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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:
The determination of optimum parameters for identification of agricultural crops with airborne SLAR data. P. Binnenkade
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

111 
Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 
The determination of optimum parameters for identification 
of agricultural crops with airborne SLAR data 
P.Binnenkade 
National Aerospace Laboratory NLR, Amsterdam, Netherlands 
ABSTRACT: The SLAR campaigns of the Dutch ROVE-Team "Crop Identification" in the years 1983-1985 are 
discussed. From data—acquisition through classification the determining parameters are elaborated. The 1985 
campaign which used steeper incidence angles in order to simulate satellite data, and is thus different from 
previous ROVE-campaigns, is discussed. 
1 INTRODUCTION 
Microwave remote sensing has played an important 
role in The Netherlands Remote Sensing community 
since the late sixties. Especially the work on the 
radar backscatter of vegetation canopies has always 
been given great emphasis. The ROVE-team (ROVE 
stands for Radar Observation of VEgetation), which 
has been involved in all land-applications of micro- 
wave remote sensing in The Netherlands, then and 
today consists of representative scientists and 
technicians from the following institutes: 
- Agricultural University of Wageningen and its 
associated institutes 
- Delft University of Technology, Microwave Group 
- Physics and Electronics Laboratory TNO 
- National Aerospace Laboratory NLR. 
Starting with a pulse-type X-band measuring radar 
operating from a TV-tower in 1968, the ROVE-group 
nowadays makes use of a calibrated digital SLAR 
(Fig. 1) mounted in the NLR Metro II Laboratory air 
craft and a multiband airborne scatterometer 
(DUTSCAT) installed in the NLR Queen Air laboratory 
aircraft in combination with supporting ground truth 
instrumentation. 
One of the principal aims of the ROVE-group is the 
identification and classification of agricultural 
crops from microwave data. 
Such data (obtained from airborne or spaceborne 
sensors) contain only one type of information: radar 
backscatter as a function of position. This radar 
backscatter is the condensed result of a great 
number of contributing factors. Even when confined 
to only one frequency the radar return is influenced 
by: 
- polarization effects 
- illumination function 
- incidence (grazing) angle 
- crop height 
- crop coverage 
- vegetation-structure parameters 
- soil roughness 
- moisture content. 
Some of these factors may be considered fixed and 
measurable whereas others can be influenced and 
changed by setting the radar and/or antenna and by 
flight-geometry modifications. 
Nevertheless, due to the complexity of the above 
parameters, work on theoretical models became indis- 
pendable (Ulaby, Attema, Hoekman). At an early stage 
it was recognized that this modelling work had to be 
supported by ground-based measurements on crops and 
soils. Special emphasis was given to the need for 
simplicity in the models to limit the number of un 
known parameters (Ref. 1). 
2 CROP IDENTIFICATION 
One of the specialized sub-groups of ROVE is the 
workinggroup "Crop Identification" in which the 
following institutes participate: 
- Centre for Agrobiological Research CABO 
- Delft University of Technology, Information Theory 
group 
- Physics and Electronics Laboratory TNO 
- National Aerospace Laboratory NLR. 
The workinggroup has chosen to undertake two 
parallel paths of (applied) research: 
1. Research into (hierarchical) classification 
methods for radar data. 
2. Initiation and execution of semi-operational 
application programmes. 
As for the latter, upon request from The Nether 
lands agricultural authorities an application pro 
gramme has been carried out in 1983 and 1984 to 
monitor crop rotation, especially potatoes, in a 
number of (ecologically-different) regions within 
The Netherlands. Crop disease control authorities 
allow potatoes to be grown only once every three 
years on any one field (if no other protective 
measures are taken); thus it has become desirable 
to monitor adherence to this practice. 
The group was asked to devise a method to uniquely 
discriminate potatoes from all other crops, hence 
time-consuming ground investigations be reduced. 
Three test-sites with an area each of 20*4 km 
were chosen in the Flevo-polders, Groningen and 
Brabant province respectively. 
3 THE DUTCH DIGITAL SLAR 
Sideways-looking airborne radar (SLAR) is an in 
strument which allows for data to be acquired on a 
line- to-line basis. The calibrated digital SLAR 
(X-band) uses a digital recording system where 
each line is formed on a point-to-point basis 
(Table 1). The received radar backscatter varies 
widely in a stochastic way when natural surfaces 
and -objects are observed; good estimates of the 
backscatter coefficient can only be made by com 
bining a large number of independent measurements. 
The Netherlands SLAR has been designed to do so 
(Table 1).
	        

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