image ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Remote Sensing Techniques

Urban areas, compared to peripheral and rural areas, have higher temperatures which are caused by a series of unplanned activities that are undertaken by humans. Such a thing leads to the emergence of the Surface Urban Heat Island (SUHI) phenomenon. In this paper, summer SUHI is determined through the calculation of LST for the Municipality of Prishtina using GIS and Remote Sensing techniques. To make this calculation, the Landsat 8 satellite image with 0% cloud cover was used. From the calculations made it turns out that the pixels with the highest value of LST are found in those parts where the urban area appears, where there are numerous constructions with impermeable materials, as well as in those areas where there are bare surfaces. Whereas, the pixels with lower values of LST appear in those parts where there are vegetation and water bodies, making these areas fresher. The SUHI phenomenon makes the lives of citizens difficult, therefore, such information is very important for the leaders and urban planners of the city of Prishtina, so that they take a series of steps towards minimizing such an effect in order to the life of the citizens to be as healthy as possible.

scholarly journals Identificação de Ilhas de Calor na Cidade de Campina Grande-PB Utilizando Sensoriamento Remoto (Identification of Heat Islands in Campina Grande City-PB Using Remote Sensing)

2016 ◽  
Vol 9 (2) ◽  
pp. 614 ◽  
Author(s):  
Elânia Daniele Silva Araújo
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Rural Areas ◽  
Urban Areas ◽  
Spatial And Temporal Variability ◽  
Heat Islands ◽  
Social Nature ◽  
Spatial Changes ◽  
Remote Sensing Techniques ◽  
The City

A intensa urbanização causa diversos problemas de natureza ambiental, climática e social. O crescimento não planejado da população urbana e a remoção da vegetação são fatores que intensificam estes problemas. As temperaturas na cidade são significativamente mais quentes do que as suas zonas rurais circundantes devido às atividades humanas. As intensas mudanças espaciais em áreas urbanas, promovem significativo aumento na temperatura, causando o chamado efeito de Ilha de Calor Urbano (ICU). Campina Grande é uma cidade de tamanho médio que experimentou um crescimento desordenado, desde o tempo do comércio de algodão e, como qualquer cidade de grande ou médio porte, sofre alterações em seu espaço. Dessa forma, este estudo teve por objetivo analisar a variabilidade espaço-temporal da temperatura da superfície (Ts) e detectar ICU, através de técnicas de sensoriamento remoto. Para o efeito, foram utilizadas imagens dos satélites Landsat 5 e 8, dos anos de 1995, 2007 e 2014. Aumentos da Ts foram bem evidentes e foram detectadas duas ICU. Campina Grande mostra um padrão de tendência: o crescimento urbano não planejado é responsável por mudanças no ambiente físico e na forma e estrutura espacial da cidade, o que se reflete sobre o microclima e, em última análise, na qualidade de vida das pessoas.   ABSTRACT The intense urbanization causes several problems of environmental, climate and social nature. The unplanned growth of urban population and the vegetation removal are factors that deepen these problems. Temperatures in the city are significantly warmer than its surrounding rural areas due to human activities. Large spatial changes in urban areas promote significant increase in temperature, causing the so-called Urban Heat Island effect (UHI). Campina Grande is a medium-sized town that experienced an uncontrolled growth since the time of the cotton trade and like any large or medium-sized city, undergoes changes in its space. Therefore, this study aimed to analyze surface temperature spatial and temporal variability and to detect potential UHI, through remote sensing techniques. Spectral images from Landsat 5 and 8 satellites were used. Using images from years 1995, 2007 and 2014, considerable increases in temperature were identified and two UHI were recognize. Campina Grande shows a trend pattern: the urban unplanned growth is responsible for changes in the physical environment and in the form and spatial structure of the city, reflecting on people quality of life. Keywords: change detection, surface temperature, heat islands, urbanization.   

scholarly journals Possibilities of milpa identification in Yucatan through remote sensing techniques and Sentinel-2 data

10.29007/hbs2 ◽  
2019 ◽  
Author(s):  
Juan Carlos Valdiviezo-Navarro ◽  
Adan Salazar-Garibay ◽  
Karla Juliana Rodríguez-Robayo ◽  
Lilián Juárez ◽  
María Elena Méndez-López ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Food Sovereignty ◽  
Region Of Interest ◽  
Remote Sensing Data ◽  
Support Vector ◽  
Multispectral Images ◽  
Crop Fields ◽  
Remote Sensing Techniques ◽  
Sentinel 2

Maya milpa is one of the most important agrifood systems in Mesoamerica, not only because its ancient origin but also due to lead an increase in landscape diversity and to be a relevant source of families food security and food sovereignty. Nowadays, satellite remote sensing data, as the multispectral images of Sentinel-2 platforms, permit us the monitor- ing of different kinds of structures such as water bodies, urban areas, and particularly agricultural fields. Through its multispectral signatures, mono-crop fields or homogeneous vegetation zones like corn fields, barley fields, or other ones, have been successfully detected by using classification techniques with multispectral images. However, Maya milpa is a complex field which is conformed by different kinds of vegetables species and fragments of natural vegetation that in conjunction cannot be considered as a mono-crop field. In this work, we show some preliminary studies on the availability of monitoring this complex system in a region of interest in Yucatan, through a support vector machine (SVM) approach.

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