Application of remote sensing and GIS for sustainable development

Bibliographic data

Monograph

Persistent identifier:: 856472832

Title:: Application of remote sensing and GIS for sustainable development

Sub title:: [Workshop on "Environmental Modelling Using RS & GIS for Sustainable Development" ... on 11th March 1999]

Scope:: 82 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856472832

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

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:: Monograph

Collection:: Earth sciences

Chapter

Title:: ECOLOGICAL ANALYSIS AND MODELLING : ISSUES AND CHALLENGES. Harini Nagendra and Madhav Gadgil

Document type:: Monograph

Structure type:: Chapter

13 has ndia, is is i the lack ; and n of fined these land and Dland h as does rsity. d for have at ura I water better their nation ations •urces heme atural s and i at ion tional :a on e not , and forest one orests losecf ine is arests. aiding pecies : form ent of ansing ith the an this ;an be ;s for amesh of the distribution of endemic plants of the evergreen and semi-evergreen forests of the Western Ghats, using data from herbaria, literature and field sampling of the French Institute over fifteen years. Such data can be correlated with the presence of different vegetation cover types, and prove invaluable for formulating strategies for conservation of these species. FUTURE DIRECTIONS It is essential then, to organize a system by which data collected at all these different scales - land/water cover maps as well as data on distribution of various natural resources - can be collated and compared. To begin with, a look at various land/water cover maps used for monitoring various natural resources, will facilitate the design of a more universal mapping scheme which can be used for surveying several kinds of resources. Such a mapping system should ideally be organized at several hierarchical levels, like those used for land use mapping in several countries. The next step would be to identify the level in the hierarchy at which remote sensors are capable of accurate mapping, inter-observer variation in identification is minimal, and correspondence with distribution of the various natural resources being assessed is maximal. This level may possibly differ based on the nature of remotely sensed data available, the ease with which data collection is possible, and the type of resource being monitored. Finally, for specific natural resources such as water quality, soil type, fossil fuel level, biomass or species diversity, on which fairly large amounts of data are available in different formats, attempts should be made to relate this data to specific spatial locations, and hence to specific water/land cover types. This will then enable analysis of the nature and extent of correlation between cover types and levels of distribution of such resources. Based on such analysis, future data collection exercises can then be planned to fill in lacunae in the data, and also answer new scientific questions which will inevitably arise as a result of this data analysis. Of course, all this would involve coordination of efforts by various agencies involved in this effort all over India - a task which is by no means an easy one, but one that must be undertaken, considering the benefits. ACKNOWLEDGEMENTS The ideas expressed here have benefitted greatly from discussions with N.V. Joshi, C.B.S. Dutt, U. Ghate and P.G. Diwakar, whom we gratefully acknowledge. Our field studies were greatly assisted by M.B. Naik and S.G. Patgar. We thank the Ministry of Environment and the Department of Space, Government of India, for financial support. REFERENCES Atkinson P.M. (1991). Optimal ground based sampling for remote sensing investigations: estimating the regional mean. International Journal of Remote Sensing, 12(3): 559-567. Condit R. (1996). Defining and mapping vegetation types in mega-diverse tropical forests, Trends in Ecology and Evolution, 11(1 ):4-5. Dobbertin M. and Biging G.S. (1996). A simulation study of the effect of scene autocorrelation, training sample size and sampling method on classification accuracy, Canadian Journal of Remote Sensing, 22(4):360-367. Dutt C.B.S., Udayalakshmi V. and Sadhasivaiah A.S. (1994). Role of remote sensing in forest management, Proceedings of the 15th Asian Conference on Remote Sensing, 1(E):2.1 -2.7. Fisher P.F. (1994). Visualization of the reliability in classified remotely sensed images, Photogrammetric Engineering and Remote Sensing, 60(7):905-910. Forman R.T.T. and Godron M. (1987). Landscape Ecology, John Wiley and Sons, New York. Forman R.T.T. (1995). Land mosaics : The ecology of land scapes and regions, Cambridge University Press; Cambridge. England. Franklin S.E., Connery D.R. and Williams J.A. (1994). Classification of Alpine vegetation using Landsat Thematic Mapper, SPOT HRV and DEM data, Canadian Journal of Remote Sensing, 20( 1 ):49-56. Gaussen H., Legris P. and Viart M. (1961). Carte Internationale du Tapis Vegetal et des conditions ecologiques, a 1/1,000,000, Cape Comorin, French Institute, Pondicherry. Gaussen H., Legris P., Viart M., Meher-Homji V.M. and Labroue L. (1965). Carte Internationale du Tapis Vegetal et des conditions ecologicpies, a 1/100,000, Mysore, French Institute, Pondicherry. Hansen A.J. and di Castri F. eds. (1992). Landscape boundaries: consequences for biotic diversity and ecological flows, New York, Springer-Verlag. Janssen L.L.F. and van der Wei F..I.M. (1994). Accuracy assessment of satellite derived land-cover data: a review, Photogrammetric Engineering and Remote Sensing, 60(4):419-426.

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