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Forest Survey and Management Using Remote Sensing

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Forest Survey and Management Using Remote Sensing Proc. Indian Acad. Sci. (Engg. Sci.), Vol. 6, Pt. 3, September 1983, pp. 209-231. Printed in India. Forest survey and management using remote sensing N V MADHAVAN UNNI Forestry and Ecology Division, National Remote Sensing Agency, Balanagar, Hyderabad 500 037, India Abstract. Some of the important work done in India and other parts of the world in the application of remote sensing for forest survey and management has been reviewed in this paper. The account of work has been given under three main headings viz airborne remote sensing, satellite remote sensing and multistage approach. Keywords. Forest survey; forest management; airborne remote sensing; aerial photography; satellite remote sensing; multiband photography; multispectral scanning; thermal infrared. 1. Introduction The problems involved in maintaining a sustained supply of natural resources for the contemporary needs and futuristic projections of demands of mankind have made the land managers conscious of a compelling need for planned utilization of earth resources. Conservation and planned utilization of earth resources require a detailed understanding of the resources available with respect to their quality, quantity and distribution so as to strike a balance between the exploitation and regeneration processes and ensure the preservation of environmental quality. The conventional survey methods are not very efficient for this purpose. The advent of modern remote sensing techniques for collecting information about earth's surface features using photographic cameras and multispectral scanners from aerial and satellite platforms and man-machine interactive processing and analysis have ushered in an exciting and new era revolutionising the resource survey methods. Their capability to provide near real-time data with wide synoptic coverage and also for temporal verification are significant advantages with immense possibilities. 2. Application of remote sensing to forestry Aerial remote sensing to study forests is almost a century old although the term in the modern sense, starting with the use of infrared photography, is only half a century old. Satellite remote sensing is only of recent origin beginning with the use of photographs taken from Apollo-9 satellite in late sixties. 3. Airborne remote sensing Airborne remote sensing is of two types viz photographic or non-photographic. Use of photographs taken from an elevated platform is quite old. However, the non- photographic scanning methods have come into existence only during the sixties. 209 210 N V Madhavan Unni 3.1 Use of aerial photography Although there had been earlier experimentation of photography from raised platform like hot air balloon etc, for making forest maps, perhaps the first serious attempt of using photographs taken from aircraft to study forests was by Seeley (1929) who used oblique photographs to measure tree heights from shadows and related tree heights to timber volume. Aerial photographs are useful for classification of forest land and forest volume inventory. 3.1a Classification ofJorest lands Use of aerial photographs or other imageries is to complement and improve or reduce field work rather than absolutely replacing it. Therefore forest land is classified according to a scheme and using a combination of image interpretation techniques and field work. As different parts of the world have different types of forest cover, the classification schemes also vary from region to region. Therefore the interpretation keys also will be different. Identification of forest types and tree species will depend upon the scale, film used, the season and the image quality. Considerable research has gone into the selection of the best film/filter combination for the forest type identification. Panchromatic photography has been found to be superior in identifying tree species in western United States by Jensen & Colwell (1949). However, Spurr & Brown (1946) and Seeley (1949) found that in the eastern us seperation between hardwoods and conifers was better on infrared minus blue, although species identification was not very good. Chase & Korotov (1947) and Steigerwaldt (1948) found that infrared minus blue in Great Lakes States was better. Stone (1950) found that in Alaska panchromatic was successful while Hegg (1966) preferred infrared minus blue. In India black and white aerial photographs were used by Jones, a Canadian expert who collected data on the forest of Kulu and Seraj Valley. Versteegh (1968) prepared forest cover type map for Bastar (Madhya Pradesh) on 1:25,000 scale using aerial black and white photographs of 1:15,000 scale. Tomar & Maslekar (1974) suggested a classification scheme for forest survey and mapping of forests of India with reference to photo-interpretation (table 1). Tiwari (1978) made a comparative evaluation of accuracy, time and cost to prepare forest and land-use map using photointerpretation techniques and conventional ground survey, in Tehri-Gherwal area, and found that they gave more accurate information with respect to the boundaries of the types, and that they could be mapped in much less time and at lower cost. The Forest Survey of India prepared forest cover type and land-use maps (as reported by Shedha 1983) on 1:50,000 and 1:63,360 scale by interpreting medium to small scale panchromatic aerial photographs for about 4,20,000 km 2 in India, 36,600 km z in Nepal and 29,200 km z in Bhutan during the period 1965-1982. Figure 1 is a part of the forest cover type map prepared for a part of the Godavari basin area by visual stereoscopic interpretation of panchromatic aerial photographs at 1:25,000 scale (Madhavan Unni et al 1983). An integrated perspective of the forest cover types was attempted indicating average density and height and the type of terrain on which they stand. The topography is first defined into three categories viz (a) flat (slopes upto 10 ~) (b) undulating (slopes 10-30 ~o) and (c) hilly (slopes more than 30 ~o). The cover types were identified by giving the dominant tree species, for example teak Forest survey and management usin 9 remote sensin 9 211 0 0 ~ . ~ ~, "t~ 0 8 6 - ~ ~ - _ ~.~ ~ ~ E ~- ~ ~ ~ ~ ~ ~ ~ ~ |~ ~ ~ ~ ~ ~ ~ ~ ~ e. .-- 0 ~ ~.~ ~ ~ ~ .~ ~ ~.~ ~ ., ~, o ~ ~ ~ ~E ~ L 0 .= ~ '~ = ~ ~ :a ~'~ ~ = ,o 0 "a i- 0E z 212 N V Madhavan Unni I i i i I 0 2SO late. iKM, Forest survey and management usin 9 remote sensin9 213 Legend tree height density lOm<~>lOm Topography species 60~,/.I~" j teak~ ~ misc~a-~ 20-,0.,FZql neous , .... , 5.20ol~.jdzllD2l undulated misowit,h~ bamboo Fit;:~! d egra ded [---~ bomboo~ b ta nk[~"-~l T- teak B-bamboo pure mtxed h a r d w uc k i a L.n'2t:~-Ju.,.l~ sina ta I'r ~-'-'~i'd r'oaC[ m vittage Topographical. reference tank streams I Q 225 approx, hmght Figure l. Forestmap prepared by visual interpretation of aerial photographs for a part of Godavari basin (Madhavan Unni et a11983) forest means percentage of teak more than 30 ~o; mixed teak with 10-30 ~o by number of stems and when no species predominate the term miscellaneous was used. Five crop densities were identified such as 5-20 ~o, 20-40 ~o, 40-60~o, 60-80~o and 80 ~o and above. The average tree height also was estimated into two classes (i) less than 10 m and (ii) more than 10 m. Besides, plantations, degraded areas and forest blanks also were identified and delineated. This type of maps is useful to understand the forest type distribution and the timber stand volume available. It also helps in identifying areas suitable for raising plantations. Figure 2 is a land facet/land form map for a part of the Godavari basin prepared by Bedi (1982) by visual interpretation of aerial photographs on 1:25,000 scale. It delineates the different land forms in the area with constituent rocks and thickness of soil cover, erosion/accretion stages, existing vegetation cover and limitations/ capabilities. Whether or not a particular category is favourable for forest growth and in areas where there are forests what are the management practices like checking headwards extension of stream and erosion, land scaping, raising plantations and so on are to be taken to check the degradation process, were also recommended. Considerable studies on using aerial photographs of different film filter combi- nations for forest species identification and type mapping have been carried out in Europe (Belov & Berezin 1958; Pohorly 1958; Hildebrandt 1963; Lackner 1966; Nyyss6nen et al 1968; Rabinau 1969). Although there are differences of opinion, the general consensus is that the species identification improves as the photo scales become larger, colour and colour infrared are better than black and white for species identification when medium and large scale photographs are used and stand type identification is better on medium scale (1:151000) photographs than on both large and 214 N V Madhavan Unni VFF FTF FTF FTF FTF FTF FTF FTF ',,\ ~.,. mlsZSO 0 500 I K M I I , I ,I Forest survey and management usin9 remote sensin9 215 A- denudational features E- streams ~fragments of adissected flat top surface main stream/river round top ridge with variable slope tributary streams scarp / steep slope I rock wall terrace scarp residual hill F- forest / vegetation relation triangular facet densely forested flat top forested degraded slope B-depositionaL features sparsely forested valley fill ~fan densely forested valley fill Bazada forest pocket C-slopes. G-mlscelLeous features ~a slope direction cleared and cultivated area --t-- gentle wllage or settlement -~, medium to steep ----- converging f~ dam diverging 'as' obsequent D-erosion classes ~rr sheet erosion l} hill erosion lit deeply incised gully Figure 2. Landform/land facet map prepared by visual interpretation of aerial photo- graphs for a part of Godavari basin (Bedi 1983) small scale photographs although in regions where fewer species occur stand type could be identified on small scale (1:30,000) photographs. All of them agree that when photography is done in summer, black and white or colour infrared is preferred for stand type identification irrespective of the scale chosen.
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