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Wavelet for Predicting Soil Nutrients using Remotely Sensed Satellite Images
by
Viraj A. Gulhane,
Sandeep V. Rode,
Chaitanya B. Pande
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 174 - Number 4 |
| Year of Publication: 2017 |
| Authors: Viraj A. Gulhane, Sandeep V. Rode, Chaitanya B. Pande |
10.5120/ijca2017915385
|
Viraj A. Gulhane, Sandeep V. Rode, Chaitanya B. Pande . Wavelet for Predicting Soil Nutrients using Remotely Sensed Satellite Images. International Journal of Computer Applications. 174, 4 ( Sep 2017), 35-38. DOI=10.5120/ijca2017915385
@article{
10.5120/ijca2017915385,
author = {
Viraj A. Gulhane,
Sandeep V. Rode,
Chaitanya B. Pande
},
title = { Wavelet for Predicting Soil Nutrients using Remotely Sensed Satellite Images },
journal = {
International Journal of Computer Applications
},
issue_date = { Sep 2017 },
volume = { 174 },
number = { 4 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = {
35-38
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume174/number4/28398-2017915385/
},
doi = { 10.5120/ijca2017915385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:21:17.692971+05:30
%A Viraj A. Gulhane
%A Sandeep V. Rode
%A Chaitanya B. Pande
%T Wavelet for Predicting Soil Nutrients using Remotely Sensed Satellite Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 4
%P 35-38
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In country like India, where agricultural economy plays major role, understanding and tracking the soil nutrients are essential. However, the chemical analysis, which determines the nutrient contents of soil, is expensive and time consuming. Hence, we attempt to exploit remote sensing imagery for estimating them. This paper analyzes the correlation between the level of soil nutrients and wavelet decompositions of remote sensing imagery of a particular region. Four renowned wavelet transformations such as Daubechies, Symlet, Biorthogonal and Coiflet are used to represent the image in wavelet domain. Subsequently, here exploit a neural network model to predict the soil nutrient content using the principle wavelet components. Experimental analysis on the prediction accuracy and the correlation measure reveals the suitability of each wavelet transformation of remote sensing imagery in predicting the soil nutrients.
References
- Xuelei Wang., C.M. Mannaerts., Shengtian Yang., Yunfei Gao and Donghai Zheng., “Evaluation of soil nitrogen emissions from riparian zones coupling simple process-oriented models with remote sensing data”, Science of the Total Environment 408, pp. 3310–3318, 2010.
- Kneubuhler, M., Damm, A., Schweiger, A.K., Risch, A.C., Schutz, M. and Schaepman, M.E., “Continuous Fields From Imaging Spectrometer Data for Ecosystem Parameter Mapping and Their Potential for Animal Habitat Assessment in Alpine Regions”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, 29 May 2014.
- Vandana Tomar., Vinay Prasad Mandal., Pragati Srivastava., Shashikanta Patairiya., Kartar Singh., Natesan Ravisankar., Natraj Subash. and Pavan Kumar., “Rice Equivalent Crop Yield Assessment Using MODIS Sensors’ Based MOD13A1-NDVI Data”, IEEE Sensors Journal, vol. 14, no. 10, pp. 3599-3609, October 2014.
- Lin Qiu., Xiaomin Chen. and Jianjun Pan., “In situ measurement of soil macropores by dye tracing and image analysis”, 2013 Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), IEEE, pp. 13 – 17, 12-16 Aug. 2013.
- Zheng Hongbo., Wu Jianping. and Zhang Shan., “Study on the Spatial Variability of Farmland Soil Nutrient Based on the Kriging Interpolation”, International Conference on Artificial Intelligence and Computational Intelligence, 2009. AICI'09, vol. 4, pp. 550 – 555, 7-8 Nov. 2009.
- Lei Chen ; Saileung Ng, “Economic loss of soil erosion in Linyi City”, 2011 IEEE International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE), pp. 259-262, 2011.
- Ustin, L., Asner, G.P., Gamon, J.A., Huemmrich, K.F., Jacquemoud, S., Schaepman, M. and Zarco-Tejada, P., “Retrieval of Quantitative and Qualitative Information about Plant Pigment Systems from High Resolution Spectroscopy”, IEEE International Conference on Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006, pp. 1996 – 1999, July 31 2006-Aug. 4 2006.
- A. Gitelson., M. N. Merzlyak. and O. B. Chivkunova., “Optical properties and nondestructive estimation of anthocyanin content in plant leaves,” Photochem. Photobiol., vol. 74, no. 1, pp. 38–45, Jul. 2001.
- Vina, A. and Gitelson, A.A., “Sensitivity to Foliar Anthocyanin Content of Vegetation Indices Using Green Reflectance”, IEEE on Geoscience and Remote Sensing Letters, vol. 8, no. 3, pp. 464 – 468, May 2011.
- Bach, H. and Mauser, W., “Methods and examples for remote sensing data assimilation in land surface process modeling”, IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 7, Part: 1, pp. 1629- 1637, 2003.
- Lihua Xu. and Deti Xie., “Prediction for Available Nitrogen and Available Phosphorus by Using Hyperspectral Data”, 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE), 1-3 June 2012.
- Peng Lu., Zheng Niu. and Linghao Li., Prediction of Soil Organic Carbon by Hyperspectral Remote Sensing Imagery”, Third Global Congress on Intelligent Systems (GCIS), 2012, pp. 291- 293, 2012.
- Lianqinq Xue, Dan Li, Shuo Huang and Chunlin Wu., "Spatial Variability Analysis on Soil Nitrogen and Phosphorus Experiment Based on Geostatisics”, International Workshop on Education Technology and Training and International Workshop on Geoscience and Remote Sensing, ETT and GRS 2008., Vol. 2, pp. 237 – 240, 2008.
- Nafiseh Ghasemi, Mahmod Reza Sahebi, and Ali Mohammadzadeh, “Biomass Estimation of a Temperate Deciduous Forest Using Wavelet Analysis”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, No. 2, 2013
- David J. Mulla., “Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps”, Biosystems Engineering; Special Issue: Sensing in Agriculture 114, 358 – 371, 2013.
- Amor V.M. Ines., Narendra N. Das., James W. Hansen.and Eni G. Njoku., “Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction”, Remote Sensing of Environment, vol. 138, pp. 149-164, November 2013.
- Elizabeth M. Isenstein. and Mi-Hyun Park., “Assessment of nutrient distributions in Lake Champlain using satellite remote sensing”, Journal of Environmental Sciences, vol. 26, no. 9, pp. 1831-1836, 1 September 2014.
- Qinhong Liao., Jihua Wang., Cunjun Li. and Xiaohe Gu., “Estimation of fluvo-aquic soil organic matter from hyperspectral reflectance by using discrete wavelet transformation”, IEEE 2012 First International Conference on Agro-Geoinformatics (Agro-Geoinformatics), pp. 1-5, 2012
- Heng Dong., Chao Chen., Jinliang Wang., Qiming Qin., Hongbo Jiang., Ning Zhang., Mingchao Liu, “Study on quantitative retrieval of soil nutrients”, 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3330- 3333, 2011.
- Hongyan Chen., Gengxing Zhao., Yinjuan Wang., Long Sui. and Hu Meng., “Discussion on remote sensing estimation of soil nutrient contents”, 2011 International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE), pp. 3072-3075, 2011.
- Cheng – Wen, Chang, David Laird, Maurice J. Mausbach and Charles R.Hurburg Jr., “Near-Infrared Reflectance Spectroscopy – Principal Components Regression Analyses of Soil Properties”, Soil Society of American Journal, vol. 65, no. 2, pp. 480-490, 2001.
- Qiang Ma., Wantai Yu. and Hua Zhou., “The relationship between soil nutrient properties and remote sensing indices in the Phaeozem region of Northeast China”, 2010 IEEE Second International Conference on Computational Intelligence and Natural Computing Proceedings (CINC), vol. 2, pp.109- 112, 2010.
- V.A.Gulhane and S.V.Rode, “Correlation Analysis on Soil Nutrients and Wavelet Decompositions of Satellite Imagery”, Accepted to publish in proceedings of International Conference on Industrial Instrumentation and Control (ICIC 2015), Pune, India
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Computer Science
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Keywords