Mapping National Park landscape from ground, air and space

被引:15
作者
Bird, AC [1 ]
Taylor, JC [1 ]
Brewer, TR [1 ]
机构
[1] Cranfield Univ, Sch Agr Food & Environm, Bedford MK45 4DT, England
关键词
D O I
10.1080/01431160050110250
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Aerial photograph interpretation and field mapping were used in a series of experiments to evaluate the use of Landsat and Systeme Probatoire pour l'Observation de la Terre (SPOT) satellite imagery for landscape mapping. The 'Monitoring Landscape Change in the National Parks' (MLCNP) Project mapped landscape in each of the National Parks of England and Wales in terms of 38 land cover classes with significant visual impact. The main source of data was aerial photography but satellite imagery for selected areas was also analysed. It was found that single-date multi-spectral imagery could be classified to an acceptable level of agreement with ground data only if the 38 sub-classes of the interpretation scheme were grouped into the seven main class headings. Visual interpretation of SPOT panchromatic imagery at the 38 sub-class level proved comparable with aerial photograph interpretation for an area of the North York Moors. This paper describes the approaches taken in data analysis and presents the main results obtained. The use of confusion matrices allowed measurements of agreement to be made between the three sources of data. A significant problem in mapping landscape was to arrive at unambiguous class definitions when many of the categories had no clear boundaries on the ground. Confusion matrix analysis, together with the use of a hierarchical classification scheme, allowed links to be made between data collected from ground, air and space. Some classification problems were attributable to all sources of data due to inherent difficulties with the classification system.
引用
收藏
页码:2719 / 2736
页数:18
相关论文
共 17 条
[1]   Fine spatial resolution satellite sensors for the next decade [J].
Aplin, P ;
Atkinson, PM ;
Curran, PJ .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (18) :3873-3881
[2]   ADVANCES IN CLASSIFICATION FOR LAND COVER MAPPING USING SPOT HRV IMAGERY [J].
BAKER, JR ;
BRIGGS, SA ;
GORDON, V ;
JONES, AR ;
SETTLE, JJ ;
TOWNSHEND, JRG ;
WYATT, BK .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1991, 12 (05) :1071-1085
[3]   AN UNSUPERVISED APPROACH TO THE CLASSIFICATION OF SEMINATURAL VEGETATION FROM LANDSAT THEMATIC MAPPER DATA - A PILOT-STUDY ON ISLAY [J].
BELWARD, AS ;
TAYLOR, JC ;
STUTTARD, MJ ;
BIGNAL, E ;
MATHEWS, J ;
CURTIS, D .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1990, 11 (03) :429-445
[4]  
BUNCE RGH, 1992, ITE SYMP, V27, P69
[5]  
EALES RP, 1989, THESIS SILSOE COLL U
[6]   CLASSIFICATION OF TM IMAGERY IN THE STUDY OF LAND-USE IN LOWLAND BRITAIN - PRACTICAL CONSIDERATIONS FOR OPERATIONAL USE [J].
FULLER, RM ;
PARSELL, RJ .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1990, 11 (10) :1901-1917
[7]  
FULLER RM, 1994, PHOTOGRAMM ENG REM S, V60, P553
[8]  
HANUSCHAK G, 1979, TECHNICAL B USDA EC, V1609, P1
[9]   GLOBAL ESTIMATES FROM CONFUSION MATRICES - A REPLY TO JUPP [J].
HAY, AM .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1989, 10 (09) :1571-1573
[10]  
HUDSON WD, 1987, PHOTOGRAMM ENG REM S, V53, P421