Suman Kunwar^1,*, Jannatul Ferdush²

Revue Internationale de Géomatique, Vol.33, pp. 1-13, 2024, DOI:10.32604/rig.2023.047627

Abstract As the global population continues to expand, the demand for natural resources increases. Unfortunately, human activities account for 23% of greenhouse gas emissions. On a positive note, remote sensing technologies have emerged as a valuable tool in managing our environment. These technologies allow us to monitor land use, plan urban areas, and drive advancements in areas such as agriculture, climate change mitigation, disaster recovery, and environmental monitoring. Recent advances in Artificial Intelligence (AI), computer vision, and earth observation data have enabled unprecedented accuracy in land use mapping. By using transfer learning and fine-tuning with red-green-blue (RGB) bands, we achieved an… More > Graphic Abstract

Shen Zhang¹, Yongqi Jian¹, Bingjing Yan², Jin Jin¹, Jiasen Wu¹, Chenfei Liang¹, Juan Liu^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.8, pp. 1745-1756, 2022, DOI:10.32604/phyton.2022.021076

Abstract The impact of land consolidation on the soil microbial PLFA diversity is of great importance for understanding the effective arable land usage, improving agricultural ecological conditions and environment. In this study, we collected the soil samples (0–20 cm) in experimental plots with 0 (Z₀), 1 (Z_1a) and 4 (Z_4a) years of land consolidation in the forest station of Ningbo City, Zhejiang Province, southeastern China. The results were analyzed using ANOVA for randomized block design. Compared with control (Z₀), the soil pH value under Z_1a treatment increased by 14.6%, soil organic carbon (SOC) content decreased by 65.4%, so did the PLFA… More >

Seung-Yeon Hwang¹, Jeong-Joon Kim^2,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2649-2663, 2022, DOI:10.32604/cmc.2022.022593

Abstract Artificial intelligence, which has recently emerged with the rapid development of information technology, is drawing attention as a tool for solving various problems demanded by society and industry. In particular, convolutional neural networks (CNNs), a type of deep learning technology, are highlighted in computer vision fields, such as image classification and recognition and object tracking. Training these CNN models requires a large amount of data, and a lack of data can lead to performance degradation problems due to overfitting. As CNN architecture development and optimization studies become active, ensemble techniques have emerged to perform image classification by combining features extracted… More >

Garay MM¹, NM Amiotti², P Zalba¹

Phyton-International Journal of Experimental Botany, Vol.84, No.2, pp. 280-287, 2015, DOI:10.32604/phyton.2015.84.280

Abstract Afforestation is a recommended practice to mitigate global warming. However, their implementation may generate undesirable impacts, mostly if exotic species are used. Plantations of Pinus radiata D Don in Ventania (Bs. As., Argentina) soils showed notorious increments of extractable P (Pe), which could affect the dynamic of this element as well as the degree of phosphorus saturation (GSP_Bray). The objectives of this study were: i) to quantify the GSP_Bray in Mollisols afforested with P. radiata comparing the results with those coming from adjacent, natural grassland areas (base line); ii) to evaluate the potential environmental risk induced by afforestation through the… More >