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:: 4 Renewable resources in rural areas: Vegetation, forestry, agriculture, soil survey, land and water use. Chairman: J. Besenicar, Liaisons: M. Molenaar, Th. A. de Boer

Document type:: Multivolume work

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Chapter

Title:: Comparison of SPOT-simulated and Landsat 5 TM imagery in vegetation mapping. H. Tommervik

Document type:: Multivolume work

Structure type:: Chapter

forest cover types that were in a optimal phenological stage (summer) got such a good classification accuracy. Lannelongue & Saint (1981) investigated simulated SPOT-data, and stated that "the geometry is not repre sentative of the SPOT-system". I do hope that the real SPOT-data will give us a possibility of improved detec tion and mapping of forest cover types, but I don't expect the optimal use of the SPOT-satellite system for vegetation mapping purposes before the HRV-sensor get an additional channel in the MIR-area of 1.5 - 1.7 um. This is also the area where the vegetation cover types with lichen cover is best detectable and mapped. 3.5 Visual interpretation and classification Visual classification and interpretation was done on the imageries. Ratio methods were elaborated using channel-ratios of 5:3, 4:3, 5:4:3:2 and 4:3:2:1. In addition to this, several channel-combinations were interpretated in order to detect very hardly detectab le vegetation cover types by digital classification. The most successfully results were obtained by using the ratios and channel-combinations in the following subheadings: 3.5.1 Ratio Landsat 5 TM 1984-06-03 Ratio 5:3 gave a good delineation of mixed spruce seedling stands (01) from the surroundingdeciduous forests (figure 3). In addition this ratio gave a good delineation between lowland vegetation and alpine vege tation (T0mmervik 1985b). This was also the result by using the ratio of 5:4:3:2. Ratio 4:3 gave a good delineation of pine forests (A4a) from other forests. SPOT-simulation 1982-06-30 Ratio 3:2 (NIR-quotient) gave a good delineation of clearcuts, roads, in addition of detection of the var iation in the farmland. Spruce seedling stands (homo geneous) were good delineated from the surrounding forests. 3.5.2 Channel combinations Landsat 5 TM 1984-06-03 The channel combinations of CH 456, CH 532 and CH 754 gave a good delineation of the mixed spruce seed ling stands from the surrounding deciduous forests, but not so good as the ratio 5:3. This combination gave a good delineation of G7 Birch forests of meadow type and E5a/E5c Grey alder forests (rich type) from poorer forest cover types. Pine forests were also well detec ted. Landsat 5 TM 1984-10-02 The channel combinations of CH 432, CH456 and CH 543 gave a good result in detection and delineation of C5 Swamp forests at the river banks and E5a/E5c Grey alder forests at the hillsides,due to the litter. The chann el combination of CH 432 was a good basis for inter pretation of H/ Rich shrub and snowbeds (K2, K6 and K6'). The channel combination of CH 456 gave a good délinéation of pine forests (A4a), Spruce seedling stands (01), Snowbeds (K2 and K6) and Farmland (AA1/ AA2) . SPOT-simulation 1982-06-30 Channelcombination of CH 321 gave almost same result of interpretation and detection of vegetation cover types as Landsat 5 TM, but as a result of the improved spatial resolution, texture and variation within the vegetation cover types can be seen. Channel combinat ion of CH 432 gave a good ability to study texture and pattern within the vegetation cover types. This is due to the association between the panchromatic channel (4) and the multispectral channels 3 and 2. As a res- Figure 3. Ratio of channel 5 and 3 (5:3) shows a good delineation of mixed spruce seedling stands from the surrounding deciduous forests. The area is marked with an arrow. ult of improved spatial resolution (10 m), clearcuts with shrubs were detectable. 3.5.3 General discussion Hame (1984) has stated that the best results in deline ation of mixed spruce seedling stands and other very hardly detectable vegetation cover types, were obtained using parallelepiped classifications with the first two principal components calculated of Landsat MSS-imagery. Jaakkola (1985) has done a similar study on SPOT-sim ulated imagery and stated that the best results of the classifications of the imagery, were obtained by using multi-point (contextual) classification techniques. I have shown by simple ratio-methods and channel combin ations elaborated on TM-imagery, that we can delineate very heterogeneous forest cover- and vegetation cover types easily. 4. CONCLUSIONS Second generation satellites such as Landsat 5 TM and SPOT HRV, providing high spatial resolution between 10 m and 30 m and in the case of Landsat 5 TM, new spectral channels, will increase the level and accuracy of digital classification. This study has shown that it was possible to classify the vegetation cover types which were furthest phenological develloped, with an overall accuracy of 90 percent or more, in spite of the unfortunately fact that the scenes were taken too early in the springtime or taken to late in the autumn. In addtition to this the digital classification even went good in an area with a fairly wide variation in eco logical niches and a heterogeneous vegetation. Visual interpretation and classification based on ratio-techniques and channel combinations was a very good tool to improve the interpretation of imagery. The best results in this case were obtained by the TM-sen- sor of the Landsat 5 satellite. The middle infrared (MIR) channels of TM were useful for vegetation classification, especially for deline ation of heterogeneous forest cover types. Comparison between Landsat 5 TM-sensor and the simu lated SPOT HRV-sensor has shown that the two sensor- systems have almost the same ability to detect and map vegetation cover types within the area, due to the higher radiometric resolution for the TM-sensor compa red to the simulated HRV-sensor. Classification of the SPOT-simulated imagery showed that vegetation units

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