Feature Extraction using Normalized Difference Vegetation Index (NDVI): A Case Study of Jabalpur City

Bhandari, Ashish Kumar; Kumar, Arun; Singh, Gagandeep

doi:10.1016/j.protcy.2012.10.074

Cited by 268 publications

(152 citation statements)

References 14 publications

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“…Multi spectral analysis is a way to manage urban areas and perform municipal planning. In case of a disaster, NDVI is a great tool to facilitate intervention for humanitarian help [65].…”

Section: The Normalized Difference Vegetation Index (Ndvi)mentioning

confidence: 99%

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Rhezali¹,

Lahlali

2017

J. Imaging

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Nitrogen (N) is one of the most limiting factors for maize (Zea mays L.) production worldwide. Over-fertilization of N may decrease yields and increase NO 3 − contamination of water.However, low N fertilization will decrease yields. The objective is to optimize the use of N fertilizers, to excel in yields and preserve the environment. The knowledge of factors affecting the mobility of N in the soil is crucial to determine ways to manage N in the field. Researchers developed several methods to use N efficiently relying on agronomic practices, the use of sensors and the analysis of digital images. These imaging sensors determine N requirements in plants based on changes in Leaf chlorophyll and polyphenolics contents, the Normalized Difference Vegetation Index (NDVI), and the Dark Green Color index (DGCI). Each method revealed limitations and the scope of future research is to draw N recommendations from the Dark Green Color Index (DGCI) technology. Results showed that more effort is needed to develop tools to benefit from DGCI.

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“…Multi spectral analysis is a way to manage urban areas and perform municipal planning. In case of a disaster, NDVI is a great tool to facilitate intervention for humanitarian help [65].…”

Section: The Normalized Difference Vegetation Index (Ndvi)mentioning

confidence: 99%

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Rhezali¹,

Lahlali

2017

J. Imaging

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“…Several studies by Xu (2006), Li et al (2013), Szabo et al (2016), and Gao et al (2016) have been conducted in an attempt to utilize the NDWI as a tool to extract the waterbody content in order to map the land surface water with acceptable results. The NDVI was used to indicate the green vegetation presents in the pixel to classify vegetated and non-vegetated areas (Verrelst et al 2008;Bhandari et al 2012;Pujiono et al 2013). …”

Section: Ndvi and Ndwimentioning

confidence: 99%

Assessment of the successfulness of mangrove plantation program through the use of open source software and freely available satellite

Nursamsi

Komala

2017

Nusantara Biosci

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Nursamsi I, Komala WR.2017. Assessment of the successfulness of mangrove plantation program through the use of open source software and freely available satellite images. Nusantara Bioscience 9: 251-259. Mangrove forest has a major role in the process of human-environment interaction, but almost every mangrove forest in the world is under threat. In Indonesia alone, 25% of South East Asiaâ€™s mangroves are at a risk. The continued decline in mangrove forest induced by anthropogenic activity has made all the stakeholders who have the concern at the mangrove forest preservation worried, including the government. There were several programs have been performed by the government to preserve the mangrove forest. One of the programs was â€œMangrove Rehabilitation Program in three districts: Ciamis, Indramayu, and Subangâ€ held by Forestry Department of West Java Province in 2007. The aims of this study were to assess the changes in mangrove forest area before the program performed and to evaluate the successfulness of the program, using the increasing of mangrove forest area as a parameter. This study was conducted only in Subang and Indramayu Districts of West Java, Indonesia. The assessment was conducted using Landsat 4-5 TM, Landsat 7 ETM+, and Landsat 8 OLI acquired in 1996, 2006, and 2016 respectively. For each image, a supervised classification method was performed using open source GRASS GIS software. The resulting maps were then compared to quantify the changes. Field work activity conducted and confirmed the changes that occurred in the study areas. Our study shows that all of the two districts exhibit successfulness of the plantation program. Ground truth survey confirmed that the successfulness of the plantation program is due to the participation of communities in the area of study. This study also shows that by using open source software and freely available satellite images, the fast, robust, and reliable data as an initial step to monitor both short-term and long-term plantation program can be collected effectively and inexpensively.

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“…Formula: NIR on behalf of the near infrared band, R on behalf of the red band Firstly, the vegetation index NDVI of Tianjin was calculated, and then the vegetation coverage was estimated; It is assumed that the reflected radiation value of the sensor received by the satellite is composed of R and the total reflection radiation value of vegetation and soil (Bhandari and Kumar, et al, 2012),as the formula (2) (1 )…”

Section: Vegetation Coverage Factor Extractionmentioning

confidence: 99%

Soil Erosion Dynamic Detection Based on Remote Sense and GIS Techniques

2017

Revista Tecnica De La Facultad De Ingenieria Universidad Del Zu

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Considering the shortcomings of heavy workload, time-consuming and laborious in common soil erosion observation and experimental methods, Jixian district in Tianjin was selected as the research area in this paper. The multi-factor comprehensive method in the second national soil erosion remote sensing survey is adopted. This paper uses the TM data of 2004 and Landsat-8 data and DEM data in 2015 of this region, according to the Soil Erosion Classification and Grading Standard (SL 190-2007) issued by the Ministry of Water Resources. The soil erosion intensity grading map of two periods in Jixian was obtained and the annual average erosion modulus was calculated. Based on the TM images in 2004 and Landsat-8 data in 2015, DEM data were employed in the study. The results showed that the soil erosion in Jixian district was mildly eroded in the recent ten years, although the average annual erosion modulus has declined, it is still necessary to pay attention to the areas above the strength erosion.

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Feature Extraction using Normalized Difference Vegetation Index (NDVI): A Case Study of Jabalpur City

Cited by 268 publications

References 14 publications

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Nitrogen (N) Mineral Nutrition and Imaging Sensors for Determining N Status and Requirements of Maize

Assessment of the successfulness of mangrove plantation program through the use of open source software and freely available satellite

Soil Erosion Dynamic Detection Based on Remote Sense and GIS Techniques

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