For mapping multiple vegetation types at large scale, determining appropriate plot size and spatial resolution is very important. However, this can be difficult because of spectral mixtures, low correlation of remote sensing and field data, and high cost to collect field data at a high density. This paper presents a method to determine appropriate plot size and spatial resolution for mapping multiple vegetation types using remote sensing data for a large area. This method is based on field data and geo-statistics theory. The method accounts simultaneously for within-support and regional spatial variability by modeling both within-support and regional semi-variograms. The range parameters of the within-support semi-variograms implied the maximum range of the appropriate plot sizes. Using the regional semi-variograms, the support size was considered appropriate when the ratio of the nugget variance to sill variance stabilized. The method is assessed using field data and satellite TM data by developing the semivariograms by vegetation type and TM band; and by cross validation of vegetation classification. A possible improvement for remote sensing to aid mapping is suggested.
|Original language||English (US)|
|Number of pages||10|
|Journal||Photogrammetric Engineering and Remote Sensing|
|State||Published - 2001|
ASJC Scopus subject areas
- Computers in Earth Sciences