Mj. Ortiz et al., CLASSIFICATION OF CROPLANDS THROUGH INTEGRATION OF REMOTE-SENSING, GIS, AND HISTORICAL DATABASE, International journal of remote sensing, 18(1), 1997, pp. 95-105
This work presents a methodology to classify croplands using a multite
mporal/historical dataset of images and ground ancillary data referrin
g to three consecutive years. An image processing/geographic informati
on system as well as a database management system (DBMS) were used to
make the integration of these multisource data. In order to evaluate t
he usefulness of a database for crop classification, the area under st
udy was digitally classified by two groups of interpreters, using two
methodologies: (a) the proposed methodology using maximum likelihood c
lassification assisted by an historical/multisource database, and (b)
a conventional maximum likelihood classification only. Both results we
re compared using the Kappa statistics. The indices to both the propos
ed and the conventional digital classification methodologies were 0.66
9 (very good) and 0.472 (good), respectively. The use of the database
rendered an improvement over the conventional digital classification.
Furthermore, along with this study some problems related to multisourc
e data integration are discussed.