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:: Explorations of the enhanced FCC 1:100.000 for development planning Land-use identification in the Nairobi area. F. Grootenhuis & H. Weeda, K. Kalambo

Document type:: Multivolume work

Structure type:: Chapter

452 7 (180/61 of January 24th, 1976) was specifi cally used to delineate water bodies, urban- rural settlement and infrastructure. Band 5 is used for the black and white reproduction in this paper, showing maximum detail. The land-cover map 1:1M based on visual interpre tation of LANDSAT imagery had been completed and was available for further exploration (Grootenhuis, Weeda and Kalambo 1986 a). Background material consulted were: Geological map, Degree sheet no: 51 NE Quarter, 1971, 1:125.000 Geological map, Degree sheet no: 52 NW Quarter, 1963, 1:125.000 Ministry of Natural Resources, Mines and Geology Department, Kenya Exploratory Soil map and Agroclimatic Zone map of Kenya, 1982, 1:1.000.000 Ministry of Agriculture, Kenya Route map of Kenya, 1976, 1:1.000.000 Survey of Kenya Nairobi and Environs, 1978, 1:100.000 Survey of Kenya Topographical 1 :50.000 map, Limuru, Sheet 148/1,1976 Topographical 1 :50.000 map, Kiambu, Sheet 148/2,1976 Topographical 1 :50.000 map, Ngong , Sheet 148/3,1976 Topographical 1:50.000 map, Nairobi, Sheet 148/4,1976 Survey of Kenya The optical pantograph and distortion free overhead projector enabled comparison of the LANDSAT images and background information at the same 1:100.000 scale. The multi spectral additive viewer was used to study various combinations of bands 4, 5, 6 and 7. A print taken from the view screen showing a balance between bands 5, 6 and 7 at scale 1:250.000 was used for crop distinction. The photo showed a discrimination between coffee, tea and pineapple plantation in different shades of orange and yellow. This appears to result from differences in band 5 and band 6 reflec tance of these crops. 2.2 Method A tranparency of the Nairobi and Environs map 1:100.00 was superimposed on the enlarged LANDSAT print. In consequence, the resulting geographical reference of the pixels simpli fied the visual interpretation of the images in relation to the ground truth. A land-cover map at 1:1M scale was already available as a result of previous work in the Nairobi area with LANDSAT images (Grootenhuis, Weeda and Kalambo 1986 a)„ This map was projected over the LANDSAT print, using the distortion free overhead projector, and the respective zones were transferred to the 1:100.000 scale map. By means of the geographical reference, the boundaries could be checked in the field sup ported by the topographical maps 1:50.000. The boundaries were redrawn where necessary. The identified zones showed homogeneous patterns, which enabled a representative choice of sampling points. About six field inspections were made per zone, depending on the size and complexity. In this way, sixty sampling points were located within the 60 km x 60 km study area. The field inspection points were located at random along accessible roads, using a specific land-use data sheet. The variables recorded, included details on altitude, landform, soil, drainage, vegetation land-use and visual characteristics. Cross- sections were sketched in the field to record the distribution of landscape elements. The land-cover/land-use classification system of the United States Geological Survey (Anderson 1976) was applied. Integration of the visual interpretation of the enlarged LANDSAT image with the fieldwork and the consulted back ground data led to the production of a land- use map at 1:100.000 scale showing land-use units (Figure 2). 3 RESULTS The land-cover map enlarged to scale 1:100.000 and superimposed on the photographic print of the image at the same scale, provided the delineation of the land-use zones. The boun daries were checked using the 1:50.000 topo graphical maps, and only little adjustment of their location was necessary. Sharp boundaries were found around large scale plantations due to property boundaries. A similar situation is found at the forest edge where the boundary is secured by the Forest Department. In cases of transition between two zones, determination of the boundary is related to specific physi-r cal factors (as geomorphology and soil). Differentiation in texture and tone within one broad phototonal zone suggested sub-divi sions were necessary. Gathering additional knowledge about these areas in the field made it possible to distinguish the land-use units within the land-use zone. During the examination of the photo-tones, it was found that the same colour can repre sent different land-uses. For example, the reflection of coffee, pineapple, foodcrops and river bottoms in the near infra-red (band 7) is the same and all appear red in the FCC. Within the land-use zones, different tones and textures were identified. The ground truth provided confirmation of the different land-use units. Sets of land-use units are responsible for the mottled patterns within each zone. The cross-sections and the block- diagrams of the land-use zones (Figure 3-6) illustrate the sub-division into character istic land-use units and their relative dis tribution in percentages. The land-use units depict clearly the inter action between man and his environment. Agricultural practices relating to altitude, climate, type of soil, slope and landownership can now be identified.(Table 3). Table 1. Key to the land-use zones. Mapping unit Land—use zone (M) Mountain M1.M2 (E) Escarpment E (S) Slopes si - S4 (P) Plains P1 - P4

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