Urban land use challenges to vegetation index of green open spaces (original) (raw)
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On account of rapid urbanization, vegetation cover of the earth's surface has been declining day by day. To study the spatial and temporal changes of vegetation cover we can use remote sensing and geographic information system. The present study aims to analyze and detect the spatial and temporal changes of NDVI of Kolkata Municipal Corporation (KMC). The researcher used the Normalized Difference Vegetation Index (NDVI) to detect the spatio-temporal changes of the vegetation cover of the KMC from 1991 to 2011. It is computed by using the visible and near-infrared bands of the electromagnetic spectrum (EMS). For this, multi-spectral remote sensing data have been used. The results show that the city of Kolkata is experiencing a declining trend of green cover; it is more prevalent in the added area of the KMC, i.e. the area covered by Wards No.101 to 141.
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Urban vegetation can have beneficial effects on biodiversity and human health and has been widely studied in temperate cities. The situation, however, is different in the tropics: there is a knowledge gap describing the influence of the growth and expansion of tropical cities on vegetation within the cities. There is also a scarcity of work discussing appropriate methods to quantify urban vegetation in the tropics, where financial resources for research are normally quite limited. Our objectives in this article were to measure the amount of urban vegetation in a tropical city, its relationship to population and infrastructure, and to determine if satellite results differ from those obtained on the ground. For these objectives we studied the city of Heredia, Costa Rica, during the rainy season, when vegetation was most developed. We sampled 91 sites from the ground (with 360 degree digital panoramic photographs) and compared the measurements with the corresponding satellite photographs. Satellite and ground estimates of vegetation and infrastructure differed significantly (Kruskal-Wallis ANOVA, p=0.00002). The satellite estimate of vegetation was nearly one third higher that the ground estimate. These finding illustrated that a significant part of the vegetation is hidden from the view, reducing the potential beneficial effects that a person's perception of plants has on their psychology. Conversely, the estimate of infrastructure cover was much higher from the ground than in the satellite photographs. In the ground estimate the dominant landscape component was vegetation (48%), followed by buildings (28%), roads (23%) and billboards (0.41%). We conclude that density of the human population, rather than its total size, is the best predictor of vegetation in this tropical landscape (multiplicative model regression, F Ratio 7.33, p= 0.0081).
Journal of Settlements and Spatial Planning, 2021
The rapid pace of urban development triggers complex problems mostly related to urban environment pollution, and shortcomings of city’s improvement. The modern city is characterized by the highest man-made pressure on the natural environment, the main problems being overcrowding, lack of open-access green areas, as well as the decrease of vegetation areas, fact that does not create comfortable living conditions for urban residents. At present, remote sensing methods are some of the priority tools used in vegetation state assessment, particularly, the calculation of vegetation index (NDVI). But often, obtaining the necessary information is limited only to the analysis of satellite data, without geobotanical field surveys, which considerably increase the reliability of the detected results. In addition, the definition of dependencies when using an integrated approach of different man-affected surfaces with a different type of overgrowth within the city remains insufficiently studied. ...
2018
Resumo São apresentadas aplicações utilizando imagens de satélite para identificação de fitofisionomias da cidade de Campo Grande que podem ser utilizadas para estudos de vegetação urbana, palinologia e mudanças ambientais. Foram utilizadas imagens dos satélites Landsat 8 e Rapideye da região urbanizada de Campo Grande. Foi realizada análise da cobertura de solo de cada uma das sete sub-regiões urbanas da cidade, aplicando o índice Normalized Difference Vegetation Index (NDVI) nestas imagens. Levantamento a campo foi realizado para confirmar as fitofisionomias identificadas através das imagens de satélite. A aplicação de imagens de satélite em conjunto com a validação in loco, possibilitou a distinção das feições água, estruturação urbana, vegetação aberta, rasteira e densa. Para o reconhecimento de fitofisio-nomias urbanas as imagens Rapideye foram as mais indicadas para este tipo de estudo. As imagens Rapideye identifica-ram 6.55% mais áreas de vegetação densa, do que as imagens Landsat 8. Palavras-chave: Sensoriamento remoto; modelagem urbana; Landsat 8, Rapideye Abstract These paper reports applications using satellite images to the identification of vegetation types in the Campo Grande city. This identification allows studies of urban vegetation, palynology and environmental changes. Images from Landsat 8 and Rapideye satellites from the Campo Grande urban area were used. A soil coverage map was done for each one of the seven sub-regions. The Normalized Difference Vegetation Index was applied. In addition, a field survey was carried out to confirm the vegetation types sites through satellite images. Satellite images and in situ data validation allowed the distinction of the following features: water, urban structure, herbaceous, open and dense vegetation. For the identification of urban vegetation, Rapideye images were the most suitable for this type of study. The Rapideye satellite sensor detected 6.55% more dense vegetation area than Landsat 8 images.