Detection of urban irregular development and green space destruction using normalized difference vegetation index (NDVI), principal component analysis (PCA) and post classification methods: A case study of Saqqez city

2012 ◽  
Vol 7 (17) ◽  
Author(s):  
Himan Shahabi
Keyword(s):  
Principal Component Analysis ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Component Analysis ◽  
Classification Methods

scholarly journals Using the ARP-03 for high-resolution mapping of calcic horizons

2013 ◽  
Vol 27 (3) ◽  
pp. 313-321 ◽  
Author(s):  
S. Priori ◽  
M. Fantappič ◽  
S. Magini ◽  
E.A.C. Costantini
Keyword(s):  
Principal Component Analysis ◽  
Electrical Resistivity ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Component Analysis ◽  
Proximal Sensing ◽  
Cheap Method ◽  
Resolution Mapping

Abstract The aim of this work is to present a fast and cheap method for high-resolutionmapping of calcic horizons in vineyards based on geoelectrical proximal sensing. The study area, 45 ha located in southern Sicily (Italy), was characterized by an old, partially dismantled marine terrace and soils with a calcic horizon at different depths. The geoelectrical investigation consisted of a survey of the soil electrical resistivity recorded with the Automatic Resistivity Profiling-03 sensor. The electrical resistivity values at three pseudo-depths, 0-50, 0-100 and 0-170 cm, were spatialized by means of ordinary kriging. A principal component analysis of the three electrical resistivity maps was carried out. During the survey, 18 boreholes, located at different electrical resistivity values, were made for soil description and sampling. The depth to the calcic horizon showed a strong correlation with electrical resistivity. The regression model between calcic horizon and the principal component analysis factors with the highest correlation coefficients was selected to spatialise the calcic horizon values. An Normalized Difference Vegetation Index map was used to validate the calcic horizon map in terms of crop response to different soil rooting depths. The strengths of this method are the quick, non-invasive kind of survey, the relevance for vine vigour, and the high spatial resolution of the final map.

scholarly journals ALGORITMA UNTUK DETEKSI TUMPAHAN MINYAK DI LAUT TIMOR MENGGUNAKAN CITRA MODIS

2017 ◽  
Vol 4 (1) ◽  
pp. 41-62
Author(s):  
Muhammad Sudibjo ◽  
Vincentius P. Siregar ◽  
Jonson Lumban Gaol
Keyword(s):  
Principal Component Analysis ◽  
Oil Spill ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Component Analysis ◽  
Fluorescence Index ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Tumpahan minyak di Laut Timor yang terjadi pada tahun 2009 telah menyebarkan minyak seluas 10.842.81 km2.Tumpahan minyak ini berhasil dideteksi oleh satelit Moderate Resolution Imaging Spectroradiometer (MODIS). Tujuan dari penelitian ini adalah membandingkan hasil deteksi tumpahan minyak dari beberapa algoritma dengan citra menggunakan citra MODIS dan melihat perbedaan visual yang dihasilkan. Algoritma yang digunakan adalah Oil Spill Index, Fluorescence Index, Principal Component Analysis (PCA), Normalized Difference Vegetation Index (NDVI). Visualisasi tumpahan minyak yang terlihat pada citra MODIS dengan algoritma oil spill indeks dan fluorescence index lebih cerah dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel lebih tinggi, sedangkan visualisasi minyak menggunakan algoritma PCA dan NDVI lebih gelap dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel yang lebih rendah. Hasil uji akurasi yang dilakukan terhadap algoritma oil splill index, fluorescence index, PCA, NDVI berturut-turut sebagai berikut 41%, 46%, 41%, dan 60%

scholarly journals Association between Green Space Structure and the Prevalence of Asthma: A Case Study of Toronto

2021 ◽  
Vol 18 (11) ◽  
pp. 5852
Author(s):  
Yuping Dong ◽  
Helin Liu ◽  
Tianming Zheng
Keyword(s):  
Air Pollution ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Chronic Inflammatory Disease ◽  
Space Structure ◽  
Tree Diversity ◽  
Underlying Mechanisms ◽  
Index Tree

Asthma is a chronic inflammatory disease that can be caused by various factors, such as asthma-related genes, lifestyle, and air pollution, and it can result in adverse impacts on asthmatics’ mental health and quality of life. Hence, asthma issues have been widely studied, mainly from demographic, socioeconomic, and genetic perspectives. Although it is becoming increasingly clear that asthma is likely influenced by green spaces, the underlying mechanisms are still unclear and inconsistent. Moreover, green space influences the prevalence of asthma concurrently in multiple ways, but most existing studies have explored only one pathway or a partial pathway, rather than the multi-pathways. Compared to greenness (measured by Normalized Difference Vegetation Index, tree density, etc.), green space structure—which has the potential to impact the concentration of air pollution and microbial diversity—is still less investigated in studies on the influence of green space on asthma. Given this research gap, this research took Toronto, Canada, as a case study to explore the two pathways between green space structure and the prevalence of asthma based on controlling the related covariates. Using regression analysis, it was found that green space structure can protect those aged 0–19 years from a high risk of developing asthma, and this direct protective effect can be enhanced by high tree diversity. For adults, green space structure does not influence the prevalence of asthma unless moderated by tree diversity (a measurement of the richness and diversity of trees). However, this impact was not found in adult females. Moreover, the hypothesis that green space structure influences the prevalence of asthma by reducing air pollution was not confirmed in this study, which can be attributed to a variety of causes.

Application of the principal component analysis on geochemical data: a case study in the basement complex of Southern Ilesa area, Nigeria

2010 ◽  
Vol 4 (1-2) ◽  
pp. 239-247 ◽  
Author(s):  
Emmanuel A. Ariyibi ◽  
Samuel L. Folami ◽  
Bankole D. Ako ◽  
Taye R. Ajayi ◽  
Adebowale O. Adelusi
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Geochemical Data ◽  
Basement Complex

scholarly journals Groundwater Quality Assessment: An Improved Approach to K-Means Clustering, Principal Component Analysis and Spatial Analysis: A Case Study

Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 437 ◽  
Author(s):  
Ana Marín Celestino ◽  
Diego Martínez Cruz ◽  
Elena Otazo Sánchez ◽  
Francisco Gavi Reyes ◽  
David Vásquez Soto
Keyword(s):  
Principal Component Analysis ◽  
Spatial Analysis ◽  
Groundwater Quality ◽  
Quality Assessment ◽  
Principal Component ◽  
Component Analysis ◽  
Groundwater Quality Assessment
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