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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:
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
Document type:
Multivolume work
Structure type:
Chapter

Chapter

Title:
The application of remote sensing in Song-nen plain of Heilongjiang province, China. Zhang Xiu-yin, Jin Jing, Cui Da
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

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
545 
The application of remote sensing in Song-nen plain 
of Heilongjiang province, China 
Zhang Xiu-yin, Jin Jing, Cui Da 
Subcenter of Agricultural Remote Sensing Heilongjiang Academy of Agri. Science, China 
ABSTRACT: This report describes the development and the results that obtained though the practical application 
of remote sensing technology to evaluate and classify the natural resources and land use in Song-nen plain of 
Efeilongjiang province in 1985. The method were used visual interpretation and multitemporal analysis techniques 
to derive information from lanasat images and combined with topograph maps as well as airphotos which were used 
for the detail of the area that was not clear on the landsat images and for measuring; the coefficient of land 
use. The thematicmaps at 1:200000 scales prepared on land use and other specialistic maps. This result gave a 
way of how the natural resources and land use in our province can be inventory, evaluation and management by 
using remote sensing data on the cost minimizing basis. 
1 INTRODUCTION 
Song-nen plain is the main region of both Heilongjia-^ 
ang province and nation for agricultural and animal 
husbandry. It's located in the west part of Heilong 
jiang province China. The total area of Song-nen 
plain, is 103 thousend square kilometers. It's between 
Song Hua river and Nen Jiang river and surroundings. 
This is first time to inventory, evaluate and classi 
fy the natural resourcers and land use by using remo 
te sensing data from landsat images.The aim of the 
study is that to explore a way by using remote sens 
ing data accoding to our province condition, and to 
know how mach the natural resources con be used as 
well as how the land was used in the past years. 
2 GENERAL DESCRIPTION 
Song-nen plain is situated in fhe west part of Heilo- 
ongjiang province,China. It's between latitude 44 10' 
N—48 35 'N and longitude 121 20' E— 128 05 ' E - Main 
part of the area (center and south-west part'is low 
plain which altitude about 120 — 200 M above the sea 
level and studded with lakes, reservoirs, ponds and 
pools.Tn the north-east part of the plain is gentle 
slop hills. The clamate of this region belongs to 
semiarid. The rainfull of the area is about 350-500 
mm, and 60 percent concentrated in July and August. 
( Figure 1 ). 
3 MATERIALS 
This study is based on infomation obtained from MSS 
landsat images( at H2 00000 scale )combined with to 
pograph maps ( at 1:506000 scale ) and airphotos whi 
ch were used for the detail of the area where was not 
clear on the landsat images. The images selected were 
E - 22457, E-30930, E-22438, E-22276, E-22261, E-312- 
01, E-22296, E-30192 etc. Total of number were 18 
sheets, in defferent months and years. The false col- 
lor composite were made by applying different filter 
and techiques and that to be more effective for in 
terpretation land use. The sample area, the landsat-D 
TM image were used also. 
4 THE METHOD 
This invintory of natural resources and land use was 
based on visual interpretation from landsat images 
and to go to the field for check. 
The steps of the work as follow: 
1. Preparation 
It included that landsat images ( both MSS and TM at 
a scale 1:200000 ), topograph maps ( at 1:50000 scale 
and airphotos were collected, basic maps and transpa- 
rencemaps were made (both at scale 1:200000 ). 
2» Interpretation of landsat images in lab. 
First, interpretation marks were established by going 
to the field and in the lab. and then defined stanard 
of classification and delineated of the interpreta 
tion from landsat images. The samjbre area were sele 
cted also in this step. 
3. Field work for vhe interpretation check. 
It’s included that check for the accuracy of inter 
pretation and correct the errorwhich were interpre 
ts ted. 68 number of sampling area for checking , and 
the total number of checked field were 11 5. The area 
of checked were about 73.647 thousend hac. and about 
10% of the total area. The accuracy of interpretation 
was 94-7 percent. 
4. Making the final maps and measurement calcula 
ting the areas. 
The final maps completed were present land use map 
and natural resourcem maps such as natural pasture 
and grassland map, forest map, water resourees map 
and reed distribution map of Song-nen plain at a sca 
le 1:200000. 
The method of calculation area was that if the cal 
culated area was larger than 1 cm square on the map 
which were measured by planimeter and the calculated 
area was smaller than 1 cm square which was measured 
by caunting the squares that f r0 m the standard trans 
parent square paper which covered on final map. 
The total area = the number of squares times 
one square representative area 
The classification of land use as follow5 
Agricultural land ( including cultivated land, paddy 
field and permanent vegetable field ). 
Range land ( including natural pastureland and grass 
land ). 
Wood land ( including forest, shrub and brushes ). 
Water area ( including rivers and lakes, reservoirs, 
ponds and pools ). 
Urban or built up areas (including cities and towns, 
and industry areas ). 
Reed land 
Communication land ( including railway and road area) 
Unutilization land ( including marsh land, sand land, 
bare rock and soline-alkaline land).
	        

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