Definitions
Remote sensing can be defined as the study of make observations, take measurements, and produce images of phenomena that are beyond the limits of our own senses and capabilities without making actual contact with the object of study. It can also be defined as: Any of the technical disciplines for observing and measuring the Earth from a distance, “The acquisition and measurement of data/information on some property(ies) of a phenomenon, object, or material by a recording device including satellite imaging, Global Positioning Systems, Radar, Sonar and aerial photography which is not in physical or close contact with the feature(s) under surveillance” and generate digital or hard copy image data (Jensen, 2007, 2008; http://en.wikipedia.org/wiki/Remote_sensing).
Introduction
Remote sensing data are indispensable for measurement and evaluation of regional-to-global processes. Remote sensing is now widely used for collecting data, monitoring and studying the natural resources...
Bibliography
Aase, J. K., and Siddoway, F. H., 1981. Spring wheat yield estimates from spectral reflectance measurements. IEEE Transactions on Geoscience and Remote Sensing, GE-19, 78–84.
Baret, F., Guyot, G., and Major, D. J., 1989. TSAVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation. In Proceedings of the 12th Canadian Symposium on Remote Sensing and IGARSS’89, Vancouver, Vol. 3, pp. 1355–1358.
Barnes, E. M., Sudduth, K. A., Hummel, J. W., Lesch, S. M., Corwin, D. L., Yang, C. H., Daughtry, C. S. T., and Bausch, W. C., 2003. Remote and ground-based sensor techniques to map soil properties. Photogrammetric Engineering and Remote Sensing, 69(6), 619–630.
Baumgardner, M., Silva, L., Biehl, L., and Stoner, E., 1985. Reflectance properties of soil. Advances in Agronomy, 38, 1–44.
Ben-Dor, E., Irons, J. R., and Epema, G., 1999. Soil reflectance. In Rencz, A. N. (ed.), Remote Sensing for the Earth Sciences. New York: Wiley, pp. 111–188.
Broge, N. H., and Leblanc, E., 2000. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment, 76, 156–172.
Clevers, J. G. P. W., 1994. Imaging spectrometry in agriculture – plant vitality and yield indicators. In Hill, J., and Mégier, J. (eds.), Imaging Spectrometry – A Tool for Environmental Observations. Dordrecht: Kluwer Academic, pp. 193–219.
Cohen, W. B., 1991. Temporal versus spatial variation in leaf reflectance under changing water stress conditions. International Journal of Remote Sensing, 12(9), 1865–1876.
Collins, W., 1978. Remote sensing of crop type and maturity. Photogrammetric Engineering and Remote Sensing, 44, 43–55.
Dutkiewicz, A., Lewis, M., and Ostendorf, B., 2009. Evaluation and comparison of hyperspectral imagery for mapping surface symptoms of dryland salinity. International Journal of Remote Sensing, 30, 693–719.
Dwivedi, R. S., 1992. Monitoring and the study of the effects of image scale on delineation of salt-affected soils in the Indo-Gangetic alluvial plains. International Journal of Remote Sensing, 13, 1527–1536.
Dwivedi, R. S., and Rao, B. R. M., 1992. The selection of the best possible Landsat-TM band combinations for delineating salt-affected soils. International Journal of Remote Sensing, 13, 2051–2058.
Eldaw Elwadie, M., Pierce, F. J., and Qi, J., 2005. Remote sensing of canopy dynamics and biophysical variables estimation of corn in Michigan. Agronomy Journal, 97, 99–105.
Everitt, J. H., Anderson, G. L., Escobar, D. E., Davis, M. R., Spencer, N. R., and Andrascik, R. J., 1995. Use of remote sensing for detecting and mapping leafy spurge (Euphorbia esula). Weed Technology, 9, 599–609.
Fourty, T., Baret, F., Jacquemond, S., Schmuck, G., and Verdebout, J., 1996. Leaf optical properties with explicit description of its biochemical composition: direct and inverse problems. Remote Sensing of Environment, 56, 104–117.
Gao, B. C., 1996. NDWI – A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.
Gitelson, A., Kaufman, Y., and Merzlyak, M., 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 58, 289–298.
Gitelson, A., Kaufman, Y. J., Stark, R., and Rundquist, T. D., 2002. Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment, 80, 76–87.
Golubiewski, N. (Lead Author); Hussein, G. H. G. (Topic Editor). 2007. Remote sensing’s functional role in studies of land-use/land-cover change. In Cleveland, C. J. Encyclopedia of Earth. Washington, DC: Environmental Information Coalition, National Council for Science and the Environment. (Published in the Encyclopedia of Earth March 15, 2007; Retrieved September 20, 2009). http://www.eoearth.org/article/Remote_sensing’s_functional_role_in_studies_of_land-use/land-cover_change
Hatfield, J. L., 1983. Remote sensing estimators of potential and actual crop yield. Remote Sensing of Environment, 13, 301–311.
Hoffer, R. M., 1978. Biological and physical considerations in application computer aided analysis techniques to remote sensing. In Swain, P. H., and Davis, S. M. (eds.), Remote Sensing: Quantitative Approach. New York: McGraw-Hill, pp. 237–286.
Huete, A. R., 1988. A soil vegetation adjusted index (SAVI). Remote Sensing of Environment, 25, 295–309.
Huete, A. R., and Liu, H. Q., 1994. An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS. IEEE Transactions on Geoscience and Remote Sensing, 32(4), 897–905.
Huete, A., Justice, C., and Liu, H., 1994. Development of vegetation and soil indices for MODIS-EOS. Remote Sensing of Environment, 49(3), 224–234.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L. G., 2002. Overview of the radiometric aiophysic performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195–213.
Hunt, G. R., 1980. Electromagnetic radiation: the communication link in remote sensing. In Siegal, B. S., and Gillesppie, A. R. (eds.), Remote Sensing in Geology. New York: Wiley, pp. 5–46.
Idso, S. B., Jackson, R. D., Reginato, R. J., Kimball, B. A., and Nakayama, F. S., 1975. The dependence of bare soil albedo on soil water content. Journal of Applied Meteorology, 14, 109–113.
Idso, S. B., Hatfield, J. L., Reginato, R. J., and Jackson, R. D., 1978. Wheat yield estimation by albedo measurement. Remote Sensing of Environment, 7, 273–276.
Idso, S. B., Pinter, P. J., Jr., Jackson, R. D., and Reginato, R. J., 1980. Estimation of grain yields by remote-sensing of crop senescence rates. Remote Sensing of Environment, 9, 87–91.
Irons, J. R., Weismiller, R. A., and Petersen, G. W., 1989. Soil reflectance. In Asrar, G. (ed.), Theory and Application of Optical Remote Sensing. New York: Wiley, pp. 66–106.
Jensen, J. R., 2007. Remote sensing of vegetation. In Remote Sensing of the Environment, An Earth Resource Perspective, 2nd edn. Chapter 11. Prentice-Hall. Upper Saddle River.
Jensen, J. R., 2008. Remote sensing for vegetation. Power Point Presentation http://www.cas.sc.edu/geog/rslab/551/
Karnieli, A., Kaufman, Y. J., Remer, L., and Wald, A., 2001. Remote Sensing of Environment, 77(1), 10–21.
Latz, K., Weismiller, R. A., Van Scoyoc, G. E., and Baumgardner, M. F., 1984. Characteristic variations in spectral reflectance of eroded Alfisols. Soil Science Society of American Journal, 48, 1130–1134.
Lenney, M. P., Woodcock, C. E., Collins, J. B., and Hamdi, H., 1996. The status of agricultural lands in Egypt: the use of multitemporal NDVI features derived from landsat TM. Remote Sensing of Environment, 56, 8–20.
Moran, M. S., Clarke, T. R., Inoue, Y., and Vidal, A., 1994. Estimating crop water deficits using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment, 46, 246–263.
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.
Moran, M. S., Peters-Lidard, C. D., Watts, J. M., and McElroy, S., 2004. Estimating soil moisture at the watershed scale with satellite-based radar and land surface models. Journal of Remote Sensing, 30(5), 805–826.
Mulders, M. A., 1987. Remote Sensing in Soil Science. Amsterdam: Elsevier, p. 379.
Pinter, P. J., Jr., Jackson, R. D., Idso, S. B., and Reginato, R. J., 1981. Multidate spectral reflectance as predictors of yield in water-stressed wheat and barley. International Journal of Remote Sensing, 2, 43–48.
Ramsey, R. D., Falconer, A., and Jensen, J. R., 1995. The relationship between NOAA_AVHRR NDVI and Ecoregions in UTAH. Remote Sensing of Environment, 53(3), 188–198.
Ray, T., 1994. A FAQ on Vegetation in Remote Sensing. http://www.yale.edu/ceo/Documentation/rsvegfaq.html
Reginato, R. J., Vedder, J. F., Idso, S. B., Jackson, R. D., Blanchard, M. B., and Goettelman, R., 1977. An evaluation of total solar reflectance and spectral band ratioing techniques for estimating soil water content. Journal of Geophysical Research, 82, 2101–2104.
Rondeaux, G., Steven, M., and Baret, F., 1996. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55, 95–107.
Running, S. W., Loveland, T. R., and Pierce, L. L., 1994. A vegetation classification logic based on remote sensing for use in global biogeochemical models. Ambio, 23, 77–81.
Salama, R. B., Hatton, T. J., Elder, G. M., Ye, L., and Dowling, T. 1997. Hydrogeological characterisation of catchments using Hydrogeomorphic Analysis of Regional Spatial Data (HARSD): characterisation of Axe Creek Catchment. In: Taniguchi, M. (ed.), Subsurface Hydrological Responses to Land Cover and Land Use Change. Kluwer Academic, Victoria, Australia, pp. 153–166.
Scull, P., Franklin, J., Chadwick, O. A., and McArthur, D., 2003. Predictive soil mapping: a review. Progress in Physical Geography, 27(2), 171–197.
Selige, T., and Schmidhalter, U., 2006. Remote sensing of soil properties to support site specific farming. Developments in Plant and Soil Sciences, 92
Shanahan, J. F., Schepers, J. S., Francis, D. D., Varvel, G. E., Wilhelm, W. W., Tringe, J. M., Schlemmer, M. R., and Major, D. J., 2001. Use of remote-sensing imagery to estimate corn grain yield. Agronomy Journal, 93, 583–589.
Szilágyi, A., and Baumgardner, M. F. 1991. Salinity and spectral reflectance of soils, In: Proceedings American Society of Photogrammetry Remote Sensing Symposium, March 25–29, 1991, Baltimore, MD, pp. 430–437.
Tucker, C. J., 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127–150.
Tucker, C. J., Holben, B. N., Elgin, J. H. Jr., and McMurtrey, J. E., III, 1980. Relationship of spectral data to grain yield variations. Photogrammetric Engineering and Remote Sensing, 46, 657–666.
Wessman, C. A., 2003. The use of remote sensing in following soil process, Remote sensing of soil processes. Agriculture, Ecosystems and Environment. In: Proceedings of the International Workshop on Modern Techniques in Soil Ecology Relevant to Organic Matter Breakdown, Nutrient Cycling and Soil Biological Processes, Volume 34, Issues 1–4, 15 February 1991, pp. 479–493.
Zarco-Tejada, P. J., Rueda, C., and Ustin, S., 2003. Water content estimation in vegetation with MODIS reflectance data and model inversion methods. Remote Sensing of Environment, 85, 109–124.
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Salama, R.B. (2011). Remote Sensing of Soils and Plants Imagery. In: Gliński, J., Horabik, J., Lipiec, J. (eds) Encyclopedia of Agrophysics. Encyclopedia of Earth Sciences Series. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3585-1_132
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