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

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CC BY: Attribution 4.0 International. You can find more information here.

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:
Theoretic reflection modelling of soil surface properties. B. P. J. van den Bergh & B. A. M. Bouman
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

s of absorption 
icients of 
volume of each 
minerais, the 
d to be : 
eq. 4 
on of the mi- 
on of minerai i 
minerai i 
he results of 
amples of pure 
.h the aid of 
.ion of three 
ive been calcu- 
icident radia- 
a function 
quartz, gypsum 
don ( - 1 p 2 ) 
licite 
. . 188 
. .062 
). 969 
) . 905 
) .855 
). 8 2 1 
). 793 
). 77 1 
). 7 4 1 
3.724 
3.688 
erals in a 
reflectance 
aid of equa- 
the minera- 
icle size of 
urfaces (van 
ve been air- 
alcite and 
n small cups 
>s and mean 
) i1 s ample s. 
¡ample B 
'O 
!5 
). 2 
.25-250 
ilculated and 
>fotometer; 
and 2b. 
L, 
100 _ 
"-'80 .. 
o 
<1> 
£40 ‘ 
0) 
u 
20 ■■ 
# ! measured 
X * : calculated 
_i i i 1 . i . i . i i L u i 1 I 
' 1.0 1.4 1.8 2.2 
wavelength 
tyumf 
Figure 2a. Calculated and measured reflectance 
of sample A. 
1.0 1.4 1.8 2.2 
wavelength (um) 
Figure 2b. Calculated and measured reflectance 
of sample B. 
In general, the same trend is observed for 
the measured reflectance and the calculated 
reflectance. The presence of gypsum in sample 
B is clearly recognised in the characteristic 
dips around 1.4 and 1.9 um in the measured 
reflectance curve. These dips, although less 
pronounced, are also observed in the calcula 
ted reflectance curve. Differences in reflec 
tance value are due to differences in cali 
bration of the two spectrometers; to differen 
ces in sample preparation (the depth of the 
Hunt and Salisbury samples was only 3.5 mm); 
and to differences in shape and surface 
structure between the minerals used by Hunt 
and Salisbury and those in the Tunesian soil 
samples. 
The influence of soil water 
The influence of soil water on reflection 
from soil surfaces is complex and involves 
many variables. Adding water to a sample of 
dry soil introduces an extra component of ab 
sorption which optical characteristics depend 
on its solute content and on the tension at 
which it is bound to the soil mass (pF). An 
attempt has been made here to include soil 
water as a single parameter in modelling at 
the intrinsic soil surface level. Again, re 
ference is made to Bowers and Hanks (B&H, 
1965): "The effect of moisture content on re 
flection from a Newtonian Silt Loam". Plots 
of Ln(r) versus moisture content at different 
wavelengths showed a linear relation between 
Ln(r) and moisture content. It is assumed 
that the influence of soil water on mean pe 
netrated layer thickness can be neglected 
when compared to its effect on the coeffi 
cient of absorption. On this assumption, the 
following formula for the coefficient of ab 
sorption of the total soil mass is proposed : 
2 
k = k + 9 k (m ) eq.5 
s w w 
in which : k = coefficient of absorption of 
the total soil mass 
k = coefficient of absorption of 
the dry soil mass 
k = coefficient of absorption of 
the soil water 
9 = moisture content in percentage 
of volume 
Applying this equation to the measurements 
of Bowers and Hanks raised the problem of 
finding some input for the mean penetrated 
layer thickness d. Since no specifications 
concerning aggregate size of the Newtonian 
Silt Loam could be found, arbritary values 
for the mean aggregate diameter 0 have been 
chosen. In figure 3,calculated values for 
k , using equation 5 and 3 with 0 = 100, 500 
and 1000 |im,are plotted against wavelength 
of incident radiation. 
Figure 3. Calculated values of k 
tion of wavelength, and k derived 
et al. , 1965 . W 
as a fune- 
from Allen 
The shape of these curves compares well with 
that of the water absorption curve of Allen 
et al. , 196-5. Considering the method used for 
obtaining some value for mean penetrated la 
yer thickness, no comparison between absolute 
values for k can be made. Also, the influen- 
■i w 
ce of soil water composition and soil water 
tension on k has not been taken into ac 
count. 
CONCLUDING REMARKS 
The combination of equation 3, equation 4 
and equation5 leads to the following formu 
la, describing reflectance from a moist mix 
ture of mineral matter in a specific parti 
cle size class : 
r = exp ( - ( Y*c . k . + 9 k ) (vf^Ln ( 0/X) ) ) eq.6 
11 w w 
Modelling of intrinsic soil surface reflec 
tion has to include more variables such as 
shape and surface structure of the particles 
and aggregates, nature and content of organic
	        

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