Mojtaba Eidi; Ataollah Ebrahimi; Esmaiel Asadi; Hormoz Sohrabi; Hamzehali Shirmardi
Volume 21, Issue 3 , December 2014, , Pages 455-465
Abstract
In this study, the distance methods of density measurementwere compared for four plant species in terms of accuracy, time, and efficiency of the random distribution patterns in Karsanak area, located in the eastern part of Shahrekord in Chaharmahal-va-Bakhtiary province. The study area with 32000m2(160*200) ...
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In this study, the distance methods of density measurementwere compared for four plant species in terms of accuracy, time, and efficiency of the random distribution patterns in Karsanak area, located in the eastern part of Shahrekord in Chaharmahal-va-Bakhtiary province. The study area with 32000m2(160*200) was divided into eight sections of 4000 m2. The total number of each species was counted in each section and considered as the basis for the simulation. Then, eight sections with 4000m2 area were simulated in Stochastic Geometry software, and in each section, a transect of 100m length was established in the center of small side along which 10 points were determined by random systematic method with nine-meter intervals. The distance methods compared included nearest neighbor, closest individual, third closest individual, random pairs, point center quarter, angle order, wandering quarter and variable area transect as well as control group (counting the number of each species in each section). The selected species included Astragalus effuses, Eryngium billardieri, Astragalus rhodosemius and Astragalusverus. The distribution pattern of plant communities was determined by Hopkines and Eberhardt indices. The density estimation error was calculated to evaluate the accuracy. Duncan's test was used to compare the accuracy of methods, and standard deviation and time method were used to compare the efficiency of methods. The results of this study showed that nearest neighbor and closest individual methods (in terms of time), random pairs method (in terms of accuracy) and variable area transect (in terms of precision) could be introduced as the most efficient methods.
Mehdi Jafari; Gholam Reza Zehtabian; Amir Houshang Ehsani
Volume 20, Issue 1 , June 2013, , Pages 72-87
Abstract
Today, remote sensing data can provide the latest information for the study of land cover and land uses These images are of utmost importance due to the providing updated information, variety of forms and the possibility of processing for making land use maps. Determining the location of each land use ...
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Today, remote sensing data can provide the latest information for the study of land cover and land uses These images are of utmost importance due to the providing updated information, variety of forms and the possibility of processing for making land use maps. Determining the location of each land use together with land cover helps managers in making decisions. Also, the current status of the land cover can be studied by using land use maps at different levels. In order to evaluate the ability of multitemporal satellite data of TM and ETM + in land use classification and the effect of the thermal band on increasing the accuracy of the land use maps, Landsat TM digital data relating to the September 27, 1990 and Landsat ETM + digital data of 10 July 2002 from Kashan were analyzed. Initial studies were performed on images in terms of the presence of geometric errors. In order to prepare the images for digital processing, improved operation and image enhancement were applied on the images. Ground truth map was prepared in the same stage. Then, the supervised classification of satellite images with algorithms and different approaches including a variety of bands were tested and the accuracy of each of the methods and approaches were investigated. The results showed that the highest Kappa accuracy in both Landsat TM and ETM + with all the bands were 86.34 and 83.21, respectively. While the elimination of the thermal band decreases the accuracy to 82.46 and 79.93 % The results of this study showed that using thermal bonding caused an increase of 4 percent in Kappa accuracy, and the highest accuracy was occurred in the classes of clay plains, flood plains, mountains and puffy salt lands. Therefore, despite the lower spectral resolution, the use of thermal bonding is recommended in such studies.