Geography Reference
In-Depth Information
Kumar, L., Schmidt, K., Dury, S., & Skidmore, A. (2001). Imaging spectrometry and vegetation
science. In F. D. Van der Meer & S. M. De Jong (Eds.), Imaging spectrometry (pp. 111-155).
Dordrecht: Kluwer Academic Publishers.
Kwarteng, A. Y., & Chavez, P. S, Jr. (1998). Change detection study of Kuwait city and environs
using
multitemporal
Landsat
Thematic
Mapper
data.
International
Journal
of
Remote
Sensing, 19(9), 1651-1661.
Lam, N. S.-N. (2008). Methodologies for mapping land cover/land use and its change. In S. Liang
(Ed.), Advances in land remote sensing (pp. 341-367). New York: Springer.
Lambin, E. F., Geist, H. J., & Lepers, E. (2003). Dynamics of land-use and land-cover change in
tropical regions. Annual Review of Environment Resources, 28, 205-241.
Lambin, E. F., & Linderman, M. (2006). Time series of remote sensing data for land change
science. IEEE Transactions on Geoscience and Remote Sensing, 44(7), 1926-1928.
Liu, W., & Wu, E. Y. (2005). Comparison of non-linear mixture models: Subpixel classification.
Remote Sensing of Environment, 94(2), 145-154.
Lillesand, M. T., Kiefer, R. W.,
& Chipman,
J. W. (2008). Remote sensing and image
interpretation (6th ed.). Hoboken, NJ: Wiley.
Liu, J. G., & Mason, P. J. (2009). Essential image processing and GIS for remote sensing.
London, UK: Wiley.
Lord, D., Desjardins, R. L., Dube, P. A., & Brach, E. J. (1985). Variations of crop canopy spectral
reflectance measurements under changing sky conditions. Photogrammetric Engineering and
Remote Sensing, 51(6), 689-695.
Loveland, T. R., Zhu, Z., Ohlen, D. O., Brown, J. F., Reed, B. C., & Yang, L. (1999). An analysis
of the IGBP global land-cover characterization process. Photogrammetric Engineering and
Remote Sensing, 65(9), 1021-1032.
Lu,
D.,
Mausel,
P.,
Brondizio,
E.,
&
Moran,
E.
(2003a).
Change
detection
techniques.
International Journal of Remote Sensing, 25(12), 2365-2407.
Lu, D., & Weng, Q. (2007). A survey of image classification methods and techniques for
improving
classification
performance.
International
Journal
of
Remote
Sensing,
28(5),
823-870.
Lyon, J. G., Yuan, D., Lunetta, R. S., & Elvidge, C. D. (1998). A change detection experiment
using vegetation indices. Photogrammetric Engineering and Remote Sensing, 64(2), 143-150.
Mahmood, T., & Easson, G. (2006). Comparing aster and Landsat-7 ETM+ for change detection.
In Proceedings of ASPRS Annual Conference, May 1-5, 2006, Reno, Nevada.
Marcal, A. R. S., Borges, J. S., Gomes, J. A., & Da Costa, J. F. P. (2005). Land cover update by
supervised classification of segmented ASTER images. International Journal of Remote
Sensing, 26(7), 1347-1362.
Martinez-Beltran, C., & Calera-Belmonte, A. (2001). Irrigated crop estimation using Landsat TM
imagery in La Mancha, Spain. Photogrammetric Engineering & Remote Sensing, 67(10),
1177-1184.
Maselli, F., Conese, C., Petkov, L., & Gilabert, M. A. (1993). Environmental monitoring and crop
forecasting in the Sahel through the use of NOAA NDVI data. A case study: Niger 1986-89.
International Journal of Remote Sensing, 14(18), 3471-3487.
Mather, P. M. (2004). Computer processing of remotely-sensed images: An introduction (3rd ed.).
Chichester: Wiley.
McCoy, R. M. (2005). Field methods in remote sensing. New York, NY: Guilford Press.
McIver, D. K., & Friedl, M. A. (2002). Using prior probabilities in decision-tree classification of
remotely sensed data. Remote Sensing of Environment, 81(2-3), 253-261.
McVicar, T. R., & Jupp, D. L. B. (1998). The current and potential operational uses of remote
sensing to aid decisions on drought exceptional circumstances in Australia: A review.
Agricultural Systems, 57(3), 399-468.
Meadows, M. E., & Hoffman, M. T. (2002). The nature, extent and causes of land degradation in
South Africa: Legacy of the past, lessons for the future? Area, 34(4), 428-437.
Search WWH ::




Custom Search