A spatial processing algorithm to reduce the effects of mixed pixels and increase the separability between classes

Pattern Recognition

Volumn 17, Issue 5, 1984, Pages 525-533

  Merickel, Michael B ^a   Lundgren, James C ^a   Shen, Sylvia S ^a  

^a Lockheed Engineering Management Services Company Inc ^*  (United States)

Author keywords

Crop proportion estimation; Increased separability between classes; Landsat imagery; Mixed pixels

Indexed keywords

CROP PROPORTION ESTIMATION.; INCREASED SEPARABILITY BETWEEN CLASSES; LANDSAT IMAGERY; MIXED PIXELS;

COMPUTER PROGRAMMING - ALGORITHMS; FARMS - CROPS; IMAGE PROCESSING;

CASCADE; LANDSAT; MIXED PIXELS; MSS;

REMOTE SENSING;

EID: 0021644143     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(84)90050-5     Document Type: Article

References (16)

1. Detection and evaluation of mixed pixels in Landsat agricultural scenes
2. Field size length and width distributions based on LACIE ground data
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4. Automated pixel screening and selection technique
5. Spatial color sequence proportion estimation technique
6. Relating Landsat digital count values to ground reflectance for optically thin atmospheric conditions
7. Satellite remote sensing: an integral tool in acquiring global crop production information
8. System for analysis of Landsat agricultural data
9. Use of Landsat-derived temporal profiles for corn-soybean feature extraction and classification
10. CLASSY —an adaptive maximum likelihood clustering algorithm
11. Can crop types be resolved using mixture distribution components —some initial results and implications
12. Evaluation of small area crop estimation techniques using Landsat and ground-derived data