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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:
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
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

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Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
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 
Harbin Remote Sensing Sub-centre of Heilongjiang Academy of Agricultural Sciences, China 
ABSTRACT: Through the measurements and analysis of the growing condition and the yield of grain in 24 sample- 
sites located in the field of BeiAn city with the spectral radiometers (WFD9), we have got the result that 
Spring Wheat possesses most distinguishing features of reflective spectrum like those of other green plants, 
but it has its own special feature. The curves of spring wheat reflection usually change with its different 
growing stage and has certain rule of change. The reflective data of the radio between the band 5 and band 7 
(MSS) seems to be closely related with the yield by using the method of regression. The results reinforce the 
potential to us that we can forecast the yield of spring wheat before the harvest with measurements of radio 
meter . 
1. METHODS AND MATERIALS 
The field experiment was located on the Black earth 
in BeiAn city (47 40’-48 40’N, 126-127 50’ E) Heilon 
Jiang Province. According to the historical yield of 
BeiAn city, the field was divided into two levels of 
yield: the high yield and the mid yield. 
A Model "WFD9" radiometer with 16 field of view was 
used to measure radiances corresponding to the Land- 
sat MSS band 4, 5, 6, and 7, representing 0.5-0.6, 
0.6-0.7, 0.7-0.8 and 0.8-1.1 um wavelenth, respec 
tively. The reflectances were measured with two 
radiometers (WFD9) on clear days throughout the 
growing season of spring wheat. Readings were obtained 
on 15 days during the growing season. 
Our original intent was to use the reflectances 
of spring wheat to establish the spectrumyieId 
model and attempted to estimate the yield of spring 
wheat with the measurement of spectral radiometer. 
2. RESULTS AND DISCUSSION 
In table 1, there is no difference in the reflectance 
tendency of different crops, but in the band 6 or 7, 
the differnces of reflectances are notable, it approa 
ched from 13.2% to 41%. see fig.l. 
In table 2, the difference of reflectance of the 
variant growing stage of spring wheat also possesses 
the same rule. The value of difference in the band 7 
approached 7.86% to 19.31% 
On figure 2 and 3, we have found the reflectance can 
be used to moniter the growing strenth of spring 
wheat. The reflectance of plants growing well is 
higher than that of plants growing badly. The 
difference in band 7 is very significant. The absorp 
tion of sunshine is lesser and its reflection is 
greater because the chlorophyll content of plants is 
lesser at seedling and nodal stage. The absorption 
and reflection of sunshine are stronger and weaker, 
respectively, because the chlorophyll content of 
plants is higher from hesding stage to milky matu 
rity stage. 
The reflective data of the ratio between the band 
5 and band 7 seem to be closely related with the 
yield by using the method of regression. We have 
obtained the primary spectrumyield modal of spring 
wheat as follows: 
Y= -567.27 + 974 X (high yield spectrumyield model) 
R = 0.87 
Y= -907.3 + 2485 X (mid yield spectrumyield model) 
R = 0.93 
(note: X = log IR/R) 
Figure 2. The spectral curves of spring wheat 
growing well and badly in heading stage.
	        

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