Ceballos, G., Ehrlich, P. R., & Dirzo, R. (2017). Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proceedings of the national academy of sciences, 114(30), E6089-E6096. ##
Ripple, W. J., Wolf, C., Newsome, T. M., Barnard, P., & Moomaw, W. R. (2020). World scientists’ warning of a climate emergency. BioScience, 70(1), 8-100. ##
Choe, E., van der Meer, F., van Ruitenbeek, F., van der Werff, H., de Smeth, B., & Kim, K. W. (2008). Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain. Remote Sensing of Environment, 112(7), 3222-3233. ##
Ingram, J.C., Dawson, T.P., Whittaker, R.J., 2005. Mapping tropical forest structure in southeastern Madagascar using remote sensing and artificial neural networks. Remote Sens. Environ. 94, 491– 507. ##
Watson, J.E., Joseph, L.N., Fuller, R.A., 2010. Mining and conservation: implications for Madagascar’s littoral forests. Conservation Letters 3, 286–287. ##
Rogan, J., Agrawal, S., Gamboa, C., et al,.2018 . Bebbington, A.J., Bebbington, D.H., Sauls, L.A.,Resource extraction and infrastructure threaten forest cover and community rights. Proc. National Academy Sci., 201812505. ##
Hodgson, D.A., Vyverman, W., Chepstow-Lusty, A., Tyler, P.A., 2000. From rainforest to wasteland in 100 years: the limnological legacy of the Queenstown mines, Western Tasmania. Archiv für Hydrobiologie 149, 153–176 ##
Kim, S.-M., Choi, Y., Suh, J., Oh, S., Park, H.-D., Yoon, S.-H., 2012a. Estimation of soil erosion and sediment yield from mine tailing dumps using GIS: a case study at the samgwang mine, Korea. Geosystem Eng. 15, 2–9. ##
Mazabanda, C., Kemper, R., Thieme, A., Hettler, B., Finer, M., 2018. Impacts of mining project (mirador) in the Ecuadorian amazon. 2018. Monitoring Andean Amazon Project (MAAP). ##
Werner, T. T., Bebbington, A., & Gregory, G. (2019). Assessing impacts of mining: Recent contributions from GIS and remote sensing. The Extractive Industries and Society, 6(3), 993-1012. ##
Agboola, O., Babatunde, D. E., Fayomi, O. S. I., Sadiku, E. R., Popoola, P., Moropeng, L., ... & Mamudu, O. A. (2020). A review on the impact of mining operation: Monitoring, assessment and management. Results in Engineering, 8, 100181. ##
Zhu, D., Chen, T., Zhen, N., & Niu, R. (2020). Monitoring the effects of open-pit mining on the eco-environment using a moving window-based remote sensing ecological index. Environmental Science and Pollution Research, 27, 15716-15728. ##
Gallwey, J., Robiati, C., Coggan, J., Vogt, D., & Eyre, M. (2020). A Sentinel-2 based multispectral convolutional neural network for detecting artisanal small-scale mining in Ghana: Applying deep learning to shallow mining. Remote Sensing of Environment, 248, 111970. ##
Qian, X., Li, C., Wang, W., Yao, X., & Cheng, G. (2023). Semantic segmentation guided pseudo label mining and instance re-detection for weakly supervised object detection in remote sensing images. International Journal of Applied Earth Observation and Geoinformation, 119, 103301. ##
Zhang, Z., He, G., Wang, M., Wang, Z., Long, T., & Peng, Y. (2015). Detecting decadal land cover changes in mining regions based on satellite remotely sensed imagery: A case study of the stone mining area in Luoyuan county, SE China. Photogrammetric Engineering & Remote Sensing, 81(9), 745-751. ##
Xiao, D., Yin, L., & Fu, Y. (2021). Open-pit mine road extraction from high-resolution remote
sensing images using RATT-UNet. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. ##
Shamsolmoali, P., Zareapoor, M., Wang, R., Zhou, H., & Yang, J. (2019). A novel deep structure UNet for sea-land segmentation in remote sensing images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(9), 3219-3232. ##
Qin, P., Cai, Y., & Wang, X. (2021). Small waterbody extraction with improved U-Net using Zhuhai-1 hyperspectral remote sensing images. IEEE Geoscience and Remote Sensing Letters, 19, 1-5. ##
Fan, X., Yan, C., Fan, J., & Wang, N. (2022). Improved U-net remote sensing classification algorithm fusing attention and multiscale features. Remote Sensing, 14(15), 3591. ##
Wang, C., Chang, L., Zhao, L., & Niu, R. (2020). Automatic identification and dynamic monitoring of open-pit mines based on improved mask RCNN and transfer learning. Remote Sensing, 12(21), 3474. ##
Chen, T., Hu, N., Niu, R., Zhen, N., & Plaza, A. (2020). Object-oriented open-pit mine mapping using Gaofen-2 satellite image and convolutional neural network, for the Yuzhou City, China. Remote Sensing, 12(23), 3895. ##
Maxwell, A. E., Bester, M. S., Guillen, L. A., Ramezan, C. A., Carpinello, D. J., Fan, Y., ... & Pyron, J. L. (2020). Semantic segmentation deep learning for extracting surface mine extents from historic topographic maps. Remote Sensing, 12(24), 4145. ##
Xu, D., Zhao, Y., Jiang, Y., Zhang, C., Sun, B., & He, X. (2021). Using improved edge detection method to detect mining-induced ground fissures identified by unmanned aerial vehicle remote sensing. Remote Sensing, 13(18), 3652. ##
Xie, H., Pan, Y., Luan, J., Yang, X., & Xi, Y. (2021). Open-pit mining area segmentation of remote sensing images based on DUSegNet. Journal of the Indian Society of Remote Sensing, 49, 1257-1270. ##
Xie, H., Pan, Y., Luan, J., Yang, X., & Xi, Y. (2021). Semantic segmentation of open pit mining area based on remote sensing shallow features and deep learning. In Big Data Analytics for CyberPhysical System in Smart City: BDCPS 2020, 28-29 December 2020, Shanghai, China (pp. 52-59). Springer Singapore. ##
Liang, C., Xiao, B., & Cheng, B. (2021, July). GCN-Based Semantic Segmentation Method for Mine Information Extraction in GAOFEN-1 Imagery. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 3432-3435). IEEE. ##
Wu, K. Y., Wang, X., Zhou, J. J., Wang, X. F., Fan, Y. P., & Yao, M. (2021, October). An improved D-LinkNet method for road extraction from high resolution remote sensing images. In 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP) (pp. 175-180). IEEE. ##
He, H., Xu, H., Zhang, Y., Gao, K., Li, H., Ma, L., & Li, J. (2022). Mask R-CNN based automated identification and extraction of oil well sites. International Journal of Applied Earth Observation and Geoinformation, 112, 102875. ##
Wu, M., Zhang, C., Liu, J., Zhou, L., & Li, X. (2019). Towards accurate high resolution satellite image semantic segmentation. Ieee Access, 7, 55609-55619. ##
Xing, Z., Zhao, S., Guo, W., Meng, F., Guo, X., Wang, S., & He, H. (2023). Coal resources under carbon peak: Segmentation of massive laser point clouds for coal mining in underground dusty environments using integrated graph deep learning model. Energy, 285, 128771. ##
Selva, M., Aiazzi, B., Butera, F., Chiarantini, L., & Baronti, S. (2015). Hyper-sharpening: A first approach on SIM-GA data. IEEE Journal of selected topics in applied earth observations and remote sensing, 8(6), 3008-3024. ##
Wang, Q., Shi, W., Li, Z., & Atkinson, P. M. (2016). Fusion of Sentinel-2 images. Remote sensing of environment, 187, 241-252. ##
Kaplan, G., & Avdan, U. (2018, March). Sentinel-2 pan sharpening—comparative analysis. In Proceedings (Vol. 2, No. 7, p. 345). MDPI. ##
Bouslihim, Y., Kharrou, M. H., Miftah, A., Attou, T., Bouchaou, L., & Chehbouni, A. (2022). Comparing pan-sharpened landsat-9 and sentinel-2 for land-use classification using machine learning classifiers. Journal of Geovisualization and Spatial Analysis, 6(2), 35. ##
Siok, K., Ewiak, I., & Jenerowicz, A. (2020).Multi-sensor fusion: A simulation approach to pansharpening aerial and satellite images. Sensors, 20(24), 7100. ##
Sun, Z., Xuan, P., Song, Z., Li, H., & Jia, R. (2022). A texture fused superpixel algorithm for coal mine waste rock image segmentation. International Journal of Coal Preparation and Utilization, 42(4), 1222-1233. ##
Saranathan, A. M., & Parente, M. (2015). Uniformity-based superpixel segmentation of hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 54(3), 1419- 1430. ##
Wu, X., Zhang, X., & Lin, H. (2018). Superpixel Based Factor Analysis and Target Transformation Method for Martian Minerals Detection. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 1901-1906. ##
Gay, R., Lecoutre, J., Menouret, N., Morillon, A., & Monasse, P. (2022). Bilateral K-Means for Superpixel Computation (the SLIC Method). Image Processing On Line, 12, 72-91. ##
Song, J., Cong, W., & Li, J. (2017). A Fuzzy Cmeans Clustering Algorithm for Image Segmentation Using Nonlinear Weighted Local Information. J. Inf. Hiding Multim. Signal Process., 8(3), 578-588. ##
Song, Q., Wu, C., Tian, X., Song, Y., & Guo, X. (2022). A novel self-learning weighted fuzzy local information clustering algorithm integrating local and non-local spatial information for noise image segmentation. Applied Intelligence, 1-22. ##