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:: LANDSAT temporal-spectral profiles of crops on the South African Highveld. B. Turner

Document type:: Multivolume work

Structure type:: Chapter

arly indepen- thonormal set calculated by Jering, 1963) 's representa- egetation and s from satel- ' standardized extracted for îlues together re stored for the present 3 MSS data. 3 data ne test sites site temporal rghum and sun planting date ariability in ected by local ces. of MSS data compensate for tal count and difference ed from EROS nship: (1) i be converted (2) 2 Sr. are given trome et al., 1 values of min-^'min) max-R'min) MAIZE 315 0 50 100 150 200 250 300 350 I960 1981 JULIAN OATE SORGHUM Compensation for station-to-station differences was carried out by means of a linear transformation of the MSS data using the calculated values of A and B. 4.2.1.2 Compensation for satellite-to-satellite differences The method and values prepared by Parris and Rice referred to above were used (Rice et al., 1983). 4.2.2 The Tasseled cap Transformation for the study area. JULIAN OATE The application of the Gram-Schmidt process to the data corrected as described in 4.2.1.1 and 3.3.2 above produces the required set of orthogonal unit vectors. The matrix of the Tasseled cap transformation for the Grootvlei test site was found to be SUNFLOWER 315 0 50 100 150 200 250 300 350 1980 1981 JULIAN OATE 0.30 -0.36 -0.26 (Turner, 1986) and in 3.3.3. 0.38 0.34 -0.80 0.37 -0.77 0.58 SBI, GVI and YVI 0.69 0.30 0.05 were defined as 4.3 Vegetation indices Figure 5. Temporal Plots of Growth Stages of Field Samples within WRS 182-79. Table 4. Range of Absolute Radiances (Anon, 1976 and Strome, 1975) EROS CCRS R max R min R' max R' min LANDSAT 1 MSS 4 2.48 0 3.00 0.0 MSS 5 2.00 0 2.00 0.0 MSS 6 1.76 0 1.75 0.0 MSS 7 not calibrated not calibrated LANDSAT 2 MSS 4 2.63 0.08 3.00 0.0 MSS 5 1.76 0.06 2.00 0.0 MSS 6 1.52 0.06 1.75 0.0 MSS 7 3.91 0.11 4.00 0.0 LANDSAT 3 MSS 4 2.50 0.04 2.50 0.0 MSS 5 2.00 0.03 2.00 0.0 MSS 6 1.65 0.03 1.75 0.0 MSS 7 4.50 0.03 4.00 0.0 The calculated values of A and B are given in Table 5. Table 5. Coefficients of Linear Transformation for SRSC 8-bit data to EROS 7/6 bit data A B LANDSAT 1 MSS 4 0.61 0.00 MSS 5 0.50 0.00 MSS 6 0.25 0.00 MSS 7 not calibrated LANDSAT 2 MSS 4 0.59 -4.02 MSS 5 0.57 -4.36 MSS 6 0.60 -5.26 MSS 7 0.26 -1.85 LANDSAT 3 MSS 4 0.51 -2.06 MSS 5 0.51 -2.06 MSS 6 0.51 -2.06 MSS 7 0.51 -2.06 Sample wheat test sites were formed by concatenation of known samples from wheat fields representative of WRS 182-79 (Malan and Turner, 1984). A temporal plot of the VI and NVI is given in Fig. 6. 5. DISCUSSION OF THE RESULTS The coefficients of the matrix of the Tasseled cap transformation obtained in the present work were found to differ significantly from those obtained by Kauth and Thomas for MSS data representative of the US Corn Belt. Although the Tasseled cap transforma tion does indeed exploit the structure of the MSS data to produce independent indices SBI and GVI, the orientations of the distribution of the bispectral plots appear to be dependent on geographic location. This study has therefore illustrated that even when the MSS data is reduced to the same standard condi tions applied by Kauth and Thomas for the US Corn Belt, the coefficients of the Tasseled cap transfor mation are different for US and South African condi tions. However, the concepts evolved by Kauth and Thomas would still appear to be directly applicable to agricultural MSS data collected for the South African Highveld. The vegetation indices, as shown in Fig. 6, form two distinct sets representing the wheat and non wheat cover types. Seasonal variations seem to be significant and may be correlated with the quantity and timing of rain and the growth stage of the wheat. The single observation for the 1982 season seems anomalous in two respects: The maximum index is greater than for the other two seasons and the division between wheat and non-wheat is less pro nounced. These significant variations may be due to higher rainfall during October 1982 (1627 mm) than in 1981 (316 mm) and 1983 (1266 mm). 5.1 Future developments The generation of the temporal profiles of the spec tral and ground reference data sets for each field and an analysis of these data in terms of the spec tral separability of the crops, the influence of the planting date, row direction, etc. on the vegetation indices, the spatial variability of vegetation in dices for similar crops within a LANDSAT scene, and

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