Dr. Felix Kogan Profile

Dr. Felix Kogan

at National Oceanic and Atmospheric Administration

SPIE Involvement:

Author

SPIE Journal Paper | 12 April 2018 Open Access

Space-based vegetation health for wheat yield modeling and prediction in Australia

Felix Kogan, Wei Guo, Wenze Yang, Shannon Harlan

JARS, Vol. 12, Issue 02, 026002, (April 2018) https://doi.org/10.1117/12.10.1117/1.JRS.12.026002

KEYWORDS: Vegetation, Satellites, Data modeling, Climatology, Agriculture, Thermal modeling, Atmospheric modeling, Ecosystems, Near infrared, Radiometry

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Proceedings Article | 19 September 2016 Presentation + Paper

Using remote sensing satellite data and artificial neural network for prediction of potato yield in Bangladesh

Kawsar Akhand, Mohammad Nizamuddin, Leonid Roytman, Felix Kogan

Proceedings Volume 9975, 997508 (2016) https://doi.org/10.1117/12.2237214

KEYWORDS: Artificial neural networks, Agriculture, Vegetation, Remote sensing, Satellites, Neurons, Data modeling, Neural networks, Climatology, Mathematical modeling

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Proceedings Article | 4 September 2015 Paper

Using artificial neural network and satellite data to predict rice yield in Bangladesh

Kawsar Akhand, Mohammad Nizamuddin, Leonid Roytman, Felix Kogan, Mitch Goldberg

Proceedings Volume 9610, 96100E (2015) https://doi.org/10.1117/12.2186261

KEYWORDS: Neurons, Gold, Neural networks, Data modeling, Agriculture, Artificial neural networks, Satellites, Remote sensing, Vegetation, Error analysis

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Proceedings Article | 3 June 2015 Paper

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

Mohammad Nizamuddin, Kawsar Akhand, Leonid Roytman, Felix Kogan, Mitch Goldberg

Proceedings Volume 9488, 94880O (2015) https://doi.org/10.1117/12.2086186

KEYWORDS: Gold, Agriculture, Vegetation, Data modeling, Remote sensing, Climatology, Statistical analysis, Dysprosium, Climate change, Satellites

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Proceedings Article | 24 September 2013 Paper

Early warning of malaria at Bikaner, Rajasthan in India using AVHRR-based satellite data

Leonid Roytman, Mohammad Nizamuddin, Kawsar Akhand, Felix Kogan, Mitchell Goldberg

Proceedings Volume 8871, 88710F (2013) https://doi.org/10.1117/12.2022405

KEYWORDS: Vegetation, Dysprosium, Satellites, Error analysis, Climatology, Radiometry, Humidity, Near infrared, Statistical analysis, Earth observing sensors

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Proceedings Article | 29 May 2013 Paper

Optical remote sensing a potential tool for forecasting malaria in Orissa, India

Mohammad Nizamuddin, Kawsar Akhand, Leonid Roytman, Felix Kogan, Mitch Goldberg

Proceedings Volume 8723, 87231A (2013) https://doi.org/10.1117/12.2014702

KEYWORDS: Vegetation, Satellites, Dysprosium, Remote sensing, Climatology, Environmental monitoring, Error analysis, Humidity, Radiometry, Statistical analysis

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Proceedings Article | 16 September 2011 Paper

Statistical normalization of brightness temperature records from the NOAA/AVHRR

Marco Vargas, Felix Kogan, Wei Guo

Proceedings Volume 8156, 81560Y (2011) https://doi.org/10.1117/12.892556

KEYWORDS: Satellites, Vegetation, Aerosols, Atmospheric particles, Sensors, Clouds, Atmospheric sensing, Earth's atmosphere, Infrared radiation, Infrared sensors

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Proceedings Article | 12 August 2010 Paper

Potential of using remote sensing for forecasting malaria in Tripura, India

Mohammad Nizamuddin, Leonid Roytman, Mitch Goldberg, Felix Kogan

Proceedings Volume 7809, 78090G (2010) https://doi.org/10.1117/12.861034

KEYWORDS: Satellites, Vegetation, Remote sensing, Error analysis, Statistical analysis, Meteorological satellites, Data centers, Dysprosium, Radiometry, Environmental sensing

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Proceedings Article | 1 May 2009 Paper

Satellite-observed sensitivity of weather condition for predicting malaria vector distribution in Bandarban district, Bangladesh

Mohammad Nizamuddin, Atiqur Rahman, Leonid Roytman, Felix Kogan, Al Powell, Mitch Goldberg

Proceedings Volume 7312, 73120T (2009) https://doi.org/10.1117/12.818316

KEYWORDS: Satellites, Error analysis, Dysprosium, Vegetation, Meteorological satellites, Climatology, Statistical analysis, Data modeling, Statistical modeling, Near infrared

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Proceedings Article | 14 October 2008 Paper

Removing long-term errors from the AVHRR observation based on Normalized Difference Vegetation Index (NDVI)

Md. Rahman, Leonid Roytman, Atiqur Rahman, Felix Kogan, Runa Jesmin

Proceedings Volume 7110, 71101G (2008) https://doi.org/10.1117/12.799900

KEYWORDS: Satellites, Vegetation, Data corrections, Neodymium, Ecosystems, Sensors, Climatology, Climate change, Error analysis, Radiometry

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Proceedings Article | 10 September 2008 Paper

Improvements of numerical weather predictions using a new AVHRR green vegetation fraction dataset

Yuhong Tian, Cheng-Zhi Zou, Kenneth Mitchell, Vince Wong, Felix Kogan, Le Jiang, Xiwu Zhan

Proceedings Volume 7085, 70850N (2008) https://doi.org/10.1117/12.795316

KEYWORDS: Climatology, Data modeling, Vegetation, Computer simulations, Humidity, Temperature metrology, Soil science, Skin, Analytical research, Solar radiation models

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Proceedings Article | 22 February 2008 Paper

Removing long-term errors from AVHRR-based brightness temperature (BT)

Mohammed Rahman, Leonid Roytman, Felix Kogan

Proceedings Volume 6749, 674917 (2008) https://doi.org/10.1117/12.737507

KEYWORDS: Satellites, Standards development, Error analysis, Sensors, Calibration, Environmental sensing, Climatology, Vegetation, Earth observing sensors, Environmental monitoring

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Proceedings Article | 15 December 2006 Paper

Early drought detection, monitoring, and assessment of crop losses from space: global approach

Felix Kogan

Proceedings Volume 6412, 641209 (2006) https://doi.org/10.1117/12.693580

KEYWORDS: Vegetation, Satellites, Environmental sensing, Climatology, Data modeling, Agriculture, Environmental monitoring, Error analysis, Statistical modeling, Atmospheric modeling

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Proceedings Article | 12 December 2006 Paper

Application of various satellite derived information for drought detection and calculation of water balance

Katarzyna Dabrowska-Zielinska, Maria Gruszczynska, Felix Kogan, Wanda Kowalik, Iwona Malek, Stanislaw Lewinski

Proceedings Volume 6412, 64120X (2006) https://doi.org/10.1117/12.693754

KEYWORDS: Vegetation, Satellites, Soil science, Agriculture, Atmospheric modeling, Data modeling, Meteorology, Remote sensing, Temperature metrology, Environmental sensing

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Proceedings Article | 12 December 2006 Paper

Evaluation of GVI-based indices for drought early warning in India

A. Jeyaseelan, Felix Kogan

Proceedings Volume 6412, 64120S (2006) https://doi.org/10.1117/12.693929

KEYWORDS: Vegetation, Satellites, Agriculture, Remote sensing, Atmospheric monitoring, Databases, Spatial resolution, Clouds, Solar radiation, Decision support systems

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Drought is the major disaster, which occurs in some part of India every year due to monsoon variability. India has established satellite based National Agricultural Drought Assessment and Monitoring System (NADAMS), at National Remote Sensing Agency, Department of Space since 1987. NADAMS provides near real time monitoring and early warning of drought conditions at National level using NOAA AVHRR and at regional level using IRS WiFS and AWiFS data. ISRO-NASA-NOAA science cooperation project has been initiated during 2005 for development of satellite based decision support drought monitor system in India. Initially, the evaluation of GVI based indices for drought early warning in India was taken up. The study was carried out over five small regions each covering part of a district and over five large regions each covering few districts in each state of Gujarat, Maharashtra and Rajasthan states and the result of the study is presented in this paper. The weekly GVI based indices such as Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI) for the period from 1991-2004 over 5 small regions covering part of districts namely Banaskantha district of Gujarat state to represent Bajra crop, Surendra nagar district of Gujarat state to represent Cotton crop, Nasik district of Maharashtra to represent Bajra crop, Bhandara district to represent Rice crop and Akola district of Maharastra to represent Jowar crop was selected. The weekly GVI based indices over 5 large regions with larger database from 1981 to 2004 covering few districts of Rajasthan state to represent winter wheat and few districts of Maharashtra state to represent Jowar, Rice and Cotton crops were selected. The comparison of seasonal average VCI, TCI and VHI with the corresponding crops yield over 5 small regions indicate better regression coefficient for VHI than VCI or TCI. The comparison over 5 large regions covering larger data base from 1982-2004 indicate better regression coefficient for VCI than VHI or TCI. Results of the study suggests over smaller region, the VCI and TCI combined VHI indices relates better with crop yields, whereas over larger region, the VCI itself relates better with crop yields than with TCI or the VCI and TCI combined VHI.

Proceedings Article | 30 November 2006 Paper

NOAA-ISRO joint science projects on Earth observation system science, technology, and applications for societal benefits

A. Powell, V. Jayarman, S. Kondragunta, F. Kogan, R. Kuligowski, E. Maturi

Proceedings Volume 6407, 640704 (2006) https://doi.org/10.1117/12.694020

KEYWORDS: Satellites, Algorithm development, Aerosols, Vegetation, Meteorological satellites, Meteorology, Environmental sensing, Atmospheric modeling, Sensors, Climatology

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India and the United States of America (U.S.A.) held a joint conference from June 21-25, 2004 in Bangalore, India to strengthen and expand cooperation in the area of space science, applications, and commerce. Following the recommendations in the joint vision statement released at the end of the conference, the National Oceanic and Atmospheric Administration (NOAA) and the Indian Space and Reconnaissance Organization (ISRO) initiated several joint science projects in the area of satellite product development and applications. This is an extraordinary step since it concentrates on improvements in the data and scientific exchange between India and the United States, consistent with a Memorandum of Understanding (MOU) signed by the two nations in 1997. With the relationship between both countries strengthening with President Bush's visit in early 2006 and new program announcements between the two countries, there is a renewed commitment at ISRO and other Indian agencies and at NOAA in the U.S. to fulfill the agreements reached on the joint science projects. The collaboration is underway with several science projects that started in 2005 providing initial results. NOAA and ISRO agreed that the projects must promote scientific understanding of the satellite data and lead to a satellite-based decision support systems for disaster and public health warnings. The projects target the following areas: --supporting a drought monitoring system for India --improving precipitation estimates over India from Kalpana-1 --increasing aerosol optical depth measurements and products over India --developing early indicators of malaria and other vector borne diseases via satellite monitoring of environmental conditions and linking them to predictive models --monitoring sea surface temperature (SST) from INSAT-3D to support improved forecasting of regional storms, monsoon onset and cyclones. The research collaborations and results from these projects will be presented and discussed in the context of India-US cooperation and the Global Earth Observation System of Systems (GEOSS) concept.

Showing 5 of 16 publications

SPIE Conference Volume | 5 December 2006

Disaster Forewarning Diagnostic Methods and Management

Conference Committee Involvement (1)

Disaster Forewarning Diagnostic Methods and Management

13 November 2006 | Goa, India

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