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Cited by in F6Publishing
For: Zhao F, Sun R, Zhong L, Meng R, Huang C, Zeng X, Wang M, Li Y, Wang Z. Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning. Remote Sensing of Environment 2022;269:112822. [DOI: 10.1016/j.rse.2021.112822] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
Number Citing Articles
1 Wang Z, Liu D, Liao X, Pu W, Wang Z, Zhang Q. SiamHRnet-OCR: A Novel Deforestation Detection Model with High-Resolution Imagery and Deep Learning. Remote Sensing 2023;15:463. [DOI: 10.3390/rs15020463] [Reference Citation Analysis]
2 Qian C, Yao C, Ma H, Xu J, Wang J. Tree Species Classification Using Airborne LiDAR Data Based on Individual Tree Segmentation and Shape Fitting. Remote Sensing 2023;15:406. [DOI: 10.3390/rs15020406] [Reference Citation Analysis]
3 Dascălu A, Catalão J, Navarro A. Detecting Deforestation Using Logistic Analysis and Sentinel-1 Multitemporal Backscatter Data. Remote Sensing 2023;15:290. [DOI: 10.3390/rs15020290] [Reference Citation Analysis]
4 Masolele RN, De Sy V, Marcos D, Verbesselt J, Gieseke F, Mulatu KA, Moges Y, Sebrala H, Martius C, Herold M. Using high-resolution imagery and deep learning to classify land-use following deforestation: a case study in Ethiopia. GIScience & Remote Sensing 2022;59:1446-72. [DOI: 10.1080/15481603.2022.2115619] [Reference Citation Analysis]
5 Zhang Y, Lu D, Jiang X, Li Y, Li D. Forest Structure Simulation of Eucalyptus Plantation Using Remote-Sensing-Based Forest Age Data and 3-PG Model. Remote Sensing 2022;15:183. [DOI: 10.3390/rs15010183] [Reference Citation Analysis]
6 Liu W, Lin Z, Gao G, Niu C, Lu W. Unsupervised SAR Image Change Type Recognition Using Regionally Restricted PCA-Kmean and Lightweight MobileNet. Remote Sensing 2022;14:6362. [DOI: 10.3390/rs14246362] [Reference Citation Analysis]
7 Fei J, Liu J, Ke L, Wang W, Wu P, Zhou Y. A deep learning-based method for mapping alpine intermittent rivers and ephemeral streams of the Tibetan Plateau from Sentinel-1 time series and DEMs. Remote Sensing of Environment 2022;282:113271. [DOI: 10.1016/j.rse.2022.113271] [Reference Citation Analysis]
8 Pulighe G. Perspectives and Advancements on “Land Use and Land Cover Mapping in a Changing World”. Land 2022;11:2108. [DOI: 10.3390/land11122108] [Reference Citation Analysis]
9 Jiang J, Xing Y, Wei W, Yan E, Xiang J, Mo D. DSNUNet: An Improved Forest Change Detection Network by Combining Sentinel-1 and Sentinel-2 Images. Remote Sensing 2022;14:5046. [DOI: 10.3390/rs14195046] [Reference Citation Analysis]
10 Hu Y, Wang Z, Zhang Y, Dian Y. Logging Pattern Detection by Multispectral Remote Sensing Imagery in North Subtropical Plantation Forests. Remote Sensing 2022;14:4987. [DOI: 10.3390/rs14194987] [Reference Citation Analysis]
11 Carstairs H, Mitchard ETA, Mcnicol I, Aquino C, Chezeaux E, Ebanega MO, Dikongo AM, Disney M. Sentinel-1 Shadows Used to Quantify Canopy Loss from Selective Logging in Gabon. Remote Sensing 2022;14:4233. [DOI: 10.3390/rs14174233] [Reference Citation Analysis]
12 Yang L, Driscol J, Sarigai S, Wu Q, Chen H, Lippitt CD. Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review. Remote Sensing 2022;14:3253. [DOI: 10.3390/rs14143253] [Cited by in Crossref: 9] [Cited by in F6Publishing: 4] [Article Influence: 9.0] [Reference Citation Analysis]
13 Seydi ST, Hasanlou M, Chanussot J. Burnt-Net: Wildfire burned area mapping with single post-fire Sentinel-2 data and deep learning morphological neural network. Ecological Indicators 2022;140:108999. [DOI: 10.1016/j.ecolind.2022.108999] [Reference Citation Analysis]
14 Zhao L, Tang C, Leung MF. Research on the Change in Public Art Landscape Pattern Based on Deep Learning. Mathematical Problems in Engineering 2022;2022:1-10. [DOI: 10.1155/2022/8745174] [Reference Citation Analysis]
15 Meng R, Gao R, Zhao F, Huang C, Sun R, Lv Z, Huang Z. Landsat-based monitoring of southern pine beetle infestation severity and severity change in a temperate mixed forest. Remote Sensing of Environment 2022;269:112847. [DOI: 10.1016/j.rse.2021.112847] [Cited by in Crossref: 3] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
16 Yang Q, Wang L, Huang J, Lu L, Li Y, Du Y, Ling F. Mapping Plant Diversity Based on Combined SENTINEL-1/2 Data—Opportunities for Subtropical Mountainous Forests. Remote Sensing 2022;14:492. [DOI: 10.3390/rs14030492] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]