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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:
Multitemporal analysis of Thematic Mapper data for soil survey in Southern Tunisia. G. F. Epema
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

valid for reflectance values of A above 0 %. The 
first example is not valid if A is not equal to 0 
%. In that case the reflectance of A in that band 
has to be subtracted from all other points before a 
constant ratio will give an equal decrease. 
Table 2. Examples to show difference between ratio 
and difference image. 
before change 
after 
change 
sur 
face 
nr. 
cover 
refi. 
(%) 
cover 
refi 
(%) 
. ratio abs. 
decrease 
1 
100%A 
0 
100%A 
0 
X 
X 
2 
100%B 
20 
50%A,50%B 
10 
.5 
10 
3 
100%C 
40 
50%A,50%C 
20 
.5 
20 
1 
100% A 
0 
100% A 
0 
X 
X 
2 
50%A,50%C 
20 
100%A 
0 
0 
20 
3 
100%C 
40 
50%A,50%C 
20 
.5 
20 
Field measurements of reflectance have been 
performed in the month before the acquisition of 
the May image. The values found with the 
reflectometer cannot be compared directly with the 
TM data due to the type of apparatus (Epema in 
prep.), and the fact that there is a difference 
between reflectance at the top of the atmosphere 
and at the surface. In table 3 normal reflectance 
values are given for a range of surfaces. 
Table 3. Representative normal reflectance values 
of May 1985 with solar zenith angle of 20 degrees. 
green 
red 
nir 
Playa and playa border 
sealed surface 
22.2 
22.6 
23.5 
thin salt layer 
25.2 
28.0 
29.4 
extremely dry 
30.4 
34.7 
39.1 
extremely wet 
14.9 
17.1 
17.2 
extr dry near oasis 
33.2 
38.2 
43.7 
Footslope 
sealed surface 
39.4 
41.5 
48.7 
gypsiferous sand 
47.6 
51.1 
57.9 
lygeum spartum 
14.4 
14.5 
19.0 
Interpretations based on the 
above 
described 
images are complementary to each 
other. 
In order 
to 
observe variations within the 
playa 
difference 
images will be most 
useful. 
The influence 
of 
vegetation or shadow can be found at their best on 
ratio images. In principle for vegetation from all 
values first the reflectance of vegetation has to 
be subtracted before the ratio is calculated. The 
same will hold for the shadow influence at short 
wavelength. 
A generalized map of part of the area, subtracted 
from different images and multitemporal plots of 
bands and band ratios, is given in fig. 2. 
In general one may observe an absolute increase 
in reflectance for most of the playa and playa 
border zone. This will be due to the presence of 
salt at the surface. The increase in salt cover 
will remain important for a long period after rain 
storms, while the effect of increasing moisture 
content will last only for a short time. 
The decrease in reflectance for a part of the 
playa border zone north of the oasis is due to the 
effect that the surface is after the rainstorm 
comparable with the rest of the playa border zone. 
Probably in January surfaces as described in table 
4 dominated. Only a small part of the playa remains 
without changes. 
bands 
code 
1 
4 
7 
1 
0 
0 
0 
0 = 
Oasis 
2 
0 
+2 
0 
Pl= 
Playa and 
playa border 
3 
0 
0 
-1 
Fs= 
Footslope 
4 
+2 
+2 
+1 
5 
+2 
+1 
0 
0 = 
no or very 
weak change 
6 
mix 
3/5 
1 = 
weak change 
7 
-3 
-3 
-1 
2 = 
moderate 
change 
3 = 
strong change 
+ = 
refl. May > 
January 
refl. May < 
January 
Fig. 
2. Most important 
changes in 
reflectance for 
part 
of the 
study 
area. 
In 
the 
footslope 
area for 
most 
surfaces 
reflectance 
remains about the same. For 
several 
units 
with 
still a high 
reflectance 
in band 7 (low 
cover 
of 
gypsum crust 
or gypsum 
sand) 
a small 
absolute decrease in reflectance occurs in May. The 
same may be true for other parts of the footslopes, 
but in this area the variance within the units is 
higher than the possible change. The change may be 
due to the effect of exposure differences and 
related amount of shadow. Also for some other parts 
with a certain slope the effect is present. However 
no direct model can be developed, as in the 
correction procedure reference objects are used in 
stead of an atmospheric model. Another phenomenon 
which can be observed is the effect of increase in 
vegetation for a part of the footslope. This 
relative increase in band 4 for May in comparison 
with January will be caused by vegetation which is 
present all over the year. If this vegetation is 
healthy, the reflectance increases in band 4 and 
remains about the same in other bands. In other 
parts of the footslope area permanent vegetation 
made up only a small part of the surface. It has 
been observed that annuals between this permanent 
hummocks make no more than about 2 % of the 
surface. The effect of this vegetation is a 
decrease in reflectance in all bands (hardly less 
for band 4). The cause that this cannot be read 
from the data is the small influence on reflectance 
in comparison with the reflectance as a whole. 
Since one of the completely bare units in the playa 
reacts in all bands, within the limits of 
significancy, the same as the selected reference 
object, it can be concluded that the influence of 
vegetation is small for the selected reference 
object. 
The most important changes in reflectance are due 
to salt efflorescence, vegetation development and 
exposition. However also other differences between 
the images exist or may exist. Over a very small 
part of the study area wet surfaces are present in 
May. The change in reflectance in the eastern part
	        

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