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Remote sensing for resources development and environmental management (Volume 1)

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CC BY: Attribution 4.0 International. You can find more information here.

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:
Farm development using aerial photointerpretation in Ruvu River Valley, Ragamoyo, Tanzania, East Africa. B. P. Mdamu & M. A. Pazi
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

486 
MAPSYMBOL 
DESCRIPTION OF PHYSIOGRAPHY 
SOIL CLASSIFICATION 
A 
Deep poorly drained heavy soils on level 
plain with recent alluvial deposits. 
flat flood 
1. 
2. 
3. 
Utric Fluvisols 
Utric Gley sols 
Pellic vertisols 
C 
Deep excessively drained sands, sands to sandy lo 
ams over sandy clayson level to gently undulating 
coastal plain. 
1. 
2. 
3. 
4. 
Albic Arenosols 
Cambie 'Arenosols 
Othic Luvisols 
Eutrigle sols 
soil properties considered in describing 
the profiles. In this survey the level of 
mapping the area was limited only to main 
land type. 
2.5 Map compillation and Field work 
During field work, location of pits and 
observation on mapping Unit, boundaries 
were marked on 1:100,000 topographical map. 
Field surveying traverses were made along 
the farm boundary and across the farm area. 
Nearly, all profile pits were dug to depths 
of 150cm in order to check the ground water 
table and the soil parent material. Each 
horizon in a profile was examined for the 
study of soil development. The major pa 
rameters commonly looked for in the profile 
are depth of individual horizon, colour 
(dry and moist), texture, structure, consi 
stency porosity, parent material, presence/ 
absence of roots and fauna, presence of 
carbonates, concretions and cracks. pH, 
Conductivity, texture were measured separa 
tely in the laboratory together with other 
chemical analyses. Colour notations were 
referred to the Munsel Coloiir Chart (Soil 
Test inc. USA, 1971 Edition). Profile 
pits were described using (Guidelines for Soil 
Profile Pescription - FA0) and soil samples 
were sent to the Laboratory for some physi 
cal and chemical analyses. The final soil 
map was produced at a scale of 1:10,000 
as proposed by the client to facilitate 
farm planning and land use purposes. 
Due to field obstacles earlier observed 
during the reconnaisance field trip, soil 
observations at the far southern parts of 
the project area on the alluvial plain, 
were not made. Soils in these parts were 
extrapolated from aerial photo-interpre 
tation and the physiographical map. Nor 
mally the alluvial plain area, consists 
of poorly drained heavy clay soils subje 
cted to frequent flooding by river over 
flow’s of the Ruvu River, whereas the Coa 
stal Plain soils range from deep excessi 
vely drained sands to sandy clay loams. 
3. SOIL CLASSIFICATION AND MAPPING 
3.1 Soil Laboratory data and results 
1. pH and Ec were determined by using 
the 1:5 soil to water ratio method. 
2. Particle size analysis was carried 
out using the hydrometer. 
3» Available phosphorus was determined 
by using the Dickman and Bray 1 method. 
4. Exchangeable cations Na, K, Ca, Mg, 
were determined by leaching the soils in 
Ammonium Acetate extracting solution IN. 
5. Organic carbon % was determined by 
using the Walkley and Black method. 
6. Available Nitrogen % was determined 
using the Alkaline permanganate method. 
7. C.E.C. was not determined but was 
approvimated by adding the total of bases. 
3.2. Results 
1. From soil analytical data the soils 
in the area are non-saline. However the 
subsoils have an increased amount of solu 
ble salts. In general the pH of the soils 
indicate that the soils are acidic. It 
will be necessary to raise the pH to about 
7.0 as the pH common to most plants is 6-8. 
SCALE 1:500,000. 
MI 
QUATERNARY. 
Coastal plain deposits reworked clays 
silts, sands and rare grovels 
QUANTERNARY 
Alluvial deposits (clays, silts, sands and 
rare gravels.) 
NEOGENS (MIOCENE PLIOCENE) 
Undifterentated sedimentary deposits interbecfded .sandy 
c * :y , and clayey sands ¿ravel scattered thoughoul in a 
clay matrix 
Cretaceous 
thin 
san d stones 
sandy limestones and shales 
Figure 3 Geology* of the farm area
	        

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