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A. Bala K. S. Rawat A. Misra A. Srivastava

Abstract

This study describes the VIs Vegetation Condition Index in term of vegetation health of wheat crop; with help of LANDSAT-7ETM+ data based NDVI and LAI for Bhiwani District of Haryana states (India) and gave the spatial development pattern of wheat crop in year 2005 over the study area of India. NDVI is found to vary from 0.3 to 0.8. In northern and southern parts of study area NDVI varied from 0.6 to 0.7 but in western part of Bhiwani showed NDVI 0.2 to 0.4 due to fertility of soil and well canal destitution. LAI showed variation from 1 to 6 according
to the health of crop as the same manner of NDVI because LAI VI is NDVI dependent only change the manner of representation of vegetation health, due to this fact relation curve (r2=) between NDVI and LAI of four different growing date of sates are in successively increasing order 0.509, 0.563, 0.577 and 0.719. The study reveals that VIs can be mapped with LANDSAT-7ETM+ through remote sensing, which can be further used for many studies like crop yield or estimating evaptranspiration on regional basis for water management because satellite observations provide better spatial and temporal coverage, the VIs based system will provide efficient tools for monitoring health of crop for improvement of agricultural planning. VIs based monitoring will serve as a prototype in the other parts of the world where ground observations are limited or not available.

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Keywords

Evapotranpiration, Remote Sensing, Vegetation Indices (VIs)

References
Bala, A., Rawat, K. S., Misra, A. K. Srivastava A. (2015). Assessment and Validation of Evapotranspiration using SEBALalgorithm and Lysimeter data of IARI Agricultural Farm, India. Geocarto International, DOI: http://dx.doi.org/10.1080/10106049.2015.1076062.Online: 27 Jul 2015.
Bouman, B.A.M. (1992). Accuracy of estimating the leaf area index from VI derived from crop reflectance characteristics, a simulation study. International Journal of Remote Sensing. 13:3069-3084.
Chaurasia, S., Nigam, R., Bhattacharya, B.K., Sridhar, V.N., Mallick, K., Vyas, S.P., Patel, N.K., Mukherjee, J., Shekhar, C., Kumar, D., Singh, K.R.P., Bairagi, G.D., Purohit, N.L. and Parihar, J.S. (2011). Development of regional wheat VI-LAI models using Resourcesat-1 data. Journal of Earth System Science, 120(6): 1113-1125.
Choudhury, B.J., Ahmed N.U., Idso, S.B., Reginato R.J. and Daughtry, C.S.T. (1994). Relations between evaporation coefficients and VI studied by model simulations. Remote Sensing of Environment. 50:1-17.
Curran, P.J. (1994). Imaging spectrometry. Progress in Physical Geography, 18:247-266.
Curran, P.J. and Milton, E.J. (1983). The relationship between the chlorophyll concentration, LAI and reflectance of a simple vegetation canopy. International Journal of Remote Sensing, 4:247-255.
Gupta, R.K., Prasad, T.S. and Vijayan, D. (2003). Relationship between LAI and NDVI for IRS LISS and Landsat TM bands. National Remote Sensing Agency, Hyderabad-500037, India.
Huete, A.R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25:295-309.
Kumar, R., Shambhavi, S., Kumar, R., Singh, Y.S. and Rawat, K.S. (2013). Evapotranspiration mapping for agricultural water management: An overview. Journal of Applied and Natural Science, 5(2): 522-534.
Layrol, L., Hedoin, E., Lepoutre, D. and François, O. (2000). Matching multispectral yield and images data. Proceedings of the 5th International Conference on Precision Agriculture. Madison, Wisconsin, USA. CD-ROM.
Locke, C.R., Carbone, G.J., Filippi, A.M., Sadler, E.J., Gerwig, B.K. and Evans, D.E. (2000).Using remote sensing and modeling to measure crop biophysical variability. Proceedings of the 5th International Conference on Precision Agriculture. Madison, Wisconsin, USA. CDROM.
Moran, M.S., Inoue, Y. and Barnes, E.M. (1997). Opportunities and limitations for image-based remote sensing in precision crop management. Remote Sensing of Environment. 61:319-346.
Moulin, S., Bondeau, A. and Delecolle, R. (1998). Combining agricultural crop models and satellite observations: from field to regional scales. International Journal of Remote Sensing. 19(6):1021-1036.
Myneni, R.B., Hall, F.G., Sellers, P.J. and Marshak, A.L. (1995). The interpretation of spectral vegetation indexes. IEEE Geoscience and Remote Sensing Society. 33:481–486.
Nagler, P.L., Glenn, E.P., Thompson, T. L. and Huetee, A. (2004). Leaf area index and normalized difference vegetation index as predictors of canopy characteristics and light interception by riparian species on the Lower Colorado River. Agricultural and Forest Meteorology. 125 (1–2):1–17.
Punia S.S., Yadav, D. and Kamboj, B. (2009). Weed flora of garlic in Haryana. Indian Journal of Weed Science. 41:179-181
Rawat, K.S., Mishra, A.K. and Kumar, R. (2012). Vegetation Condition Index pattern (2002-2007) over Indian Agro- Climate Regions, using of GIS and SPOT Sensor NDVI Data. Journal of Applied and Natural Science, 4:34-38.
Rosenberg, N.J., Blad, B.L. and Verma S.B. (1983). Microclimate: The biological environment. New York: John Wiley & Sons, 459-464.
Running, S.W. (1990). Estimating primary productivity by combining remote sensing with ecosystem simulation. In Remote Sensing of Biosphere Functioning, 65–86.
Sharma, M.P., Yadav, K., Kaur, K., Prawasi, R. and Singh A. (2014). Geospatial Approach for Cropping System Analysis, A Case Study of Bhiwani District, Haryana. International Journal of Science & Engineering and Technology Research, 3:424-429.
Shunlin, L. (2004). Quntitative remote sensing of land surfaces. Published by john wiley &sons,inc. Hoboken, new jersy
Werner, S., Dölling, S., Jarfe, A., Kühn, J., Pauly, J. and Roth, R. (2000). Deriving maps of yield-potentials with crop models, site information and remote sensing. Proceedings of the 5th International Conference on Precision Agriculture, Madison, Wisconsin, USA. CDROM.
Wiegand, C.L., Richardson, A.J., Escobar, D.E. and Gerbermann, A.H. (1991).VI in crop assessments. Remote Sensing of Environment, 35:105-119.
Yang, C. and Everitt, J.H. (2000). Relationships between yield monitor data and airborne multispectral digital imagery. Proceedings of the 5th International Conference on Precision Agriculture. Madison, Wisconsin, USA. CD-ROM.
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How to Cite
Bala, A., Rawat, K. S., Misra, A., & Srivastava, A. (2015). Vegetation indices mapping for Bhiwani district of Haryana (India) through LANDSAT-7ETM+ and remote sensing techniques. Journal of Applied and Natural Science, 7(2), 874-879. https://doi.org/10.31018/jans.v7i2.699
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