FUZZY CLASSIFICATION OF JERS-1 SAR DATA - AN EVALUATION OF ITS PERFORMANCE FOR SOIL-SALINITY MAPPING

Remote sensing of surface features has been used intensively to identi fy and map salt-affected areas. Salt-tolerant vegetation is among the indicators used to separate saline-alkaline areas from non-affected on es. However, this type of vegetation causes spectral confusion and err oneous labelling between salinity and alkalinity classes when working with optical sensors such as Landstat TM or Spot. Accordingly, this pa per evaluates the capabilities of the microwave range to map saline an d alkaline areas. Fuzzy sets are used to model the information classes , and a fuzzy overlay model is implemented to classify the JERS-1 rada r satellite image. The study shows that fuzzy classification of JERS-1 SAR data provides reliable detection (overall accuracy equal to 81%) of areas degraded by salinity-alkalinity processes. The main problems appear to be due to the interaction between soil roughness and radar b ackscattering, which determined erroneous allocation of alkaline and s aline-alkaline areas to non-affected areas. (C) 1998 Elsevier Science B.V. All rights reserved.