Measuring Land Cover Change in Seremban, Malaysia Using NDVI Index

Aburas, Maher Milad; Abdullah, Sabrina Ho; Ramli, Mohammad Firuz; Ash’aari, Zulfa Hanan

doi:10.1016/j.proenv.2015.10.043

Cited by 89 publications

(48 citation statements)

References 5 publications

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“…This implies vegetation cover was decreased and non-vegetated areas increased during the study period mainly due to the increased rate of cultivated lands and built-up areas at expense of vegetated lands. Consistent with this result, study conducted by Aburas et al (2015) in Malaysia using NDVI found that vegetation cover was decreased and non-vegetated areas increased during 1990 and 2010. The socio-demographic data analysis showed that massive population resettlement and high rate of population growth exerts pressure on land resources of the area.…”

Section: Discussionsupporting

confidence: 77%

Impact of resettlement scheme on vegetation cover and its implications on conservation in Chewaka district of Ethiopia

2020

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Background: Resettlement has been conceived as a viable solution to the continual impoverishment and destitution of Ethiopian rural communities. However, it has considerable impacts on natural resources of the environment at destination areas. This study was carried out to evaluate impact of resettlement scheme on vegetation cover and its implications on conservation in Chewaka district of Ethiopia.

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Section: Discussionsupporting

confidence: 77%

Impact of resettlement scheme on vegetation cover and its implications on conservation in Chewaka district of Ethiopia

2020

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“…The NDVI is obviously used to detect any land cover changes caused by human activities like construction and other developmental projects (Aburas et al, 2015;Ahmad and Sharif, 2016). Moreover, NDVI also had been used broadly to analyse the spatio-temporal changes of vegetation coverage (Statistic Malaysia, 2014).…”

Section: Introductionmentioning

confidence: 99%

Urban Vegetation Classification With Ndvi Threshold Value Method With Very High Resolution (Vhr) Pleiades Imagery

Hashim

Latif

Adnan

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

132

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Abstract. Recently the sensing data for urban mapping used is in high demand together with the accessible of very high resolution (VHR) satellite data such as Worldview and Pleiades. This article presents the use of very high resolution (VHR) remote sensing data for urban vegetation mapping. The research objectives were to assess the use of Pleiades imagery to extricate the data of urban vegetation in urban area of Kuala Lumpur. Normalized Difference Vegetation Index (NDVI) were employs with VHR data to find Vegetation Index for classification process of vegetation and non-vegetation classes. Land use classes are easily determined by computing their Normalized Difference Vegetation Index for Land use land cover classification. Maximum likelihood was conducted for the classification phase. NDVI were extracted from the imagery to assist the process of classification. NDVI method is use by referring to its features such as vegetation at different NDVI threshold values. The result showed three classes of land cover that consist of low vegetation, high vegetation and non-vegetation area. The accuracy assessment gained was then being implemented using the visual interpretation and overall accuracy achieved was 70.740% with kappa coefficient of 0.5. This study gained the proposed threshold method using NDVI value able to identify and classify urban vegetation with the use of VHR Pleiades imagery and need further improvement when apply to different area of interest and different land use land cover characteristics. The information achieved from the result able to help planners for future planning for conservation of vegetation in urban area.

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“…It is highly frequented in remote sensing and photogrammetry, in agricultural sciences for example vegetable covering of a given territory [3] [21]. NDVI, normalised difference vegetable index supplemented by RTK signal make it possible to analyze agronomic measurements [15]. RTK is capable of being used in the case of industrial facilities or monuments analyzis [19].…”

Section: Rtk -Real Time Kinematic Surveymentioning

confidence: 99%

On-Board Diagnostic-based Positioning as an Additional Information Source of Driver Assistant Systems

2019

APH

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Nowadays the role of driver assistant systems is becoming more and more pertinent in the vehicle industry. The increasing automation level presents opportunity to involve the driver in any kind of network such as network among vehicles (V2X) and into vehicle and infrastructure connections. The essence of automation in case of the vehicle industry is to facilitate for the vehicle to provide services based on multi-information sources to help the driver because in modern transport systems the most cardinal criteria are environment friendly, plannable, cost efficient and safety travel. Thus, the stability of data transport plays the key role in case of connected vehicles. The following sections will present an opportunity in a detailed way to determine the vehicle's position relying on the vehicle's On-Board Diagnostic system based on the developed algorithm and will show how this method can help the driver assistant system's reliable operation as well.

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Measuring Land Cover Change in Seremban, Malaysia Using NDVI Index

Cited by 89 publications

References 5 publications

Impact of resettlement scheme on vegetation cover and its implications on conservation in Chewaka district of Ethiopia

Impact of resettlement scheme on vegetation cover and its implications on conservation in Chewaka district of Ethiopia

Urban Vegetation Classification With Ndvi Threshold Value Method With Very High Resolution (Vhr) Pleiades Imagery

On-Board Diagnostic-based Positioning as an Additional Information Source of Driver Assistant Systems

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