Aboutalebi, M., Torres-Rua, A., Kustas, W., Nieto, H., Coopmans, C., McKee, M., 2018. Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration. Irrigation Science 37(3), 407–429. https://DOI: 10.1007/s00271-018-0613-9.
Arai, R., Kodaira, S., Takahashi, T., Miura, S., Kaneda, Y., 2018. Seismic evidence for arc segmentation, active magmatic intrusions and syn-rift fault system in the northern Ryukyu volcanic arc. Earth, Planets and Space 70(1). https://doi.org/10.1186/s40623-018-0830-8
Athanassas, C.D., Vaiopoulos, A., Kolokoussis, P., Argialas, D., 2018. Remote Sensing of Mars: Detection of Impact Craters on the Mars Global Surveyor DTM by Integrating Edge- and Region-Based Algorithms. Earth, Moon, and Planets 121(1-2), 59–72. https:// DOI: 10.1007/s11038-018-9515-3
Bayram, B., Demir, N., Akpinar, B., Oy, S., Erdem. F., Vögtle, T., Seker, D., 2018. Effect of Different Segmentation Methods Using Optical Satellite Imagery to Estimate Fuzzy Clustering Parameters for SENTINEL-1A SAR Images, International archives of the photogrammetry, remote sensing and spatial information sciences 42(1), 39-43. https:// DOI: 10.5194/isprs-archives-42-1-39-2018
Benincasa, M., Falcini, F., Adduce, C., Sannino, G., Santoleri, R., 2019. Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis. Remote Sensing 11(22), 2636. https://doi.org/10.3390/rs11222636
Cao, J., Chen, L., Wang, M., Tian, Y., 2018. Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform. Computational Intelligence and Neuroscience 2018, 1–12. https://doi.org/10.1155/2018/3598284
Capolongo, D., Refice, A., Bocchiola, D., D’Addabbo, A., Vouvalidis, K., Soncini, A., Stamatopoulos, L., 2019. Coupling multitemporal remote sensing with geomorphology and hydrological modeling for post flood recovery in the Strymonas dammed river basin (Greece). Science of the Total Environment 651, 1958–1968. https:// DOI: 10.1016/j.scitotenv.2018.10.114
Carleer, A., Debeir, O., Wolff, E., 2005. Assessment of very high spatial resolution satellite image segmentations, Photogrammetric Engineering and Remote Sensing 71, 1285-1294. https://doi: 10.14358/PERS.71.11.1285
Chen, G., Jiang, Z., Kamruzzaman, M., 2020. Radar remote sensing image retrieval algorithm based on improved Sobel operator. Journal of Visual Communication and Image Representation 71, 102720. https://doi:10.1088/1742-6596/1933/1/012037
Chen, Y., Li, Y., Zhang, H., Tong, L., Cao, Y., Xue, Z., 2016. Automatic power line extraction from high resolution remote sensing imagery based on an improved Radon transform. Pattern Recognition 49, 174–186. https://doi.org/10.1016/j.patcog.2015.07.004
Du, S., Du, S., Liu, B., Zhang, X., Zheng, Z., 2020. Large-scale urban functional zone mapping by integrating remote sensing images and open social data. GIScience and Remote Sensing 57(3), 411–430. https://doi.org/10.1080/15481603.2020.1724707
Epuh, E., Okolie, C., Daramola, O., Ogunlade, F., Oyatayo, F., Akinnusi, S., Emmanuel, E., 2020. An integrated lineament extraction from satellite imagery and gravity anomaly maps for groundwater exploration in the Gongola Basin. Remote Sensing Applications: Society and Environment 20, 100346. https://doi.org/10.1016/j.rsase.2020.100346
Fan, J., Wang, J., 2018. A Two-Phase Fuzzy Clustering Algorithm Based on Neurodynamic Optimization with Its Application for PolSAR Image Segmentation. IEEE Transactions on Fuzzy Systems 26(1), 72–83. https:// DOI: 10.1109/TFUZZ.2016.2637373
Feng, G., Ni, M., Ou, S., Yan, W., Xu, J., 2019. A preferential interval-valued fuzzy c-means algorithm for remotely sensed imagery classification. International Journal of Fuzzy Systems 21(7), 2212-2222. https:// DOI:10.1109/SPAC46244.2018.8965521
Fourie, C., 2015. On Attribute Thresholding and Data Mapping Functions in a Supervised Connected Component Segmentation Framework, Remote Sensing 7(6), 7350-7377. https://doi.org/10.3390/rs70607350
Hong, H., Nam, J., 2017. Automatic detection of contact lines in slot coating flows. AIChE Journal 63(6), 2440–2450. https://doi.org/10.1002/aic.14752
Iqbal, M., Riaz, M., Ali, S., Ghafoor, A., Ahmad, A., 2020. Underwater Image Enhancement Using Laplace Decomposition. IEEE Geoscience and Remote Sensing Letters (19), 1–5. https:// DOI: 10.1109/IDAP.2018.8620727
Iwahashi, J., Kamiya, I., Matsuoka, M., Yamazaki, D., 2018. Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification. Progress in Earth and Planetary Science 5(1), 114–126. https://doi.org/10.1186/s40645-017-0157-2
Jurado, J., Cárdenas, J., Ogayar, C., Ortega, L., Feito, F., 2020. Semantic Segmentation of Natural Materials on a Point Cloud Using Spatial and Multispectral Features. Sensors 20(8), 2244. https://doi.org/10.3390/s20082244
Landmark, K., Schistad Solberg, A., Albregtsen, F., Austeng, A., Hansen, R., 2015. A Radon-Transform-Based Image Noise Filter With Applications to Multibeam Bathymetry. IEEE Transactions on Geoscience and Remote Sensing 53(11), 6252–6273. https://dx.doi.org/10.1109/TGRS.2015.2436380
Laws, K., 1980. Rapid texture identification, in 24th annual technical symposium, pp. 376-381. https:// doi: 10.1117/12.959169
Liu, W., Zhang, Z., Chen, X., Li, S., Zhou, Y., 2017. Dictionary Learning-Based Hough Transform for Road Detection in Multispectral Image. IEEE Geoscience and Remote Sensing Letters 14(12), 2330–2334. https:// DOI:10.1109/LGRS.2017.2764042
Mahmoudi, F., Samadzadegan, F., Reinartz, P., 2015. Object recognition based on the context aware decision-level fusion in multi views imagery, Selected Topics in Applied Earth Observations and Remote Sensing, 8(1), 12-22. https:// DOI: 10.1109/JSTARS.2014.362103
Makowski, C., Finkl, C., Vollmer, H., 2017. Geoform and Landform Classification of Continental Shelves using Geospatially Integrated IKONOS Satellite Imagery. Journal of Coastal Research 331, 1–22. https:// DOI: 10.2112/JCOASTRES-D-16A-00003.1
Masoud, A., Koike, K., 2017. Applicability of computer-aided comprehensive tool and shaded digital elevation model for characterizing and interpreting morphotectonic features from lineaments. Computers and Geosciences 106, 89–100. https://doi.org/10.1016/j.cageo.2017.06.006
Miao, Z., Shi, W., Samat, A., Lisini, G., Gamba, P., 2016. Information Fusion for Urban Road Extraction from VHR Optical Satellite Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9(5), 1817–1829. https:// doi: 10.1109/JSTARS.2015.2498663.
Ming, D., Ci, T., Cai, H., Li, L., Qiao, C., Du, J., 2012. Semivariogram-based spatial bandwidth selection for remote sensing image segmentation with mean-shift algorithm, Geoscience and Remote Sensing Letters 9(1), 813-817. https:// DOI: 10.1109/LGRS.2011.2182604
Nakao, D., Masumoto, S., Nemoto, T., 2019. Development of Lineament Extraction Method based on Topography Characteristics and Segment Tracing Algorithm (STA) using Digital Elevation Model. Geoinformatics 30(3), 87–100. https:// DOI:10.6010/geoinformatics.30.3_87
Nemer Pelliza, K., Pucheta, M., Flesia, A., 2020. Optimal Canny’s Parameters Regressions for Coastal Line Detection in Satellite-Based SAR Images. IEEE Geoscience and Remote Sensing Letters 17(1), 82–86. http://dx.doi.org/10.1109/LGRS.2019.2916225
Ni, C., Zhang, S., Liu, C., Yan, Y., Li, Y., 2016. Lineament Length and Density Analyses Based on the Segment Tracing Algorithm: A Case Study of the Gaosong Field in Gejiu Tin Mine, China. Mathematical Problems in Engineering 2016, 1–7. https://doi.org/10.1155/2016/5392453
Pires, A., Chaminé, H., Piqueiro, F., Pérez-Alberti, A., Rocha, F., 2016. Combining coastal geoscience mapping and photogrammetric surveying in maritime environments (Northwestern Iberian Peninsula): focus on methodology. Environmental Earth Sciences 75(3), 104–116. https:// DOI: 10.1007/s12665-015-4936-z
Richards, J., 2013. Correcting Registering Images, in Remote Sensing Digital Image Analysis, ed: Springer, pp. 27-77. https:// DOI 10.1007/978-3-642-30062-2
Rodríguez-Caballero, E., Afana, A., Chamizo, S., Solé-Benet, A., Canton, Y., 2016. A new adaptive method to filter terrestrial laser scanner point clouds using morphological filters and spectral information to conserve surface micro-topography. ISPRS Journal of Photogrammetry and Remote Sensing 117, 141–148. https://doi.org/10.1016/j.isprsjprs.2016.04.004
Silva, G., Carneiro, G., Doth, R., Amaral, L., de Azevedo, D., 2018. Near real‐time shadow detection and removal in aerial motion imagery application. ISPRS Journal of Photogrammetry and Remote Sensing 140, 104– 121. https://doi.org/10.1016/j.isprsjprs.2017.11.005
Swetnam, T., Gillan, J., Sankey, T., McClaran, M., Nichols, M., Heilman, P., McVay, J., 2018. Considerations for Achieving Cross-Platform Point Cloud Data Fusion across Different Dryland Ecosystem Structural States. Frontiers in Plant Science 8, 140-151. https://doi.org/10.3389/fpls.2017.02144
Tabib Mahmoudi, F., Samadzadegan, F., Reinartz, P., 2015. Object recognition based on the context aware decision-level fusion in multiviews imagery," Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of 8, pp. 12-22. https:// DOI: 10.1109/JSTARS.2014.2362103
Vizilter, Y., Rubis, A., Zheltov, S., Vygolov, O., 2016. Change detection via morphological comparative filters. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences 3(3), 279–286. https://doi.org/10.5194/isprs-annals-III-3-279-2016
Wang, C., Guo, P., Wang, H., Yang, F., 2019. Urban Trunk Roads Extraction Using Hough Transform and NDVI in Airborne Hyperspectral Remote Sensing Images. Journal of Physics: Conference Series 1237, 032030. https://doi.org/10.3390/rs9060590
Wang, T., Shi, J., Husi, L., Zhao, T., Ji, D., Xiong, C., Gao, B., 2017. Effect of solar‐cloud‐satellite geometry on land surface shortwave radiation derived from remotely sensed data. Remote Sensing 9(7), 690. https://doi.org/10.3390/rs9070690
Wang, T., Yan, G., Mu, X., Jiao, Z., Chen, L., Chu, Q., 2018. Toward operational shortwave radiation modeling and retrieval over rugged terrain. Remote Sensing of Environment 205, 419– 433. https:// DOI: 10.1109/TGRS.2020.2994384
Xu, J., Feng, G., Fan, B., Yan, W., Zhao, T., Sun, X., Zhu, M., 2020. Landcover classification of satellite images based on an adaptive interval fuzzy c-means algorithm coupled with spatial information. International Journal of Remote Sensing 41(6), 2189-2208. https://doi.org/10.1080/01431161.2019.1685718
Xu, J., Wen, X., Zhang, H., Luo, D., Li, J., Xu, L., Yu, M., 2020. Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade. Advances in Space Research 65(1), 506–517. https://DOI:10.1016/j.asr.2019.09.045
Xu, Y., Chen, R., Li, Y., Zhang, P., Yang, J., Zhao, X., Wu, D., 2019. Multispectral Image Segmentation Based on a Fuzzy Clustering Algorithm Combined with Tsallis Entropy and a Gaussian Mixture Model. Remote Sensing 11(23), 2772. https://doi.org/10.3390/rs11232772
Yang, S., Qiao, Y., Yang, L., Jin, P., Jiao, L., 2014. Hyperspectral Image Classification Based on Relaxed Clustering Assumption and Spatial Laplace Regularizer. IEEE Geoscience and Remote Sensing Letters 11(5), 901–905. https://doi.org/10.3390/rs14215530
Yu, H., Xu, L., Feng, D., He, X., 2015. Independent feature subspace iterative optimization based fuzzy clustering for synthetic aperture radar image segmentation. Journal of Applied Remote Sensing 9(1), 095060. https:// DOI: 10.1117/1.JRS.9.095060
Yu, X,, He, H., Hu, D., Zhou, W., 2014. Land cover classification of remote sensing imagery based on interval-valued data fuzzy c-means algorithm, Science China Earth Sciences 57, 1306-1313. https://doi.org/10.1007/s11430-013-4689-z
Zhang, Y., Jiang, P., Zhang, H., Cheng, P., 2018. Study on Urban Heat Island Intensity Level Identification Based on an Improved Restricted Boltzmann Machine. International Journal of Environmental Research and Public Health 15(2), 186. https://doi.org/10.3390/ijerph15020186
Zhao, F., Li, C., Liu, H., Fan, J., 2019. A multi-objective interval valued fuzzy clustering algorithm with spatial information for noisy image segmentation. Journal of Intelligent and Fuzzy Systems 36(6), 5333-5344. https:// DOI: 10.3233/JIFS-181191
Zheng, Z., Cao, J., Lv, Z., Benediktsson, J.A., 2019. Spatial–Spectral Feature Fusion Coupled with Multi-Scale Segmentation Voting Decision for Detecting Land Cover Change with VHR Remote Sensing Images. Remote Sensing 11(16), 2-22. https://doi.org/10.3390/rs11161903
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