Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

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Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856343064

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: XV, 547 Seiten

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856343064

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Damen, M. C. J.

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: Relation between spectral reflectance and vegetation index. S. M. Singh

Document type:: Multivolume work

Structure type:: Chapter

Lngh et al. ;s from the 3d which is . An average iza, 1975) luation (7). manner would adiance, ) and (7) of L S (A) is ulting the actual is value of the above parallel to tivity would be cedure is reached, flectivities found to be value. The ) with radi al number. using ten ee or four 'nly one case iquired for cally (9) were perfect Lon index (VI) retaining the a of ar residual aate igle, varying ts. 1 data are k of Duggin 1985, 1986) factors which w angle the larger e the larger natural sur ly sensed tian surfaces e as seen by t necessarily cast by made). An me which has applied to a (1985, 1986) view angle d by (a) above possible to ises (b) and which have ition were )84 at the ring station, a from about i part lose pixels 3 were positive. 3, and to some extent identifies cloudy pixels over the land. Since the data acquisition time was local afternoon and since there were clouds on the western side of the selected scene, there might have been some pixels which were contaminated by cloud shadows and identi fication of such pixels is not yet possible. 4 RESULTS AND DISCUSSION Raw NDVI were calculated using equation (1). The atmospheric correction procedure was implemented and spectral reflectances p(A^)and p(^2) were calculated. Equation (9) then yields atmospherically corrected NDVI values. A relation of the form of equation (10) was sought between raw and atmospherically corrected NDVI values. Y = mX + c (10) where Y is atmospherically corrected NDVI and X stands for raw NDVI. Line by line regression analysis was performed on a 512 x 512 scene but because of cloud cover and surrounding waters only about 80 to 200 pixels per scanline corresponded to cloud-free land area. For each scanline raw NDVIs were highly correlated to atmospherically corrected NDVI values. In fact the squared correlation coefficient ranged from 85% to 98%. The parameter c in equation (10) varied from about -0.1 to about -0.03 whereas the slope (or enhancement or magni fication) m ranged from about 2.2 to 3.5. These results indicate that the relation (10) is not a unique one. Had it been a unique relation then it would have been of great value. Therefore, it suggests that one has to apply atmospheric correction to each scene of interest. It is also clear from the values of m found above that the atmospherically corrected NDVI imagery should have high contrast compared to the contrast present in raw NDVI maps. Next a relation similar to equation (10) was sought between p (Aq) and atmospherically corrected NDVI. There was a large variability in the value of m (2 to 30) but an important outcome was that the squared correlation coefficient ranged from about 30% to about 90%. This shows that p(Aq) carries some extra information to which NDVI is not sensitive. A similar analysis between p(A2) and atmospherically corrected NDVI showed a poor correlation between these two parameters. Therefore, p(Aq), p(A2) and atmospherically corrected NDVI values may be useful in improving surface cover type classification and further investigations are underway. 5 CONCLUSIONS The primary motivation was to search for more than one parameter for land-cover classification. Application of atmospheric correction results in an increased contrast between too dissimilar surfaces. It is shown that the atmospherically corrected NDVIs are partially correlated to either channel reflect ivity. This means that these three parameters may prove to be of importance in improving land cover classification. Although atmospherically corrected NDVIs and raw NDVIs are highly correlated to each other, these preliminary results indicate that there is no unique relation between these two quantities. Thus, one has to apply atmospheric correction to each scene of interest. ACKNOWLEDGEMENT This work was carried out under the NERC contract No. F60/G6/12. REFERENCES Duggin, M.J., Piwinski, D., Whitehead, V. and Ryland, G., 1982, The scan angle dependence of radiance recorded by the N0AA-AVHRR. Proceedings of the AIAA/SPIE technical meeting, San Diego, California, 23-27 Aug., SPIE Vol. 363, p.98. Gordon, H.R., 1978, Removal of atmospheric effects from satellite imagery of the oceans, Appl. Opt., Vol. 13, p.1361. Hayes, L., 1985, The current use of Tiros-N series of meteorological satellites for land-cover studies, Int. J. Rem. Sens., Vol. 6, p.35. Hayes, L. and Cracknell, A.P., 1984, A comparison of Tiros-N series satellite data and Landsat data over Scotland. Proc. of Integrated Approaches in Remote Sensing, ESA SP-214, p.63. Holben, B.N. and Justice, C.O., 1981, An examination of spectral band ratioing to reduce the topo graphic effect on remotely sensed data, Int. J. Rem. Sens., Vol. 2, p.115. Hughes, N.A. and Henderson-Sellers, A., 1982, System albedo as sensed by satellites: its definition on variability. Int. J. Rem. Sens., Vol. 3, p.l. Janza, F.J. (editor), 1975, Manual of Remote Sensing, Vol. I, American society of photogrammetry, Falls Church, Virginia. Justice, C.O., Townshend, J.R.G., Holben, B.N. and Tucker, C.J., 1985, Analysis of the phenology of global vegetation using meteorological satellite data, Int. J. Rem. Sens., Vol 6, P.1271. Lauritson, L., Nelson, G.J. and Porto, F.W., 1979, Data extraction and calibration of Tiros-N/NOAA radiometers. N0AA technical memorandum NESS-107, N0AA/NESS, Washington D.C. Manual of Remote Sensing, 1983, (editor in chief), Data interpretation and applications. American society of photogrammetry, Falls Church, Va. Otterman, J., 1983, Absorption of insolation by land surface with sparse vertical protrusions, Tellus, Vol. 35B, p.309. Singh, S.M., 1986, Vegetation index and possibility of complementary parameters from AVHRR/2. Int. J. Rem. Sens., Vol. 7, p.295. Singh, S.M. and Cracknell, A.P., 1985, Effect of shadows cast by vertical protrusions on AVHRR data. Int. J. Rem. Sens., Vol. 6, p.1767. Singh, S.M. and Cracknell, A.P., 1986, The estimation of atmospheric effects for SPOT using AVHRR channel-1 data. Int. J. Rem. Sens., Vol. 7, P- Singh, S.M., Cracknell, A.P. and Spitzer, D., 1985, Evaluation of sensitivity decay of Coastal Zone Scanner (CZCS) detectors by comparison with in- situ near surface radiance measurements. Int. J. Rem. Sens., Vol. 6, p.749. Thekaekara, M.P., Kruger, R. and Duncan, C.H., 1969, Solar irradiance measurements from research air craft, Appl. Opt., Vol. 8, p.1713. Toll, D.L., 1985, Landsat-4 Thematic Mapper scene characteristics of a suburban and rural area, Photogram. Eng. and Rem. Sens., Vol. LI, p.1471. Townshend, J.R.G. and Tucker, C.J., 1985, Continental land cover classification using satellite data. Proc. of the 36th Congress of the International Astronomical Federation, Stockholm, Sweden. Oct. 1985, Peaceful Space and Global Problems of Mankind, Pergamon Press: Oxford, New York, Toronto, Sydney, Frankfurt. Tucker, C.J., Gatlin, A. and Schneider, S.R., 1984, Monitoring vegetation in the Nile Delta with N0AA-6 and N0AA-7 AVHRR. Photogramm. Eng. and Remote Sensing, Vol. 50, p.53. Tucker, C.J., Holben, B.N. and Goff, T.E., 1984, Intensive forest clearing in Rondonia, Brazil as detected by satellite remote sensing. Remote Sensing Environ., Vol. 15, p.255.

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