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:: Multitemporal analysis of LANDSAT Multispectral Scanner (MSS) and Thematic Mapper (TM) data to map crops in the Po valley (Italy) and in Mendoza (Argentina). M. Menenti & S. Azzali, D. A. Collado & S. Leguizamon

Document type:: Multivolume work

Structure type:: Chapter

298 Table 7. Significance of differences in TVI-values, as obtained with LANDSAT-MSS 7, MSS 5 measurements; Mendoza, Argentina; N = vineyard, W = olive trees, W+N = olive trees plus vineyard, N+P = vineyard plus vegetable crops; ns = not significant, s = significant at P = 0.05, hs = highly significant at P = 0.01 Crop 28-8-1984 27-2-1985 15-3-1985 N W W+N N+P N W W+N N+P N W W+N N+P N -■ s ns hs - hs hs hs hs ns hs W ns hs ns ns hs ns W+N - - - s - ns N+P - - as t* for (Nj-1) respectively (N2-1) degrees of free dom. The different number of degrees of freedom is the main difference between the test of hypothesis a] = 02 respectively op 4 02 • The procedures just described have been applied to a number of image samples. An approximate indication of the normality of an observed distribution is ob tained by considering the criterions skewness and kurtosis. Large values of both criterions suggest non-normality. A x^-test has been applied to a se lection of 'worst cases'. In Table 4, as well as in the next few ones, codes have been assigned to ground control plots according to the format: CROP IRRIGATION DISTRICT PLOT NUMBER and irrigation districts being: A = East Sesia B = Grande Bonifica Ferra- rese On the basis of the results in Table 4 we can con clude that even large values of kurtosis, e.g. for samples ВАЗ, CA4 and IA2 do not imply that the x^~ test will indicate significant deviations from nor mality. As for example plots CA2 and 0B2 show, one should apply a x^-test when considering samples with many elements, 50 or more say. Notwithstanding the important theoretical differ ences between procedure 1 and II, the outcome of a t- test can be essentially the same, as shown by the results in Table 5. The plots have been chosen by taking the largest observed phenological difference for each crop. As expected because of the fewer degrees of freedom applying to procedure II,differ ences assessed as not-significant according to pro cedure i, are significant according to procedure II, The capability of measuring by LANDSAT significant differences in TVI is confirmed by Table 6. Discrim ination of phenological differences, such as con sidered in Table 6 is of obvious relevance to crop monitoring. It is, however, clear that this capability makes crop discrimination more difficult. This is one additional reason to translate phenological vari ability within an area into quantitative terms, e.g. as done in Section 2 by means of the function A(t). The need for discrimination of different intercrop ping schemes has been explained in Section 2. The re sults in Table 7 demonstrate that the differences noted between the graphs in Figure 2 are actually significant on at least one overpass date. Discrimina tion of these intercropping patterns is, therefore, feasible. The Thematic Mapper under any count is a big im provement on the Multi Spectral Scanner from an in strumental point of view. A more difficult question is whether the TM improves our capability to dis criminate crops. Namely the much improved radiometric sensitivity and spatial resolution do allow for ob with crop codes being: Code Crop B rice C pasture I corn 0 soybeans Table 8. Significance of differences in TVI-values; East Sesia, Po valley, Italy; for explanation of plot coding see text; ns = not significant, s = signifi cant, hs = highly significant A: LANDSAT MSS 7 and MSS 5 measurements; samples include between 3 and 10 pixels B: LANDSAT TM 4 and TM 3 measurements; samples in clude between 4 and 10 pixels C: LANDSAT TM 4 and TM 3 measurements; samples in clude between 15 and 43 pixels Plots САЗ СА4 ВАЗ BA4 IA3 IA4 A CA3 - ns hs hs hs hs CA4 - hs hs hs hs ВАЗ - ns hs hs BA4 - s hs IA3 - ns IA4 - В САЗ - ns hs hs hs hs CA4 - hs hs hs hs ВАЗ - ns hs hs ВА4 - ns ns IA3 - ns IA4 - С САЗ - ns hs hs hs hs СА4 - hs hs hs hs ВАЗ - ns hs hs ВА4 - hs hs IA3 - ns IA4 - servation of within-field variability. From our point of view, therefore, the most sensible way of comparing the TM with the MSS sensor is to assess which one gives the higher significance of differences in TVI values. If we compare Table 8-A with Table 8-B we see that at equal number of elements per field plot, the MSS fares marginally better than the TM. The difference between BA4 and IA3 is significant with MSS measure ments and not significant with TM ones. It is only the larger number of TM elements for a given field plot (Table 8-C) which gives a slightly better sig nificance: the difference BA4 versus IA3 is 'highly significant' according to Table 8-C. These results can be looked at from different points of view. From one side we have found that the per formance of MSS, from our particular point of view, is at least comparable with TM. It is, however, true that by working with five TM pixels only, one can discriminate plots of 4500 m^ versus the 23,305 m^ of 5 MSS pixels. Moreover the TM 5, TM 6 and TM 7 measurements allow for detection of crop-specific effects, after crop mapping is accomplished. 5 RADIOMETRIC ACCURACY VERSUS SIZE OF SIGNIFICANT DIFFERENCES To draw a conclusion on the size of significant dif ferences in TVI-values we have calculated the means of (xi - X2)/[(x^ + X2)/2] for each one of a large number of significance tests, as done with the MSS and TM images considered in this paper. The result reads: not significant = 4%, significant = 10% and highly significant = 10%. These percentages give beforehand an indication of how large relative differences in TVI-values should be, for these differ ences to result as either not significant or signifi - cant aft Let us tion of assessed lish whe The nomi is 0.5% nominal of the f results We can ciple me with sat Actual quite di take the flectanc ity grea fore be It mus analysis digital values ( Furtherrr have to least nc the imag 6 CONCLU We conci patterns can be о 0.5 ha a and MSS that a ir scheme c agricult satellit feasible as prese REFERENC Andersor earth Azzali, proacf An app East S 1611 . sear cl Azzali, app lie rarese Manage Azzali, data t for Le geninp Crist, I mental opment 3-13. Hinzman, Growtl wheat Jackson, crimii varioe atmosp 208. Kenney, statif pp. Kuipers in th< LAND Si

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