Holben, B. N. (1986). Characteristics of maximum-value composite images from temporal AVHRR
data. International Journal of Remote Sensing, 7, 1417–1434. https://doi.org/10.1080/
01431168608948945.
Hong, Y., Adler, R. F., Hossain, F., et al. (2007). A first approach to global runoff simulation using
satellite rainfall estimation. Water Resources Research, 43, W08502. https://doi.org/10.1029/
2006WR005739.
Hossain, F. (2006). Towards formulation of a space-borne system for early warning of floods: Can
cost-effectiveness outweigh prediction uncertainty? Natural Hazards, 37, 263–276.
Hossain, F., & Katiyar, N. (2006). Improving flood forecasting in international river basins. Eos,
Transactions American Geophysical Union, 87, 49–54.
Islam, A. S., Bala, S. K., & Haque, M. A. (2010). Flood inundation map of Bangladesh using
MODIS time-series images. Journal of Flood Risk Management, 3, 210–222. https://doi.org/10.
1111/j.1753-318X.2010.01074.x.
Jackson, R. D., Teillet, P. M., Slater, P. N., et al. (1990). Bidirectional measurements of surface
reflectance for view angle corrections of oblique imagery. Remote Sensing of Environment, 32,
189–202.
Jain, S. K., Singh, R. D., Jain, M. K., & Lohani, A. K. (2005). Delineation of flood-prone areas
using remote sensing techniques. Water Resources Management, 19, 333–347. https://doi.org/
10.1007/s11269-005-3281-5.
Jensen, J. R., Rutchey, K., Koch, M. S., & Narumalani, S. (1995). Inland wetland change detection
in the Everglades water conservation area 2A using a time series of normalized remotely sensed
data. Photogrammetric Engineering and Remote Sensing, 61, 199–209.
Jeyaseelan, A. T. (2003). Droughts & floods assessment and monitoring using remote sensing and
GIS. In: Satellite remote sensing and GIS applications in agricultural meteorology. World
Meteorological Organization, Dehra Dun, India. Geneva, Switzerland.
Kang, L., Di, L., Deng, M., et al. (2014). Use of geographically weighted regression model for
exploring spatial patterns and local factors behind NDVI-precipitation correlation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 4530–4538.
https://doi.org/10.1109/JSTARS.2014.2361128.
Knebl, M. R., Yang, Z.-L., Hutchison, K., & Maidment, D. R. (2005). Regional scale flood
modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio
River Basin Summer 2002 storm event. Journal of Environmental Management, 75, 325–336.
Kogan, F. N. (1990). Remote sensing of weather impacts on vegetation in non-homogeneous areas.
International Journal of Remote Sensing, 11, 1405–1419.
Kogan, F. (2002). World droughts in the new millennium from AVHRR-based vegetation health
indices. Eos, Transactions American Geophysical Union, 83, 557–563.
Kogan, F., Gitelson, A., Zakarin, E., et al. (2003). AVHRR-based spectral vegetation index for
quantitative assessment of vegetation state and productivity. Photogrammetric Engineering &
Remote Sensing, 69, 899–906.
Labus, M. P., Nielsen, G. A., Lawrence, R. L., et al. (2002). Wheat yield estimates using multitemporal NDVI satellite imagery. International Journal of Remote Sensing, 23, 4169–4180.
https://doi.org/10.1080/01431160110107653.
Lensky, I. M., & Rosenfeld, D. (1997). Estimation of precipitation area and rain intensity based on
the microphysical properties Retrieved from NOAA AVHRR data. Journal of Applied Meteorology, 36, 234–242. https://doi.org/10.1175/1520-0450(1997)036<0234:EOPAAR>2.0.CO;2.
Lin, L., Di, L., & Yu, E. G. et al. (2016). A review of remote sensing in flood assessment. Tianjing,
China.
Macintosh, H., & Profeti, G. (1995). The use of ERS SAR data to manage flood emergencies at the
smaller scale. In 2nd ERS applications workshop (pp. 243–246). London: European Space
Agency.
Matgen, P., Hostache, R., Schumann, G., et al. (2011). Towards an automated SAR-based flood
monitoring system: Lessons learned from two case studies. Physics and Chemistry of the Earth,
Parts A/B/C, 36, 241–252.
16 Flood Monitoring and Crop Damage Assessment
347
data. International Journal of Remote Sensing, 7, 1417–1434. https://doi.org/10.1080/
01431168608948945.
Hong, Y., Adler, R. F., Hossain, F., et al. (2007). A first approach to global runoff simulation using
satellite rainfall estimation. Water Resources Research, 43, W08502. https://doi.org/10.1029/
2006WR005739.
Hossain, F. (2006). Towards formulation of a space-borne system for early warning of floods: Can
cost-effectiveness outweigh prediction uncertainty? Natural Hazards, 37, 263–276.
Hossain, F., & Katiyar, N. (2006). Improving flood forecasting in international river basins. Eos,
Transactions American Geophysical Union, 87, 49–54.
Islam, A. S., Bala, S. K., & Haque, M. A. (2010). Flood inundation map of Bangladesh using
MODIS time-series images. Journal of Flood Risk Management, 3, 210–222. https://doi.org/10.
1111/j.1753-318X.2010.01074.x.
Jackson, R. D., Teillet, P. M., Slater, P. N., et al. (1990). Bidirectional measurements of surface
reflectance for view angle corrections of oblique imagery. Remote Sensing of Environment, 32,
189–202.
Jain, S. K., Singh, R. D., Jain, M. K., & Lohani, A. K. (2005). Delineation of flood-prone areas
using remote sensing techniques. Water Resources Management, 19, 333–347. https://doi.org/
10.1007/s11269-005-3281-5.
Jensen, J. R., Rutchey, K., Koch, M. S., & Narumalani, S. (1995). Inland wetland change detection
in the Everglades water conservation area 2A using a time series of normalized remotely sensed
data. Photogrammetric Engineering and Remote Sensing, 61, 199–209.
Jeyaseelan, A. T. (2003). Droughts & floods assessment and monitoring using remote sensing and
GIS. In: Satellite remote sensing and GIS applications in agricultural meteorology. World
Meteorological Organization, Dehra Dun, India. Geneva, Switzerland.
Kang, L., Di, L., Deng, M., et al. (2014). Use of geographically weighted regression model for
exploring spatial patterns and local factors behind NDVI-precipitation correlation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 4530–4538.
https://doi.org/10.1109/JSTARS.2014.2361128.
Knebl, M. R., Yang, Z.-L., Hutchison, K., & Maidment, D. R. (2005). Regional scale flood
modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio
River Basin Summer 2002 storm event. Journal of Environmental Management, 75, 325–336.
Kogan, F. N. (1990). Remote sensing of weather impacts on vegetation in non-homogeneous areas.
International Journal of Remote Sensing, 11, 1405–1419.
Kogan, F. (2002). World droughts in the new millennium from AVHRR-based vegetation health
indices. Eos, Transactions American Geophysical Union, 83, 557–563.
Kogan, F., Gitelson, A., Zakarin, E., et al. (2003). AVHRR-based spectral vegetation index for
quantitative assessment of vegetation state and productivity. Photogrammetric Engineering &
Remote Sensing, 69, 899–906.
Labus, M. P., Nielsen, G. A., Lawrence, R. L., et al. (2002). Wheat yield estimates using multitemporal NDVI satellite imagery. International Journal of Remote Sensing, 23, 4169–4180.
https://doi.org/10.1080/01431160110107653.
Lensky, I. M., & Rosenfeld, D. (1997). Estimation of precipitation area and rain intensity based on
the microphysical properties Retrieved from NOAA AVHRR data. Journal of Applied Meteorology, 36, 234–242. https://doi.org/10.1175/1520-0450(1997)036<0234:EOPAAR>2.0.CO;2.
Lin, L., Di, L., & Yu, E. G. et al. (2016). A review of remote sensing in flood assessment. Tianjing,
China.
Macintosh, H., & Profeti, G. (1995). The use of ERS SAR data to manage flood emergencies at the
smaller scale. In 2nd ERS applications workshop (pp. 243–246). London: European Space
Agency.
Matgen, P., Hostache, R., Schumann, G., et al. (2011). Towards an automated SAR-based flood
monitoring system: Lessons learned from two case studies. Physics and Chemistry of the Earth,
Parts A/B/C, 36, 241–252.
16 Flood Monitoring and Crop Damage Assessment
347