The current research on multiple information fusion of remote sensing images is mainly aimed at remote sensing images of specific satellite sensors, and cannot be extended to other types of data source images. For high-resolution remote sensing images, when its surface coverage changes significantly, most of the mainstream algorithms are difficult to restore satisfactorily. The algorithm proposed in this paper combines the sparse representation and the spectral, spatial, and temporal features of remote sensing images for the first time to solve the above problems. The algorithm proposed in this paper first simulates the human visual mechanism, and obtains the spatial, spectral, and temporal features of the remote sensing image through the spatial spectral dictionary learning and the time-varying weight learning model. Secondly, local constraints are added to the extraction of temporal features to obtain temporal and geographical change information of heterogeneous remote sensing images. Then, a sparse representation model combining space-spectrum-time features is proposed to extract features of high-resolution remote sensing images. Finally, based on the VGG-16 network, this paper proposes a target recognition network with deep fully convolutional network, and uses the extracted feature map as the input of the target recognition network to realize the target recognition of the remote sensing image. Experimental results show that the method proposed in this paper can improve the accuracy of target recognition and improve the accuracy of recognition.

Halophytes have been studied as a model for morphological traits of adaptation to saline environments. However, little information has been given on plant growth, chlorophyll fluorescence responses, and change of ion content in halophytes grown in an aniline–salinity coexistent environment. This study hypothesized that aniline could induce alterations in plant growth, chlorophyll fluorescence, and ion content in Suaeda salsa, but salinity could promote the tolerance of halophytes to aniline. A 6 (aniline) × 3 (NaCl) factorial experiment (for a total of 18 treatments) was conducted to test the above hypothesis. After 30 d of cultivation, roots and shoots were harvested separately to analyze the effects of salinity on the seedling growth under aniline stress. Biomass accumulation was inhibited by aniline treatment, and the inhibition was significantly alleviated by 200 mM NaCl. The change in chlorophyll fluorescence in leaves with aniline stress was moderated by the addition of NaCl. The removal efficiency of aniline was significantly enhanced by moderate salinity. Aniline stress decreased the accumulation of Mg²⁺, but various concentrations of NaCl increased the accumulation of Mg²⁺, especially with 200 mM NaCl in both roots and shoots. Both aniline and salinity decreased the content of Ca²⁺. There was a negative correlation between the K⁺ and NaCl concentrations and between the Cl⁻ and aniline concentrations. Our results indicated that Suaeda salsa may be suitable for the remediation of salinity and aniline-enriched wastewater.

Based on the concept of microbial community multi-processing in integrated spatial bacterial succession (ISBS), this study constructs a highly efficient cellular fixed-bed bioreactor that follows the growth of biological flora in the wastewater treatment process. The reactor is organically partitioned based on synergistic laws and in accordance with environmental and microbial metabolic changes, and sewage is subjected to unitized and specialized biological treatment under direct current conditions. The results show that the ISBS reactor exhibits stable nitrogen removal performance under a low-carbon source. Compared with traditional sewage biochemical treatment technology, the microbial concentration is increased by 2–3 times and even up to 12 times, and the ammonia nitrogen removal rate is maintained at 99%. The removal rate reaches 90% (hydraulic retention time of 14 h). High-throughput sequencing analysis based on 16S rDNA reveals the microbial community structure succession at different depths of the same section of the reactor. The microbial community is rich under the influence of environmental factors and exhibits different responses. The intervals vary. An analysis of the microbial community function explains why the ISBS reactor has high nitrogen removal efficiency.