ISSN:0143-1161    

DOI:10.1080/014311697218124

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor

摘要:

The characteristic temporal backscattering signature of rice crop grown under flooded condition was used to estimate rice acreage for a region in West Bengal, India. To date ERS-1 Synthetic Aperture Radar (SAR) data, one acquired within 30 days of transplantation and another after 30-40 days was found to be optimum for early estimation of rice acreage. The rice crop was found to be distinctly separable from forest, tree vegetation, village/urban areas. Misclassification of rice was observed mainly with water, waterlogged areas and fallow fields.

ISSN:0143-1161    

DOI:10.1080/014311697218133

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor

摘要:

A Landsat Thematic Mapper (TM) natural colour composite allowed the discrimination of areas of hydrothermally altered materials, even where vegetation (mainly herbaceous plants) covered portions of the terrain. Field spectra data showed that broad iron-oxide absorption features in TM 1 and TM 2 bands enabled the spectral discrimination between areas of hydrothermally altered materials and areas of soils derived from biotite-granites. In order to improve the definition of the target areas, the TM images were merged with a digitized aerial photograph through IHS technique. The resulting high resolution hybrid images were segmented using a region growing method, which generated images partitioned into a number of homogeneous regions. The segmented images were classified using an unsupervised clustering region classifier algorithm. The result, compared with field observations, demonstrated that the method eliminated the subjectivity of the visual image interpretation and increased the accuracy in the delineation of the hydrothermally altered areas.

ISSN:0143-1161    

DOI:10.1080/014311697218142

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor

摘要:

The accuracy of snow depth estimation is affected significantly by the regional surface type. We have developed a theoretical model of vector radiative transfer (VRT) for snowpack/vegetation canopies at SSM/I channels. The vegetation canopy is modelled by a layer of nonspherical particles, and the snowpack is modelled as a layer of dense spherical particles. By numerically solving two coupled VRT equations for multi-layer models of different surface types such as tree/snow, grass/snow and snowpack only, two scattering indices SI1 = T B19v - T B37v and SI2 = T B22v - T B85v are obtained for a variety of snow depths (SD) and ice-grain sizes. These results are combined as a mesh graph in the figure of SI1 versus SI2 . When the SSM/I TB data is observed, its location in the mesh graph can indicate the estimation of SD. Our results compare well with the SSM/I data of the U.S.A. east coast January blizzard, 1996.

ISSN:0143-1161    

DOI:10.1080/014311697218151

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor

摘要:

Recently the 'soft' classification approach has gained in popularity against the discrete (hard) classification of land cover from remotely-sensed imagery. An empirical study is presented to test training procedures with neural networks for soft (mixture) classification. The results show thatland cover mixtures are best recognized following training with two-component mixed pixels, and that linearly re-scaled or binned target vector representations are equally satisfactory. Interestingly, dominant classes within pixels are also better recognized by training with wider varieties of class mixtures.

ISSN:0143-1161    

DOI:10.1080/014311697218160

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor

ISSN:0143-1161    

DOI:10.1080/014311697218179

出版商:Taylor & Francis Group    

年代:1997

数据来源: Taylor