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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:
2 Microwave data. Chairman: N. Lannelongue, Liaison: L. Krul
Document type:
Multivolume work
Structure type:
Chapter

Chapter

Title:
SLAR as a research tool. G. P. de Loor & P. Hoogeboom
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

115 
Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
SLAR as a research tool 
G.P.de Loor & P.Hoogeboom 
Physics and Electronics Laboratory TNO, The Hague, Netherlands 
ABSTRACT: In the early seventies for seme time an EME real aperture X-band SLAR with imaging on film was 
flcwn in the Netherlands. It shewed many new and unexpected phenomena, in particular over the sea. It soon 
became clear that for a closer investigation of these phenomena an absolute and digital system is necessary. 
Being simple and straightforward and still giving sufficient coverage and resolution for the research 
purposes under consideration, a real aperture system was chosen. Its final construction and implementation 
required the efforts of several institutes. Radiometric and creometric errors caused by unwanted aircraft 
motions can new be corrected during the data processing and resampling, resulting in a presentation of the 
data in a map corrected format. The radicmetric accuracy of the system and its internal and external 
calibration are discussed. 
1. INTRODUCTION 
Already since the early sixties side-looking radars 
have been flcwn over the Netherlands with as a 
result the detection of many new and interesting 
phenomena (de Loor 1981). They delivered images on 
film of which the respective grey tones had only a 
vague undefined relation with the radar backscatter 
of the observed phenomena. Therefore, when the Dutch 
remote sensing program proceeded, it soon became 
clear that such simple imaging systems were not 
sufficient. The major advantage of radar - apart from 
the fact that it can be used day and night and 
through clouds - is the fact that it can produce 
absolute figures for the backscatter. Good examples 
in this respect are the windscatterometers in 
satellites as SEASAT and the ERS-1. 
Ihe Dutch remote sensing program emphasizes the 
various aspects of the interaction of the sensor 
(the radar in this case) and the objects observed in 
order to design optimum sensors and data handling 
procedures which require a minimum of signal 
transmission bandwidth and -time. Therefore 
groundbased measurements have been carried out on 
agricultural crops (de Loor et al 1982) and the sea 
surface (de Loor and Hoogeboom 1982) and a large 
data base is new available in the Netherlands. In 
this way an insight was gained in the use of radar 
for e.g. classification, monitoring, oil detection, 
etc. It was also found that the good use of radar 
asks for special procedures which require accurate 
observation systems. Therefore the choice was made 
for a SLAR system with digital data recording, 
internal calibration, and accurate absolute data 
handling. A real aperture system is the least 
costly, relatively simple and straightforward, and 
still gives sufficient coverage for research 
purposes. 
2. DYNAMIC VERSUS GEOMETRIC RESOLUTION 
When speaking about resolution one usually means 
geometric resolution. Dynamic resolution ("contrast" 
in photography), hewever, is just as important. 
Measurements (de Loor et al 1982; de Loor and 
Hoogeboom 1982) have shewn that in the microwave 
window the variation in radar backscatter between 
areas of interest (e.g. due to waves at sea, due to 
different crop species on land, etc.) are small: a 
10 to 20 dB at maximum. To differentiate between 
these different targets (e.g. between crops) the 
radar must have a high dynamic resolution: better 
than J. dB, This is a seyepe requirement in itself 
b-’h there is another problem due to the coherence of 
the illumination we use in radar. The targets 
mentioned are all compound targets with dimensions 
larger than the pixel size. Within a pixel they all 
contain many scatterers as e.g. the stems and leaves 
in a vegetation canopy. The reflection measured by a 
radar will be the vector sum of the reflections at 
the individual scatterers. Because of their movement 
this vector sum will vary with time. The-return 
signal to the radar so fluctuates with time and its 
strength varies according to a Rayleigh distribution. 
This means that single independent observations can 
vary considerably. This is the well knewn speckle 
in many radar images. To obtain an accurate value 
for the backscatter coefficient averaging over a 
sufficient number of independent observations is 
necessary. The more the number of independent 
observations, N, the better and smoother the grey- 
tone. See figure 1. The eye does better in this 
respect (Moore 1979) than a machine, since 
unconsciously the eye averaaps over neighbouring 
pixels. An image of pixels with №=5 to 10 looks nice 
but is difficult to handle for a machine (variation 
between pixels: +2.5 dB). 
So speckle is inherent to radar images and must be 
taken into account. Among others it can obscure 
texture or - wrongly - be seen as texture (Churchill 
and Wright 1984). Three approaches are possible to 
deal with it: averaging within a pixel, averaging 
per area, or a combination of both. In the Dutch 
SLAR averaging within a pixel is used. This averaging 
is either over 8 independent samples (geometric 
resolution 7.5 x 7.52m ) or over 30 (geometric 
resolution 15 x 15 in ) which gives an accuracy per 
pixel for a compound target of respectively + 2.5 dB 
or + 1 dB. This is insufficient for many 
applications, among others in crop classification, 
and therefore Hoogeboom (1986) also uses averaging 
per field. 
3. MEASURES TAKEN IN THE DUTCH DIGITAL SLAR 
The above assumed that the independent observations 
taken by the radar are absolute values (are 
radiometrically correct). This requires a series of 
measures in the system, which indeed were taken in 
the Dutch digital SLAR. They will now be described 
shortly. This can best be done with the aid of the 
radar equation:
	        

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