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Recovery of plants after water stress events represents their high suitability for the urban condition areas. Reaction to drought and recovery of woody plants Cornus mas L., Lonicera caerulea L. and perennials Alchemilla mollis (Buser) Rothm., Geranium maculatum L., Geranium x magnificum Hyl. ‘Rosemoor’ and Geranium ‘Philippe Vapelle’ were evaluate. Within a pot experiment the non‑destructive methods of monitoring: measurement of chlorophyll content using chlorophyll meter CL‑01, leaf stomatal conductance using Delta T Leaf porometer AP4 and modulated chlorophyll fluorescence using Hansatech FMS 1 were chosen. Based upon our results we may demonstrate different protective mechanisms of plants in water stress conditions. An increase in the chlorophyll concentration in stress‑exposed tissues and recovery of stomatal conductance in Cornus mas L. and in Alchemilla mollis (Buser) Rothm. were observed. In Cornus mas L. and Lonicera caerulea L. the early recovery of parameter ɸPSII (after 2 days of re‑watering) and the delayed recovery (after 6 days of re‑watering) in Geranium plants and Alchemilla mollis (Buser) Rothm.) were shown.

The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling. When the number of sparse subbands changes, the number of nodes can be adjusted flexibly to improve the reconstruction rate. Owing to the different attenuations of distributed nodes in different locations, it is worthwhile to find out how to select the optimal sensing node as the sampling channel. This paper proposes the spectrum sensing of DMWC based on a Markov random field (MRF) to select the ideal node, which is compared to the image edge segmentation. The attenuation of the candidate nodes is estimated based on the attenuation of the neighboring nodes that have participated in the DMWC system. Theoretical analysis and numerical simulations show that neighboring attenuation plays an important role in determining the node selection, and selecting the node using MRF can avoid serious transmission attenuation. Furthermore, DMWC can greatly improve recovery performance by using a Markov random field compared with random selection.