Showing 3 results for Accuracy
F. Amiri, M. Bassiri, M. Iravani,
Volume 9, Issue 2 (7-2005)
Abstract
The vast and diverse rangelands of Iran require the selection of appropriate methods for grazing intensity measurement in the different vegetation types. Methods can be compared on the bases of time and budget as well as their accuracy. In this study nine methods of the utilization measurement were conducted on the E. ceratoides stands of Hanna exclosure Semirom, Isfahan province. The duncan multiple range test was used to compare mean utilization percentages obtained from the different methods, with paired cage method data was used as control group. Analytical Hierarchy Process (AHP) was also used to compare methods for accuracy, time and budget. The means from reference unite, twig length, production index, plant count and stem count methods had significant (p<0.05) differences compared with control group but were comparatively time consuming and more expensive than other methods. The height-weight method resulted in an estimate with no significant difference with the control group. This method was also fastest and least expensive among methods with the accurate results (p<0.05).
H. Latifi, J. Oladi, S. Saroei, H. Jalilvand,
Volume 11, Issue 40 (7-2007)
Abstract
In order to evaluate the capability of ETM+ remotely- sensed data to provide "Forest- shrub land- Rangeland" cover type map in areas near the timberline of northern forests of Iran, the data was analyzed in a portion of nearly 790 ha located in Neka- Zalemroud region. First, ortho-rectification process was implemented to correct the geometric errors of the image, which yielded 0/68 and 0/69 pixels of RMS error toward X and Y axis, respectively. The original
multi-spectral bands were fused to the panchromatic band using PANSHARP Statistical module. The ground truth map was prepared using 1 ha field plots in a systematic- random sampling grid. Vegetative form of trees, shrubs and rangelands was recorded as a criterion to allocate the plots. A set of channels including original bands, NDVI and IR/R indices, and first components of PCA was used for classification procedure. Automatic band selection command was used to select the appropriate channel set.. Classification was carried out using ML classifier on both original and fused data sets. It showed 67% of overall accuracy and 0/43 of Kappa coefficient in original data set. Due to the results present presented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of 3 form- based classes, in the studied area. Furthermore, applying complementary methods to minimize the background spectral effect is proposed for future studies.
A. Mohammadi Torkashvand, D. Nikkami,
Volume 11, Issue 42 (1-2008)
Abstract
Erosion features map is one of the basic maps in erosion and sediment studies considered important in watershed management programs. For preparing soil erosion features map (1:250000 scale), a study was conducted in Jajroud sub-basin of Tehran, Iran. Working unit maps were prepared from integrating: A) plant cover, geology and slope B) land-use, geology and slope C) land-use, rocks sensitivity to erosion and slope and D) land-use, rocks sensitivity to erosion and land units. Working unit maps obtained from integrating layers were compared with three other maps consisting of working units maps according to E) land units F) rocks sensitivity to erosion units and G) image photomorphic units. Erosion features intensities in 314 control points were controlled and erosion features ground truth map was prepared by Thiessen method and using satellite imagery. Erosion features map was crossed with different working unit maps. Results showed that D map was better than A, B and C maps with regard to economic considerations. Accuracy was 53.0 and 42.9% for methods of land unit and rock sensitivity which resulted in the maps not suitable for differentiating soil erosion features. Root Mean Squared Error of working units showed that the error of land unit and rock sensitivity methods was more than image interpretation and integrated layers methods. The highest coefficient of variation was related to land unit and rock sensitivity to erosion methods and was the least for image interpretation and integrated layers methods. The greatest precision, therefore, was related to image interpretation and integrated layers methods. In general, working unit map of image interpretation was the best method for preparing soil erosion features map.
