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:: Relationship between soil and leaf metal content and Landsat MSS and TM acquired canopy reflectance data. C. Banninger

Document type:: Multivolume work

Structure type:: Chapter

197 TABLE 2 ¡asa istics n and plant n to ec- ensity. bsorp- 550 nm centra- mini- he tanges ab- .nds ated P. excelsa) ig at the :, mature lunts of fir, such as present as it understory :s , and small •ess are ¡tand. idsat TM :a used in :om mid-Sep- 1 scenes are , All scenes lave been ising the )d of Crane ; form the 2 study. A 2 and station jround con- sles were lorizon and 2 lower ree sampling sisted of ap- 2dles and six year old Correlation Between Spruce Needle Metal Soil Metal (M ) and (M N ) Content S Correlation Coefficients (r-values) Pb s Zn s Cu s Pb N Zn N CU N Pb s 1 .00 0.91 0.79 0.15 0.74 0.34 Zn s - 1 .00 0.82 0.11 0.73 0.28 Cu s - - 1 .00 0.26 0.50 0.16 Pb N - - - 1 .00 0.21 0.05 Zn N - - - - 1 .00 0.25 CU N - - - - - 1 .00 Level of significance: r>0.49, p>0.99 0.30<r< 0.49, 0.95 < p< 0.99 r < 0.30, p < 0.90 A total of 44 soil and 44 tree samples collected from the 10.75 ha test site were analysed for total copper, lead, and zinc content using the atomic-absorption spectro photometry method. Soil lead values range from 10-10,000+ ppm, soil zinc values from 60-6300 ppm, and soil copper values from 20-940 ppm, whereas spruce needle lead values vary from 1-10 ppm, needle zinc values from 30-340 ppm, and needle copper values from 2-5 ppm. 8. ANALYSIS OF GEOCHEMICAL AND LANDSAT DATA The approach followed in establishing the relationship between the soil, needle, and spectral data involved first merging the different data sets with one another and then applying a linear regression analysis to the various combined sets. Because of the common reference system employed in the collection of the soil and spruce needle samples, the spatial correspondence between these two data sets was already established. For the merging of the Landsat spectral data with the ground-collected data, the geographical correspondence between the Landsat MSS and TM pixel arrays of the four Landsat scenes had to be first determined and then the aver age soil and needle lead, zinc, and copper values calculated for each "pure" pixel re presenting 95 per cent or more forest cover. Soil and needle metal isopleth maps of each of the three metals provided the means of merging the ground information with the Landsat spectral reflectance information of the test site, using 100-point and 36-point dot grids scaled in accordance to the 76 by 76 metre and 30 by 30 metre ground-projected instantaneous field of views of the Landsat MSS and TM sensor systems. The number of "pure" test site forest pixels contained in the September 1976 and 1981 MSS scenes is 11 and 12, respectively, and in the June and July TM scenes 76. 9. STATISTICAL ANALYSIS OF DATA Linear regression analysis and an ana lysis of variance formed the basis for establishing relationships between the soil, needle, and Landsat data sets. TABLE 2 lists the correlation coefficients (r-values) ob tained for the various pairwise combinations of the soil and needle metal data sets. The relationships between soil copper, lead, and zinc are very good to excellent, but are de cidedly poor between needle copper, lead, and zinc. The results of the regression of needle lead and copper content against their corres ponding soil lead and copper values are poor, but good with respect to needle zinc regres sed against soil zinc. TABLES 3 and 4 list the Landsat MSS and TM spectral bands and transformations regres sed against soil and needle copper, lead, and zinc pixel metal values. The results of the statistical analysis employing soil metal values have been published in previous papers (Banninger, 1985a, 1985b, 1985c, and 1986), and only the more significant findings from these studies will be presented here. For the MSS bands and transformations, the first principal component (PC1) and the Kauth-Thomas green vegetative (GVI) and soil brightness (SBI) indices show overall the highest correlations with soil metal content (r=-0.74 to r=-0.89), followed closely by Landsat bands 6 and 7, band differences BD6 and BD7, and the perpendicular vegetation indices PVI6 and PVI7 (r-values ranging from -0.65 to -0.85). These values are significant at greater than the 98 per cent probability level. For the TM bands and transformations, the normalised differences ND1 and ND3, the band difference BD1, and the simple ratio R41 exhibit the highest correlation values with respect to soil metal content (r=-0.68 to t--0.11), followed by the greenness index TMG, band difference BD3, and the first prin cipal component(PC1) (r-values from -0.6 3 to -0.70). These values are significant at greater than the 99 per cent probability level. The regression of the Landsat MSS and TM spectral bands and transformations against the spruce needle metal values produced for all Landsat scene dates (except the Septem ber 1976 MSS scene) at best only weak to fair correlations (r-values between -0.40 and -0.65, with the level of significance of the higher values only between 90 and 95 per cent). Relationships are, for the most part,

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