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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:
Relationship between soil and leaf metal content and Landsat MSS and TM acquired canopy reflectance data. C. Banninger
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

TABLE 1 
Landsat MSS and TM Spectral Band Vegetation Response Characteristics 
MSS or TM 
Band 
Bandwidth 
Interval 
(nm) 
Plant-Energy Relationships 
Band 
4 
500-600 
Spectral region of moderate leaf pigment absorption and 
moderately low plant reflectance. 
Band 
5 
600-700 
Strong leaf chlorophyll absorption region and low plant 
reflectance. 
Band 
6 
700-800 
Crossover region from strong chlorophyll absorption to 
high leaf cell reflection. 
Band 
7 
800-1100 
Region of high leaf cell reflection and plant reflec 
tance, and shows a strong sensitivity to foliage density 
TM 1 
450-520 
Region of combined leaf chlorophyll and carotene absorp 
tion and low plant reflectance. 
TM 2 
520-600 
Spans the reflectance peak of green vegetation at 550 nm 
and shows a slight sensitivity to leaf pigment concentra 
tion . 
TM 3 
630-690 
Region of maximum leaf' chlorophyll absorption and mini 
mum leaf reflectance. 
TM 4 
760-900 
Covers the high vegetation reflectance region of the 
near-infrared and shows a strong correlation to changes 
in vegetation density and vigor. 
TM 5 
TM 7 
1550-1750 
2080-2350 
Contain the two reflectance peaks within the water ab 
sorption region of the shortwave infrared. Both bands 
are highly sensitive to leaf water content and related 
stresses. 
Many of the shortcomings of the MSS 
spectral bands are ameliorated in the selec 
tion of the TM bandwidths, which are narrower 
and more precisely delineate the characteris 
tic relationships between vegetation and so 
lar energy. The increase in spatial resolu 
tion from 76 m to 30 m and radiometric reso 
lution from 64 to 256 quantisation levels 
over the MSS sensor system further enhances 
the capacity of TM data to discriminate 
stress conditions in vegetation. 
TABLE 1 lists the important Landsat MSS 
and TM band responses as they pertain to ve 
getation . 
5. DESCRIPTION OF TEST SITE 
A Norway spruce stand growing in copper- 
lead-zinc enriched soils provided the ground 
data used for establishing the relationship 
between soil and needle metal content and 
Landsat MSS and TM acquired canopy reflec 
tance data. The spruce stand lies between 
500 and 600 metres within an upland region 
consisting of hills and low lying mountains 
rising to 1200 m in elevation. The prevail 
ing climatic conditions are those of the 
humid continental zone. 
Low-grade metamorphic rocks composed of 
greenstone, marble, black schist, and car 
bonate phyllite comprise the underlying bed 
rock of the test site. Mineralisation con 
sists of small but rich concentrations of 
massive galena, sphalerite, and chalcopyrite. 
The overlying soils are residual in origin 
and exhibit a well-developed profile. Soil 
depths range from 35 cm to over 100 cm. 
Norway spruce (Picea abies, P. excelsa) 
is the dominant tree type growing at the 
test site, and occurs as a dense, mature 
stand interspersed with small amounts of fir, 
pine, and larch. Deciduous trees, such as 
beech, ash, maple, and oak, are present as 
a minor stand constituent. Forest understory 
consists mainly of forbs, grasses, and small 
bushes. No manifestations of stress are 
readily apparent in the forest stand. 
6. LANDSAT MSS AND TM SCENE DATA 
Two Landsat MSS and two Landsat TM 
scenes comprise the spectral data used in 
the study. The MSS scenes are from mid-Sep 
tember 1976 and 1981, and the TM scenes are 
from early June and August 1984. All scenes 
are essentially cloud free and have been 
corrected for atmospheric haze using the 
darkest object subtraction method of Crane 
(1971). 
7. GROUND DATA COLLECTION 
Soil and vegetation samples form the 
main ground data set used in the study. A 
survey grid comprising 50 m line and station 
spacings provided the required ground con 
trol for the sampling. Soil samples were 
collected at the base of the B-horizon and 
needle samples gathered from the lower 
branches of the spruce trees. Tree sampling 
took place in September and consisted of ap 
proximately 500 g samples of needles and 
twigs containing up to five or six year old 
needles. 
A 
collect* 
analyse^ 
content 
photome- 
from 10- 
60-6300 
20-940 ] 
vary fr< 
30-340 ] 
2-5 ppm 
8. ANAL 1 
Th< 
the rel; 
and spe< 
dif ferei 
applyin« 
various 
referenc 
of the : 
spatial 
data sei 
merging 
the groi 
correspc 
TM pixel 
had to 1 
age soil 
values c 
present: 
Soil anc 
of the 1 
merging 
Landsat 
the tes1 
dot gric 
76 metre 
instante 
MSS and 
The 
pixels c 
1981 MSE 
and in i 
9. STAT1 
Lir 
lysis oi 
establie 
needle, 
the cori
	        

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