scholarly journals A Multiview Semantic Vegetation Index for Robust Estimation of Urban Vegetation Cover

2022 ◽  
Vol 14 (1) ◽  
pp. 228
Author(s):  
Asim Khan ◽  
Warda Asim ◽  
Anwaar Ulhaq ◽  
Randall W. Robinson
Keyword(s):  
Robust Estimation ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Plant Cover ◽  
Urban Forestry ◽  
Well Being ◽  
Vegetation Management ◽  
City Council ◽  
Urban Vegetation ◽  
Management Platform

Urban vegetation growth is vital for developing sustainable and liveable cities in the contemporary era since it directly helps people’s health and well-being. Estimating vegetation cover and biomass is commonly done by calculating various vegetation indices for automated urban vegetation management and monitoring. However, most of these indices fail to capture robust estimation of vegetation cover due to their inherent focus on colour attributes with limited viewpoint and ignore seasonal changes. To solve this limitation, this article proposed a novel vegetation index called the Multiview Semantic Vegetation Index (MSVI), which is robust to color, viewpoint, and seasonal variations. Moreover, it can be applied directly to RGB images. This Multiview Semantic Vegetation Index (MSVI) is based on deep semantic segmentation and multiview field coverage and can be integrated into any vegetation management platform. This index has been tested on Google Street View (GSV) imagery of Wyndham City Council, Melbourne, Australia. The experiments and training achieved an overall pixel accuracy of 89.4% and 92.4% for FCN and U-Net, respectively. Thus, the MSVI can be a helpful instrument for analysing urban forestry and vegetation biomass since it provides an accurate and reliable objective method for assessing the plant cover at street level.

scholarly journals Global Changes in Urban Vegetation Cover

2019 ◽  
Vol 12 (1) ◽  
pp. 23 ◽  
Author(s):  
Daniel R. Richards ◽  
Richard N. Belcher
Keyword(s):  
Vegetation Cover ◽  
Urban Areas ◽  
Well Being ◽  
Google Earth ◽  
Eastern North America ◽  
Urban Vegetation ◽  
Global Changes ◽  
Suburban Sprawl ◽  
The World ◽  
Google Earth Engine

Urban vegetation provides many ecosystem services that make cities more liveable for people. As the world continues to urbanise, the vegetation cover in urban areas is changing rapidly. Here we use Google Earth Engine to map vegetation cover in all urban areas larger than 15 km2 in 2000 and 2015, which covered 390,000 km2 and 490,000 km2 respectively. In 2015, urban vegetation covered a substantial area, equivalent to the size of Belarus. Proportional vegetation cover was highly variable, and declined in most urban areas between 2000 and 2015. Declines in proportional vegetated cover were particularly common in the Global South. Conversely, proportional vegetation cover increased in some urban areas in eastern North America and parts of Europe. Most urban areas that increased in vegetation cover also increased in size, suggesting that the observed net increases were driven by the capture of rural ecosystems through low-density suburban sprawl. Far fewer urban areas achieved increases in vegetation cover while remaining similar in size, although this trend occurred in some regions with shrinking populations or economies. Maintaining and expanding urban vegetation cover alongside future urbanisation will be critical for the well-being of the five billion people expected to live in urban areas by 2030.

scholarly journals Dynamic Changes in Melbourne’s Urban Vegetation Cover—2001 to 2016

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 814
Author(s):  
Bhuban Timalsina ◽  
Suzanne Mavoa ◽  
Amy K. Hahs
Keyword(s):  
Land Tenure ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dynamic Change ◽  
Public Access ◽  
Urban Vegetation ◽  
Open Spaces ◽  
Dynamic Changes ◽  
Public Open Spaces

Understanding changes in urban vegetation is essential for ensuring sustainable and healthy cities, mitigating disturbances due to climate change, sustaining urban biodiversity, and supporting human health and wellbeing. This study investigates and describes the distribution and dynamic changes in urban vegetation over a 15-year period in Greater Melbourne, Australia. The study investigates how vegetation cover across Melbourne has changed at five-yearly intervals from 2001 to 2016 using the newly proposed dynamic change approach that extends the net change approach to quantify the amount of vegetation gain as well as loss. We examine this question at two spatial resolutions: (1) at the municipal landscape scale to capture broadscale change regardless of land tenure; and (2) at the scale of designated public open spaces within the municipalities to investigate the extent to which the loss of vegetation has occurred on lands that are intended to provide public access to vegetated areas in the city. Vegetation was quantified at four different times (2001, 2006, 2011, 2016), using the normalized difference vegetation index (NDVI). Dynamic changes of gain and loss in urban vegetation between the three periods were quantified for six local government areas (LGAs) and their associated public open spaces using a change matrix. The results showed an overall net loss of 64.5 square kilometres of urban vegetation from 2001 to 2016 in six LGAs. When extrapolated to the Greater Melbourne Area, this is approximately equivalent to 109 times the size of Central Park in New York City.

scholarly journals Monitoring the quality of life in urban area using TDVI- Case study of Kalaburagi city

2021 ◽  
Vol 06 (09) ◽  
pp. 68-75
Author(s):  
Abhilasha Kumari ◽  
Keyword(s):  
Remote Sensing ◽  
Image Classification ◽  
Urban Environment ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Ground Truth ◽  
Urban Vegetation ◽  
Urban Image ◽  
Better Than

Many vegetation indices have been proposed over last decades made specialists search for the most suitable vegetation index for a given remote sensing application. Measuring the Quality of Place (QOP) is a hard task since it involves both physical and socio-economic dimensions. Being one of the major land use categories, urban vegetation plays a significant role in one‟s judgment for QOP in a neighborhood. Both quantity and quality of the community parks and recreation areas are major determinants of neighborhood attraction. For these reasons, detection of urban vegetation cover has been one of the important implication areas of urban image classification techniques. “Transformed Difference Vegetation Index (TDVI) developed by Bannari et al. (2002), is tested in a previous work where the index has performed better than NDVI and SAVI. In that work, a comparative study between TDVI, SAVI and NDVI for estimating vegetation cover in urban environment from the Indian Remote Sensing Satellite (IRS-1D) imagery has been conducted. The validation of the obtained results according to the ground truth showed that the TDVI is an excellent tool for vegetation cover monitoring in urban environment. It does not saturate like NDVI or SAVI, it shows an excellent linearity as a function of the rate of vegetation cover. This paper adds on the previous work by analyzing the performance of TDVI in urban image classification. Results indicate that, the performance of TDVI in urban image classification is better than NDVI and SAVI. The new index not only differentiates the urban vegetation cover better but also helps to minimize the error in classifying other unclassified pixels of urban categories.

MOSAICITY OF THE VEGETATION COVER OF THE KOCHUBEY BIOSPHERE STATION PASTURES

1970 ◽  
pp. 40-42
Author(s):  
М. А. Babaeva ◽  
S. V. Osipova
Keyword(s):  
Plant Species ◽  
Vegetation Cover ◽  
Cynodon Dactylon ◽  
Plant Cover ◽  
Avena Fatua ◽  
Living Environment ◽  
Anthropogenic Factors ◽  
Indigenous Species ◽  
Fodder Plants ◽  
Falcaria Vulgaris

The regularities of changes in the resistance of different groups of fodder plants to adverse conditions were studied. This is due to the physiological properties that allow them to overcome the harmful effects of the environment. As a result of research species - plant groups with great adaptive potential to the harsh continental semi-desert conditions were identified. Monitoring observation and experimental studies showed too thin vegetation cover as a mosaic, consisting of perennial xerophytic herbs and semishrubs, sod grasses, saltwort and wormwood, as well as ephemera and ephemeroids under the same environmental conditions, depending on various climatic and anthropogenic factors. This is due to the inability or instability of plant species to aggressive living environment. It results in horizontal heterogeneity of the grass stand, division into smaller structures, and mosaic in the vegetation cover of the Kochubey biosphere station. The relative resistance to moderate stress was identified in the following species from fodder plants Agropyron cristatum, A. desertorum, Festuca valesiaca, Cynodon dactylon, Avena fatua; as for strong increasing their abundance these are poorly eaten plant species Artemisia taurica, Atriplex tatarica, Falcaria vulgaris, Veronica arvensis, Arabidopsis thaliana and other. On the site with an increasing pressure in the herbage of phytocenoses the number of xerophytes of ruderal species increases and the spatial structure of the vegetation cover is simplified. In plant communities indigenous species are replaced by adventive plant species. The mosaic of the plant cover of phytocenoses arises due to the uneven distribution in the space of environmental formation, i.e. an edificatory: Salsola orientalis, S. dendroides, Avena fatua, Cynodon dactylon, Artemisia taurica, A. lercheanum, Xanthium spinosum, Carex pachystyli, under which the remaining components of the community adapt. Based on the phytocenotic indicators of pasture phytocenoses it can be concluded that the vegetation cover is in the stage of ecological stress and a decrease in the share of fodder crops and an increase in the number of herbs indicates this fact.

scholarly journals Mental Health, Greenness, and Nature Related Behaviors in the Adult Population of Stockholm County during COVID-19-Related Restrictions

2021 ◽  
Vol 18 (6) ◽  
pp. 3303
Author(s):  
Mare Lõhmus ◽  
Cecilia U. D. Stenfors ◽  
Tomas Lind ◽  
André Lauber ◽  
Antonios Georgelis
Keyword(s):  
Mental Health ◽  
Online Survey ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Adult Population ◽  
Well Being ◽  
Stockholm County ◽  
Cognitive Stress ◽  
Symptoms Of Depression ◽  
International Data

International data suggest that exposure to nature is beneficial for mental health and well-being. The restrictions related to the COVID-19 pandemic have created a setting that allows us to investigate the importance of greenness exposure on mental health during a period of increased isolation and worry. Based on 2060 responses from an online survey in Stockholm County, Sweden, we investigated: (1) whether the COVID-19 pandemic changed peoples’ lifestyle and nature-related habits, and (2) if peoples’ mental health differed depending on their exposure to greenness. Neighborhood greenness levels were quantified by using the average normalized difference vegetation index (NDVI) within 50 m, 100 m, 300 m, and 500 m buffers surrounding the participant’s place of residence. We found that the number of individuals that reported that they visited natural areas “often” was significantly higher during the pandemic than before the pandemic. Higher levels of greenness surrounding one’s location of residence were in general associated with higher mental health/well-being and vitality scores, and less symptoms of depression, anxiety, and perceived and cognitive stress, after adjustments for demographic variables and walkability. In conclusion, the results from the present study provided support to the suggestion that contact with nature may be important for mental health in extreme circumstances.

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Annually Urban Fractional Vegetation Cover Dynamic Mapping in Hefei, China (1999–2018)

2021 ◽  
Vol 13 (11) ◽  
pp. 2126
Author(s):  
Yuliang Wang ◽  
Mingshi Li
Keyword(s):  
Standard Deviation ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Dynamic Range ◽  
Dynamic Change ◽  
Estimation Model ◽  
Sparse Vegetation ◽  
Fractional Vegetation Cover ◽  
Dynamic Mapping ◽  
Multi Temporal

Vegetation measures are crucial for assessing changes in the ecological environment. Fractional vegetation cover (FVC) provides information on the growth status, distribution characteristics, and structural changes of vegetation. An in-depth understanding of the dynamic changes in urban FVC contributes to the sustainable development of ecological civilization in the urbanization process. However, dynamic change detection of urban FVC using multi-temporal remote sensing images is a complex process and challenge. This paper proposed an improved FVC estimation model by fusing the optimized dynamic range vegetation index (ODRVI) model. The ODRVI model improved sensitivity to the water content, roughness degree, and soil type by minimizing the influence of bare soil in areas of sparse vegetation cover. The ODRVI model enhanced the stability of FVC estimation in the near-infrared (NIR) band in areas of dense and sparse vegetation cover through introducing the vegetation canopy vertical porosity (VCVP) model. The verification results confirmed that the proposed model had better performance than typical vegetation index (VI) models for multi-temporal Landsat images. The coefficient of determination (R2) between the ODRVI model and the FVC was 0.9572, which was 7.4% higher than the average R2 of other typical VI models. Moreover, the annual urban FVC dynamics were mapped using the proposed improved FVC estimation model in Hefei, China (1999–2018). The total area of all grades FVC decreased by 33.08% during the past 20 years in Hefei, China. The areas of the extremely low, low, and medium grades FVC exhibited apparent inter-annual fluctuations. The maximum standard deviation of the area change of the medium grade FVC was 13.35%. For other grades of FVC, the order of standard deviation of the change ratio was extremely low FVC > low FVC > medium-high FVC > high FVC. The dynamic mapping of FVC revealed the influence intensity and direction of the urban sprawl on vegetation coverage, which contributes to the strategic development of sustainable urban management plans.

scholarly journals Geospatial analysis of wetlands based on land use/land cover dynamics using remote sensing and GIS in Sindh, Pakistan

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110261
Author(s):  
Hamza Islam ◽  
Habibuulah Abbasi ◽  
Ahmed Karam ◽  
Ali Hassan Chughtai ◽  
Mansoor Ahmed Jiskani
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Kappa Statistics ◽  
Natural Ecosystem ◽  
Land Use Land Cover ◽  
Dry Land ◽  
Lulc Changes ◽  
Manchar Lake

In this study, the Land Use/Land Cover (LULC) change has been observed in wetlands comprises of Manchar Lake, Keenjhar Lake, and Chotiari Reservoir in Pakistan over the last four decades from 1972 to 2020. Each wetland has been categorized into four LULC classes; water, natural vegetation, agriculture land, and dry land. Multitemporal Landsat satellite data including; Multi-Spectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager (OLI) images were used for LULC changes evaluation. The Supervised Maximum-likelihood classifier method is used to acquire satellite imagery for detecting the LULC changes during the whole study period. Soil adjusted vegetation index technique (SAVI) was also used to reduce the effects of soil brightness values for estimating the actual vegetation cover of each study site. Results have shown the significant impact of human activities on freshwater resources by changing the natural ecosystem of wetlands. Change detection analysis showed that the impacts on the land cover affect the landscape of the study area by about 40% from 1972 to 2020. The vegetation cover of Manchar Lake and Keenjhar Lake has been decreased by 6,337.17 and 558.18 ha, respectively. SAVI analysis showed that soil profile is continuously degrading which vigorously affects vegetation cover within the study area. The overall classification accuracy and Kappa statistics showed an accuracy of >90% for all LULC mapping studies. This work demonstrates the LULC changes as a critical monitoring basis for ongoing analyses of changes in land management to enable decision-makers to establish strategies for effectively using land resources.

Change on detection of vegetation cover and soil salinity using GIS technique in Diyala Governorate, Iraq

2021 ◽  
Vol 30 (1) ◽  
pp. 148-158
Author(s):  
Haneen Adeeb ◽  
Yaseen Al-Timimi
Keyword(s):  
Soil Salinity ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Inverse Correlation ◽  
Salinity Changes ◽  
Gis Technique ◽  
Salinity Index ◽  
Remote Sensing Techniques ◽  
Strong Inverse Correlation

Soil salinity is one of the most important problems of land degradation, that threatening the environmental, economic and social system. The aim of this study to detect the changes in soil salinity and vegetation cover for Diyala Governorate over the period from 2005 to 2020, through the use of remote sensing techniques and geographic information system. The normalized difference vegetation index (NDVI) and salinity index (SI) were used, which were applied to four of the Landsat ETM+ and Landsat OLI satellite imagery. The results showed an increase in soil salinity from 7.27% in the period 2005–2010 to 27.03% in 2015–2020, as well as an increase in vegetation from 10% to 24% in the same period. Also the strong inverse correlation between the NDVI and the SI showed that vegetation is significantly affected and directly influenced by soil salinity changes

Mapping urban vegetation cover using WorldView-2 imagery

2012 ◽  
Author(s):  
François Cavayas ◽  
Yuddy Ramos ◽  
André Boyer
Keyword(s):  
Vegetation Cover ◽  
Urban Vegetation
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