Based on remote sensing processing technology estimating leaves stomatal density of Populus euphratica

Stomata density is an important parameter that is used to analyze the environmental stress to plants, especially water stress [1-3]. The objective of this paper is to estimate leaves stomata density of Populus euphratica using remote sensing image processing technology, i.e., object-oriented classification, and to analyze ecological significance about stomata density change. The 18 samples were selected in the study area (the lower reaches of Heihe River). Leaves stomata images were obtained by a microscope (Leica DM6000 B). First stomata images were classified based on object-oriented classification method. And then, the classified images are imported into ArcGIS for calculating stomata pixel value and cells of standard stomata, which are used to calculate the number of stomata on one image. Stomata density can be obtained by dividing the stomata number with the image area. Finally, a batch program was made using R language code to deal with a lot of images. The results show that: the method in the study has high efficiency and accuracy to obtain leaves stomata density. There are variation of stomata density in 18 samples, ranging from 76.7 stoma·mm^-2 to 139.4 stoma·mm^-2, average value 105 stoma·mm^-2. With the increase of water stress, the stomata density expresses fluctuant change, from decrease to increase to decrease.