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Remote sensing for resources development and environmental management (Volume 1)

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Bibliographic data

fullscreen: Remote sensing for resources development and environmental management (Volume 1)

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:
Spectral and botanical classification of grasslands: Auxois example. C. M. Girard
Document type:
Multivolume work
Structure type:
Chapter

Contents

Table of contents

  • Remote sensing for resources development and environmental management
  • Remote sensing for resources development and environmental management (Volume 1)
  • Cover
  • Title page
  • Title page
  • Title page
  • Preface
  • Organization of the Symposium
  • Working Groups
  • Table of contents
  • 1 Visible and infrared data. Chairman: F. Quiel, Liaison: N J. Mulder
  • 2 Microwave data. Chairman: N. Lannelongue, Liaison: L. Krul
  • 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik
  • Relationship between soil and leaf metal content and Landsat MSS and TM acquired canopy reflectance data. C. Banninger
  • The conception of a project investigating the spectral reflectivity of plant targets using high spectral resolution and manifold repetitions. F. Boochs
  • CAESAR: CCD Airborne Experimental Scanner for Applications in Remote Sensing. N. J. J. Bunnik & H. Pouwels, C. Smorenburg & A. L. G. van Valkenburg
  • LANDSAT TM band combinations for crop discrimination. Sherry Chou Chen, Getulio Teixeira Batista & Antonio Tebaldi Tardin
  • The derivation of a simplified reflectance model for the estimation of LAI. J. G. P. W. Clevers
  • The application of a vegetation index in correcting the infrared reflectance for soil background. J. G. P. W. Clevers
  • The use of multispectral photography in agricultural research. J. G. P. W. Clevers
  • TURTLE and HARE, two detailed crop reflection models. J. A. den Dulk
  • Sugar beet biomass estimation using spectral data derived from colour infrared slides. Robert R. De Wulf & Roland E. Goossens
  • Multitemporal analysis of Thematic Mapper data for soil survey in Southern Tunisia. G. F. Epema
  • Insertion of hydrological decorralated data from photographic sensors of the Shuttle in a digital cartography of geophysical explorations (Spacelab 1-Metric Camera and Large Format Camera). G. Galibert
  • Spectral signature of rice fields using Landsat-5 TM in the Mediterranean coast of Spain. S. Gandia, V. Caselles, A. Gilabert & J. Meliá
  • The canopy hot-spot as crop identifier. S. A. W. Gerstl, C. Simmer & B. J. Powers
  • An evaluation of different green vegetation indices for wheat yield forecasting. A. Giovacchini
  • Spectral and botanical classification of grasslands: Auxois example. C. M. Girard
  • The use of Thematic Mapper imagery for geomorphological mapping in arid and semi-arid environments. A. R. Jones
  • Determination of spectral signatures of different forest damages from varying altitudes of multispectral scanner data. A. Kadro
  • A preliminary assessment of an airborne thermal video frame scanning system for environmental engineering surveys. T. J. M. Kennie & C. D. Dale, G. C. Stove
  • Study on the spectral radiometric characteristics and the spectrum yield model of spring wheat in the field of BeiAn city, HeilonJiang province, China (primary report). Ma-Yanyou, You-Bochung, Guo-Ruikuan, Lin-Weigang & Mo-Hong
  • 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
  • Selection of bands for a newly developed Multispectral Airborne Reference-aided Calibrated Scanner (MARCS). M. A. Mulders, A. N. de Jong, K. Schurer, D. de Hoop
  • Mapping of available solar radiation at ground. Ehrhard Raschke & Martin Rieland
  • Spectral signatures of soils and terrain conditions using lasers and spectrometers. H. Schreier
  • Relation between spectral reflectance and vegetation index. S. M. Singh
  • On the estimation of the condition of agricultural objects from spectral signatures in the VIS, NIR, MIR and TIR wavebands. R. Söllner, K.-H. Marek & H. Weichelt, H. Barsch
  • LANDSAT temporal-spectral profiles of crops on the South African Highveld. B. Turner
  • Theoretic reflection modelling of soil surface properties. B. P. J. van den Bergh & B. A. M. Bouman
  • Monitoring of renewable resources in equatorial countries. R. van Konijnenburg, Mahsum Irsyam
  • Assessment of soil properties from spectral data. G. Venkatachalam & V. K. R. Jeyasingh
  • Spectral components analysis: Rationale and results. C. L. Wiegand & A. J. Richardson
  • 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
  • Cover

Full text

4,8 and 2 using the seasonal botanical variations 
or the seasonal spectral variations. 
4 DISCUSSION AND CONCLUSION 
The classification of grasslands using seasonal bota 
nical and spectral data must be developped according 
to the following organigram given in Figiire 4. 
Phytosociological releves 
PltLftoAoCsLoloqZcaZ tizlzvzA 
anatyAiA modoJL 
Agro-ecoloqical units 
definition 
Spectral behaviour in 
red and near infra-red. 
SzaAonaZ Apzztn.aZ bzka- 
vZqua modzZ. 
I 
Spectral and botanical classification 
of grasslands. 
Figure 4 .Orqanigram of botanical and spectral 
classification of grasslands. 
It is necessary to describe phytosociological rele 
vés and classify them according to sigmatist method. 
Once this step acheived, the more abundant species 
are selected. They enable to define and describe 
the agro-ecological units. 
Phytosociological units my be converted in agro- 
ecological units, but reverse is impossible as there 
has been a loss of informtion meanwhile. 
The agro-ecologiacl units are characterized by spec 
tral behaviour, particularly in red and near infra 
red wavelengths. Once their spectral behaviour deter 
mined, it is possible to cluster any new relevé or 
spectral set of data to one or another agro-ecologi 
cal unit. 
On the contrary it is not possible to define first 
a spectral behaviour and then try to create agro 
nomical units as the worse agronomical value.units, 
on very dry or on muddy soils show spectral beha 
viour similarity and are difficult to separate. 
It is the first time that a combined botanical and 
spectral classification is tempted. It has been ela 
borated in order to use reflectance values measured 
in the field for green biomss evaluation, and sate 
llite data for grassland classification and survey 
over large areas. 
REFERENCES 
Braun-Blanquet, J. & J. Pavillard 1925. Vocabulaire 
et sociologie végétale. Bull. Soc. Bot. Fr. 72: 
910-911. 
Brown. R.J. F.J. Ahern, 1983. Alberta rangeland as 
sessment using remotely sensed data. Centre Cana 
dien de Télédétection, Research report 83,1:128 p. 
Curran P.J 1983. Estimting green LAI from multispec- 
tral aerial photography. Photogramm. Eng. Remote 
Sensing. 49: 1709-1720. 
Everitt. J.H. 1985.Using aerial photography for de 
tecting blackbrush (Acacia rigidula) on South Texas 
rangelands. J. Range Management. 38 (3): 228-231. 
Gates D.M. H.J Keegan, J.C.Schleter,V.R. Weidnerl965. 
Spectral properties of plants. Applied Optics.4(1): 
11-20. 
Gates.D.M. 1970. Physical and physiological proper 
ties of plants.In Remote Sensing with a special 
reference to agriculture and forestry. National 
Academy of Sciences, Washington D.C:224-252. 
Grouzis.M. M. Méthy.1983. Détermination radiométrique 
de la phytomsse herbacée en milieu sahélien: per 
spectives et limites. Acta Oecologica. Oecologia 
plantarum.4(18),n°3:241-257. 
Guinochet.M. 1973. Phvtosociologie. Masson.227p. 
Knipling. E.B. 1970. Physical and phvsioloqical basis 
of the reflectance of visible aœd near infra-red 
radiation from vegetation. Remote Sensing of Environ. 
1 (3) : 155-159. 
Richardson. AJ. J.H. Everitt, H.W. Gausmn. 1983.Radio- 
metric estimation of biomss and nitrogen content 
of Alicia grass. Remote Sensing of Environ.13:179- 
184. 
Thalen. D.C.P. J.A.Leemburq,R.Beck. 1980. Estimting 
aerial biomss in semi-natural vegetation from 
spectral reflectance measurementsi)Preliminary 
experiences. Acta Bot. Neerl. 29(5/6) :565-578. 
Tucker.C. J, C. L. Van Prae t, A.Gas ton, E.Boerwinkel. 1983 
Détermination par télédétection de la oroduo tion 
primire herbacée aérienne au Sahel sénégalais. 
Proiet pilote d'inventaire et de surveillance des 
écosystèmes pastoraux sahéliens.FAO-UNEP. 
Van der MaarelE. 1979. Transform tion of cover-abun 
dance values in phvtosociologv and its effects on 
community similarity. Vegetatio.39(2):97-114. 
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