Spectral Characteristics and Mapping of Rice Fields using Multi-Temporal Landsat and MODIS Data: A Case of District Narowal

1
Dr. Farooq Ahmad
Dr. Farooq Ahmad
2
Farooq Ahmad
Farooq Ahmad
3
Qurat-ul-ain Fatima
Qurat-ul-ain Fatima
4
Hira Jannat Butt
Hira Jannat Butt
5
Shahid Ghazi
Shahid Ghazi
6
Sajid Rashid Ahmad
Sajid Rashid Ahmad
7
Ijaz Ahmad
Ijaz Ahmad
8
Shafeeq-Ur-Rehman
Shafeeq-Ur-Rehman
9
Rao Mansor Ali Khan
Rao Mansor Ali Khan
10
Abdul Raoof
Abdul Raoof
11
Samiullah Khan
Samiullah Khan
12
Farkhanda Akmal
Farkhanda Akmal
13
Kashif Shafique
Kashif Shafique
1 University of the Punjab, New Campus, Lahore, Pakistan

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Spectral Characteristics and Mapping of Rice Fields using Multi-Temporal Landsat and MODIS Data: A Case of District Narowal Banner
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Availability of remote sensed data provides powerful access to the spatial and temporal information of the earth surface. Real-time earth observation data acquired during a cropping season can assist in assessing crop growth and development performance. As remote sensed data is generally available at large scale, rather than at field-plot level, use of this information would help to improve crop management at broad-scale. Utilizing the Landsat TM/ETM+ ISODATA clustering algorithm and MODIS (Terra) the normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) datasets allowed the capturing of relevant rice cropping differences. In this study, we tried to analyze the MODIS (Terra) EVI/NDVI (February, 2000 to February, 2013) datasets for rice fractional yield estimation in Narowal, Punjab province of Pakistan. For large scale applications, time integrated series of EVI/NDVI, 250-m spatial resolution offer a practical approach to measure crop production as they relate to the overall plant vigor and photosynthetic activity during the growing season. The required data preparation for the integration of MODIS data into GIS is described with a focus on the projection from the MODIS/Sinusoidal to the national coordinate systems. However, its low spatial resolution has been an impediment to researchers pursuing more accurate classification results and will support environmental planning to develop sustainable land-use practices. These results have important implications for parameterization of land surface process models using biophysical variables estimated from remotely sensed data and assist for forthcoming rice fractional yield assessment.

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Funding

No external funding was declared for this work.

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The authors declare no conflict of interest.

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Dr. Farooq Ahmad. 2014. \u201cSpectral Characteristics and Mapping of Rice Fields using Multi-Temporal Landsat and MODIS Data: A Case of District Narowal\u201d. Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 14 (GJHSS Volume 14 Issue B6): .

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GJHSS Volume 14 Issue B6
Pg. 35- 60
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Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

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v1.2

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September 26, 2014

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English

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Availability of remote sensed data provides powerful access to the spatial and temporal information of the earth surface. Real-time earth observation data acquired during a cropping season can assist in assessing crop growth and development performance. As remote sensed data is generally available at large scale, rather than at field-plot level, use of this information would help to improve crop management at broad-scale. Utilizing the Landsat TM/ETM+ ISODATA clustering algorithm and MODIS (Terra) the normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) datasets allowed the capturing of relevant rice cropping differences. In this study, we tried to analyze the MODIS (Terra) EVI/NDVI (February, 2000 to February, 2013) datasets for rice fractional yield estimation in Narowal, Punjab province of Pakistan. For large scale applications, time integrated series of EVI/NDVI, 250-m spatial resolution offer a practical approach to measure crop production as they relate to the overall plant vigor and photosynthetic activity during the growing season. The required data preparation for the integration of MODIS data into GIS is described with a focus on the projection from the MODIS/Sinusoidal to the national coordinate systems. However, its low spatial resolution has been an impediment to researchers pursuing more accurate classification results and will support environmental planning to develop sustainable land-use practices. These results have important implications for parameterization of land surface process models using biophysical variables estimated from remotely sensed data and assist for forthcoming rice fractional yield assessment.

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Spectral Characteristics and Mapping of Rice Fields using Multi-Temporal Landsat and MODIS Data: A Case of District Narowal

Farooq Ahmad
Farooq Ahmad
Qurat-ul-ain Fatima
Qurat-ul-ain Fatima
Hira Jannat Butt
Hira Jannat Butt
Shahid Ghazi
Shahid Ghazi
Sajid Rashid Ahmad
Sajid Rashid Ahmad
Ijaz Ahmad
Ijaz Ahmad
Shafeeq-Ur-Rehman
Shafeeq-Ur-Rehman
Rao Mansor Ali Khan
Rao Mansor Ali Khan
Abdul Raoof
Abdul Raoof
Samiullah Khan
Samiullah Khan
Farkhanda Akmal
Farkhanda Akmal
Kashif Shafique
Kashif Shafique

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