164
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
Moron, M. S., Clarke, T. R., and Inoue, Y. (1994). Estimating crop water defi cit using the rela(1994). Estimating crop water defi cit using the relaEstimating crop water deficit using the relation between surface air temperature and spectral vegetation index. Remote Sensing of
Environment, 49, 246–263.
Nicholson, S. E., Davenport, M. L., and Malo, A. D. (1990). A comparison of the vegetation
response to rainfall in the Sahel and East Africa, using NDVI from NOAA AVHRR.
Climate Change, 17, 209–214.
Palmer, W. C. (1965). Meteorological drought. Research paper, vol. 45. U.S. Department of
Commerce Weather Bureau, Washington, DC.
Palmer, W. C. (1968). Keeping track of crop moisture conditions, nationwide: The crop moisture index. Weatherwise, 21(4), 156–161.
Pinty, B. and Verstraete, M. M. (1992). GEMI: A non-linear index to monitor global vegetation
from satellites. Plant Ecology, 101(1), 15–20.
Price, J. C. (1977). Thermal inertia mapping: A new view of the earth. Journal of Geophysical
Research, 82, 2582–2590.
Price, J. C. (1985). On the analysis of thermal infrared imagery: The limited utility of apparent
thermal inertia. Remote Sensing of Environment, 18, 59–93.
Price, J. C. (1990). Using spatial context in satellite data to infer regional scale evapotranspira(1990). Using spatial context in satellite data to infer regional scale evapotranspiraUsing spatial context in satellite data to infer regional scale evapotranspiration. IEEE Transactions on Geoscience and Remote Sensing, 28, 940–948.
Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H., and Sorooshian, S. (1994). A modified soil
adjusted vegetation index. Remote Sensing of Environment, 48, 119–126.
Qin, Z., Karnieli, A., and Berliner, P. (2001). A monowindow algorithm for retrieving land
surface temperature from Landsat TM data and its application to the Israel–Egypt border
region. International Journal of Remote Sensing, 22(18), 3719–3746.
Ridd, M. K. (1995). Exploring a V-I-S (vegetation-impervious surface-soil) model for
urban ecosystem analysis through remote sensing: Comparative anatomy for cities.
International Journal of Remote Sensing, 16, 2165–2185.
Rouse, J. W., Haas, R. H., Schell, J. A., and Deering, D. W. (1974). Monitoring vegetation
systems in the Great Plains with ERTS, Third ERTS Symposium, NASA Washington,
DC, SP-351 I, pp. 309–317.
Sandholt, I., Rasmussen, K., and Andersen, J. (2002). A simple interpretation of the surface
temperature/vegetation index space for assessment of surface moisture status. Remote
Sensing of Environment, 79, 213–224.
Tadesse, T., Brown, J. F., and Hayes, M. J. (2005). A new approach for predicting droughtrelated vegetation stress: Integrating satellite, climate, and biophysical data over the
U.S. central plains. Journal of Photogrammetry and Remote Sensing, 59(4), 244–253.
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring veg(1979). Red and photographic infrared linear combinations for monitoring vegRed and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127–150.
Tucker, C. J. and Miller, L. D. (1977). Soil spectra contributions to grass canopy spectral
reflectance. Photogrammetric Engineering and Remote Sensing, 43(6), 721–726.
USGS-ARS. (2006). How Images Are Categorized. Aerial Photographs and Satellite Images.
Online edition, U.S. Department of Interior—U.S. Geological Survey, Reston, VA,
USA. http://erg.usgs.gov/isb/pubs/booklets/aerial/aerial.html. Retrieved in July 2006.
van Rooy, M. P. (1965). A rainfall anomaly index independent of time and space. Notos, 14,
43–48.
Venturini, V., Bisht, G., and Islam, S. (2004). Comparison of evaporative fractions estimated
from AVHRR and MODIS sensors over South Florida. Remote Sensing of Environment,
93(1–2), 77–86.
Wang, Q., Ren, Z., and Sun, G. (2002). Research on seawater intrusion disaster in south–east
coastwise area of Laizhou Bay. Marine Environmental Science, 21, 10–13.
Wang, C., Qi, J., and Moran, S. (2004). Soil moisture estimation in a semiarid rangeland using
ERS-2 and TM imagery. Remote Sensing of Environment, 90, 178–189.
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
Moron, M. S., Clarke, T. R., and Inoue, Y. (1994). Estimating crop water defi cit using the rela(1994). Estimating crop water defi cit using the relaEstimating crop water deficit using the relation between surface air temperature and spectral vegetation index. Remote Sensing of
Environment, 49, 246–263.
Nicholson, S. E., Davenport, M. L., and Malo, A. D. (1990). A comparison of the vegetation
response to rainfall in the Sahel and East Africa, using NDVI from NOAA AVHRR.
Climate Change, 17, 209–214.
Palmer, W. C. (1965). Meteorological drought. Research paper, vol. 45. U.S. Department of
Commerce Weather Bureau, Washington, DC.
Palmer, W. C. (1968). Keeping track of crop moisture conditions, nationwide: The crop moisture index. Weatherwise, 21(4), 156–161.
Pinty, B. and Verstraete, M. M. (1992). GEMI: A non-linear index to monitor global vegetation
from satellites. Plant Ecology, 101(1), 15–20.
Price, J. C. (1977). Thermal inertia mapping: A new view of the earth. Journal of Geophysical
Research, 82, 2582–2590.
Price, J. C. (1985). On the analysis of thermal infrared imagery: The limited utility of apparent
thermal inertia. Remote Sensing of Environment, 18, 59–93.
Price, J. C. (1990). Using spatial context in satellite data to infer regional scale evapotranspira(1990). Using spatial context in satellite data to infer regional scale evapotranspiraUsing spatial context in satellite data to infer regional scale evapotranspiration. IEEE Transactions on Geoscience and Remote Sensing, 28, 940–948.
Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H., and Sorooshian, S. (1994). A modified soil
adjusted vegetation index. Remote Sensing of Environment, 48, 119–126.
Qin, Z., Karnieli, A., and Berliner, P. (2001). A monowindow algorithm for retrieving land
surface temperature from Landsat TM data and its application to the Israel–Egypt border
region. International Journal of Remote Sensing, 22(18), 3719–3746.
Ridd, M. K. (1995). Exploring a V-I-S (vegetation-impervious surface-soil) model for
urban ecosystem analysis through remote sensing: Comparative anatomy for cities.
International Journal of Remote Sensing, 16, 2165–2185.
Rouse, J. W., Haas, R. H., Schell, J. A., and Deering, D. W. (1974). Monitoring vegetation
systems in the Great Plains with ERTS, Third ERTS Symposium, NASA Washington,
DC, SP-351 I, pp. 309–317.
Sandholt, I., Rasmussen, K., and Andersen, J. (2002). A simple interpretation of the surface
temperature/vegetation index space for assessment of surface moisture status. Remote
Sensing of Environment, 79, 213–224.
Tadesse, T., Brown, J. F., and Hayes, M. J. (2005). A new approach for predicting droughtrelated vegetation stress: Integrating satellite, climate, and biophysical data over the
U.S. central plains. Journal of Photogrammetry and Remote Sensing, 59(4), 244–253.
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring veg(1979). Red and photographic infrared linear combinations for monitoring vegRed and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127–150.
Tucker, C. J. and Miller, L. D. (1977). Soil spectra contributions to grass canopy spectral
reflectance. Photogrammetric Engineering and Remote Sensing, 43(6), 721–726.
USGS-ARS. (2006). How Images Are Categorized. Aerial Photographs and Satellite Images.
Online edition, U.S. Department of Interior—U.S. Geological Survey, Reston, VA,
USA. http://erg.usgs.gov/isb/pubs/booklets/aerial/aerial.html. Retrieved in July 2006.
van Rooy, M. P. (1965). A rainfall anomaly index independent of time and space. Notos, 14,
43–48.
Venturini, V., Bisht, G., and Islam, S. (2004). Comparison of evaporative fractions estimated
from AVHRR and MODIS sensors over South Florida. Remote Sensing of Environment,
93(1–2), 77–86.
Wang, Q., Ren, Z., and Sun, G. (2002). Research on seawater intrusion disaster in south–east
coastwise area of Laizhou Bay. Marine Environmental Science, 21, 10–13.
Wang, C., Qi, J., and Moran, S. (2004). Soil moisture estimation in a semiarid rangeland using
ERS-2 and TM imagery. Remote Sensing of Environment, 90, 178–189.