应用数字遥感图像对泰国Chanthaburi省土地利用动态的监测

A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand.RS(Remote Sensing),GIS(Geographical Information System),GPS (Global Positioning System) and ancillary data were combined bythe method which adopts the main idea of classifying images by stekps from decision tree method and the hybridized supervised and unsupervised classification.An integration of automatic image interpretation,ancillary materials and expert knowledge was realized.Two subscenes of Landsat 5 Thematic Mapper(TM) images of bands 3,4 and 5 obtained on December 15,1992,and January 17,1999,were used for image gprocessing and spatial data analysis in the study.the overall accuracy of the results of classification reached 90%,which was verified by field check.Results showed that shrimp farm land,urban and traffic land,barren land,bush and agricultural developing area increased in area,mangrove,paddy field,swamp and marsh land,orchard and plantation,and tropical grass land decreased,and the forest land kept almost stable.Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.

Monitoring land use dynamics in Chanthaburi Province of Thailand using digital remotely sensed images

A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.