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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:
The canopy hot-spot as crop identifier. S. A. W. Gerstl, C. Simmer & B. J. Powers
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
  • 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
  • Remote sensing in the evaluation of natural resources: Forestry in Italy. Eraldo Amadesi & Rodolfo Zecchi, Stefano Bizzi & Roberto Medri, Gilmo Vianello
  • Visual interpretation of MSS-FCC manual cartographic integration of data. E. Amamoo-Otchere
  • Optimal Thematic Mapper bands and transformations for discerning metal stress in coniferous tree canopies. C. Banninger
  • Land use along the Tana River, Kenya - A study with small format aerial photography and microlight aircraft. R. Beck, S. W. Taiti, D. C. P. Thalen
  • The use of multitemporal Landsat data for improving crop mapping accuracy. Alan S. Belward & John C. Taylor
  • Aerial photography photointerpretation system. J. Besenicar, A. Bilc
  • Inventory of decline and mortality in spruce-fir forests of the eastern U.S. with CIR photos. W. M. Ciesla, C. W. Dull, L. R. McCreery & M. E. Mielke
  • Field experience with different types of remote-sensing data in a small-scale soil and land resource survey in southern Tanzania. T. Christiansen
  • A remote sensing aided inventory of fuelwood volumes in the Sahel region of west Africa: A case study of five urban zones in the Republic of Niger. Steven J. Daus & Mamane Guero, Lawally Ada
  • Development of a regional mapping system for the sahelian region of west Africa using medium scale aerial photography. Steven J. Daus, Mamane Guero, Francois Sesso Codjo, Cecilia Polansky & Joseph Tabor
  • A preliminary study on NOAA images for non-destructive estimation of pasture biomass in semi-arid regions of China. Ding Zhi, Tong Qing-xi, Zheng Lan-fen & Wang Er-he, Xiao Qiang-Uang, Chen Wei-ying & Zhou Ci-song
  • The application of remote sensing technology to natural resource investigation in semi-arid and arid regions. Ding Zhi
  • Use of remote sensing for regional mapping of soil organisation data Application in Brittany (France) and French Guiana. M. Dosso, F. Seyler
  • The use of SPOT simulation data in forestry mapping. S. J. Dury, W. G. Collins & P. D. Hedges
  • Spruce budworm infestation detection using an airborne pushbroom scanner and Thematic Mapper data. H. Epp, R. Reed
  • Land use from aerial photographs: A case study in the Nigerian Savannah. N. J. Field, W. G. Collins
  • The use of aerial photography for assessing soil disturbance caused by logging. J. G. Firth
  • An integrated study of the Nairobi area - Land-cover map based on FCC 1:1M. F. Grootenhuis & H. Weeda, K. Kalambo
  • Explorations of the enhanced FCC 1:100.000 for development planning Land-use identification in the Nairobi area. F. Grootenhuis & H. Weeda, K. Kalambo
  • Contribution of remote sensing to food security and early warning systems in drought affected countries in Africa. Abdishakour A. Gulaid
  • Double sampling for rice in Bangladesh using Landsat MSS data. Barry N. Haack
  • Studies on human interference in the Dhaka Sal (Shorea robusta) forest using remote sensing techniques. Md. Jinnahtul Islam
  • Experiences in application of multispectral scanner-data for forest damage inventory. A. Kadro & S. Kuntz
  • Landscape methods of air-space data interpretation. D. M. Kirejev
  • Remote sensing in evaluating land use, land cover and land capability of a part of Cuddapan District, Andhra Preadesh, India. S. V. B. Krishna Bhagavan & K. L. V. Ramana Rao
  • Farm development using aerial photointerpretation in Ruvu River Valley, Ragamoyo, Tanzania, East Africa. B. P. Mdamu & M. A. Pazi
  • Application of multispectral scanning remote sensing in agricultural water management problems. G. J. A. Nieuwenhuis, J. M. M. Bouwmans
  • Mangrove mapping and monitoring. John B. Rehder, Samuel G. Patterson
  • Photo-interpretation of wetland vegetation in the Lesser Antilles. B. Rollet
  • Global vegetation monitoring using NOAA GAC data. H. Shimoda, K. Fukue, T. Hosomura & T. Sakata
  • National land use and land cover mapping: The use of low level sample photography. R. Sinange Kimanga & J. Lumasia Agatsiva
  • Tropical forest cover classification using Landsat data in north-eastern India. Ashbindu Singh
  • Classification of the Riverina Forests of south east Australia using co-registered Landsat MSS and SIR-B radar data. A. K. Skidmore, P. W. Woodgate & J. A. Richards
  • Remote sensing methods of monitoring the anthropogenic activities in the forest. V. I. Sukhikh
  • Comparison of SPOT-simulated and Landsat 5 TM imagery in vegetation mapping. H. Tommervik
  • Multi-temporal Landsat for land unit mapping on project scale of the Sudd-floodplain, Southern Sudan. Y. A. Yath, H. A. M. J. van Gils
  • Assessment of TM thermal infrared band contribution in land cover/land use multispectral classification. José A. Valdes Altamira, Marion F. Baumgardner, Carlos R. Valenzuela
  • An efficient classification scheme for verifying lack fidelity of existing county level findings to cultivated land cover areas. Yang Kai, Lin Kaiyu, Chen Jun & Lu Jian
  • The application of remote sensing in Song-nen plain of Heilongjiang province, China. Zhang Xiu-yin, Jin Jing, Cui Da
  • Cover

Full text

s forest 
frared film 
3 0T 
predicts 
I as a 
ly. As ror 
ssume that 
e uniformly 
dependently 
n addition, 
ice of the 
imptions, we 
i the layers 
itributed in 
ise can be 
he distance 
; the leaf 
iresent here 
ibution of 
lorizontally 
diam.) 
dz + 
dz (3) 
where, since the probability is azimuthally 
independent, we have represented the solar zenith 
and view angles as scalar quantities 52 and S2 , 
respectively. Here, L is the thickness of the 
canopy, p = d(LAI)/dz, and r 5 i/| tan(S2)-tan^ 0 ) | . 
If L is less than r, 
L 
r z 
f 
r Z 1 
p(z) exp 
- 
pdu 
4 
exp 
- 
£<^du 
r 
When p is independent of height in the canopy, 
P(2,a 0 ) = \ |ex P (H> 
r 
exp(-2pr)-exp(-2pL) 
exp(-pz)exp 
(-£!!) 
V 2r ' 
dz 
(5; 
Analytic Model for HOT SPOT 
-100 -75 50 -25 0 25 50 75 100 
View Angle (Degree) 
Figure 6. Analytic two-dimensional model of hot-spot 
for solar zenith angles from 0 to 60 deg. 
Here, pL = LAI. The integral in eqn. (5) can also 
be expressed in terms of error functions. For 
values of S equal to zero or equal to Q q , this 
expression reduces to l-exp(-LAI) or 
l/2(l-exp(-2LAI)), respectively. These results are 
identical to those obtained from eqs. (1) and (2) 
by taking the limit as c (= LAI/L) tends to zero. 
The expressions for P(*S2,S2 0 ) given by eqs. (3) and 
(5) are functions of the canopy variables p, i and L 
and the angles S2 and Q q . P(S2,S2 Q ) is independent of 
the height of the observer above the canopy. Using 
eqn. (3) the effect of varying the canopy and 
angular variables can be studied. Figure 5 shows 
the effect of varying the solar zenith angle. The 
maximum probability is independent of solar zenith 
angle and occurs when the view angle is in the 
retro-direction. For normally incident radiation 
the probability is symmetric about the 
retro-direction; however, this is not true for other 
incident directions. This effect is due to the 
stronger correlation between illuminating a leaf and 
being able to see an illuminated leaf for view 
angles closer to zero degrees. Figure 6 depicts the 
influence of leaf length i on P(S2,S2 0 ) for leaf 
lengths from 1 to 15 cm. Increasing only the leaf 
size, increases the size of the holes in the canopy; 
and consequently, it increases the angle over which 
both the incident and reflected radiation can use 
the same hole. This increased correlation between 
the incident and reflected radiation produces a 
broader hot-spot, as is evidenced in Fig. 6. 
These simplistic models do not take into account 
any transmittance through the leaves or any multiple 
Analyt ic Model for HOT SPOT 
-100 75 -50 -25 0 25 . 50 75 100 
View Angle (Degree) 
Figure 5. Analytic two-dimensional model of hot-spot 
for leaf lengths from 1 to 15 cm. 
scattering. Both effects are important tor plant 
canopies, especially in the near-infrared wavelength 
region. Therefore, we developed a theoretical model 
to include mutual shading of leaves within a plant 
canopy in our multiple scattering radiation 
transport code 6 . The model also takes into account 
the vertical profiles of leaf size, leaf area index 
and leaf angular distribution. A shading function 
is derived, which gives the percentage of the 
reflected radiation intensity as a function of the 
angle relative to the sun direction. The computed 
angular distribution of the reflected solar 
radiation above the canopy thus contains the 
hot-spot effect and can be used as input for 
atmospheric radiative transfer calculations to 
obtain the radiation distribution above the 
atmosphere, which simulates the signal measured by a 1 
satellite. Initial results indicate that hot-spot 
characteristics remain almost invariant to 
atmospheric perturbations in the visible and 
near-infrared wavelength regimes 7 . 
REFERENCES 
1. G.H. Suits, 1972. Remote Sensing Envir. 2, 117. 
2. R. Greenler, 1980. Rainbows, halos, and glories, 
Cambridge Univ. Press. 
3. B. W. Hapke, 1968. Planet. Space Sci., 16, 101. 
4. K. Lumme, 1971. Astroph. Space Sci., 13, 219. 
5. N.J.J. Bunnik, W. Verhoef, R.W. deJongh, H.W.J. van 
Kasten, R.H.M.E. Geerts, H. Noordman, D. Ueni, and 
Th. A. de Boer, 1984. Proc. of 18th Int. Symp. Rem. 
Sens. Envir., Paris, France, Vol. II, 1033-1040. 
6. S.A.W. Gerstl and C. Simmer, 1986. Remote Sensing 
Envir., august issue 
7. C. Simmer and S. A. W. Gerstl, 1985. IEEE Trans. 
Geosci. and Rem. Sensing, Vol. GF.-23, No. 5, 648. 
Note, equations (3) through (5) are valid only 
when the observer is in the principal plane. 
Extensions of these results to other observation 
directions are easily obtained.
	        

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