Optimal Red Edge Band Selection for Crop and Vegetation Classification using Separability and Spectral Analysis

Authors: Jitendra, Pant, Triloki

Source: 2024 IEEE 5th India Council International Subsections Conference (INDISCON) India Council International Subsections Conference (INDISCON), 2024 IEEE 5th. :1-4 Aug, 2024

Relation: 2024 IEEE 5th India Council International Subsections Conference (INDISCON)

Analysis of the Effectiveness of the Red-Edge Bands of GF-6 Imagery in Forest Health Discrimination

Authors: Chen, J., Xu, H.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 17:5621-5636 2024

Rice Fields Mapping Using Multi-Temporal GF-6 Remote Sensing Images

Authors: Wang, Jing, Qiu, Lin, Wang, Zhiming, Tian, Miao

Source: 2022 10th International Conference on Agro-geoinformatics (Agro-Geoinformatics) Agro-geoinformatics (Agro-Geoinformatics), 2022 10th International Conference on. :1-5 Jul, 2022

Relation: 2022 10th International Conference on Agro-geoinformatics (Agro-Geoinformatics)

Computer Recognition of Species Using Intelligent UAV Multispectral Imagery

Authors: Xia, Guofei, Zheng, Yaohua, Hu, Yuxuan, Luo, Jianbin, Xu, Qibin

Source: 2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT) Emergency Science and Information Technology (ICESIT), 2021 IEEE International Conference on. :803-806 Nov, 2021

Relation: 2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT)

The addition of GF-6 red edge bands optimizes the mapping of karst rocky desertification grades

Authors: Han, Zhenying ^{b, c}, Huang, Yu ^{a, d}, Jia, Guanyu ^e, Jing, Lei ^b, Huang, Shengxuan ^{b, c}, Li, Can ^{b, c}, Lei, Weiqun ^{a, d}, Hu, Wenmin ^{a, b, c, d, ⁎}

Source: In Advances in Space Research 15 April 2025 75(8):6222-6236

Potential of Red Edge Spectral Bands in Future Landsat Satellites on Agroecosystem Canopy Chlorophyll Content Retrieval

Authors: Cui, Zhaoyu, Kerekes, John

Source: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2019 - 2019 IEEE International. :7168-7171 Jul, 2019

Relation: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium

Development of soil water content retrieving method for irrigation agriculture areas using the red-edge band of Gaofen-6 satellite

Authors: Rong Wang, Hongli Zhao, Chi Zhang, Zhen Hao, Aiqi Chen, Ran Xu, Junyan He

Source: Agricultural Water Management, Vol 303, Iss , Pp 109045- (2024)

Subject Terms: Red-Edge Band, Gaofen-6 Satellite, Spectral Space, Soil Water Index, Soil Water Content, Sentinel-2, Agriculture (General), S1-972, Agricultural industries, HD9000-9495

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0378377424003809; https://doaj.org/toc/1873-2283

Access URL: https://doaj.org/article/c4ea3c4d43584fe3a531e53248e36cfe

Estimating the Urban Fractional Vegetation Cover Using an Object-Based Mixture Analysis Method and Sentinel-2 MSI Imagery

Authors: Cai, Y., Zhang, M., Lin, H.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 13:341-350 2020

Machine Learning in Sensors and Imaging

Contributors: Nam, Hyoungsik

Subject Terms: star image, image denoising, reinforcement learning, maximum likelihood estimation, mixed Poisson–Gaussian likelihood, machine learning-based classification, non-uniform foundation, stochastic analysis, vehicle–pavement–foundation interaction, forest growing stem volume, coniferous plantations, variable selection, texture feature, random forest, red-edge band, on-shelf availability, semi-supervised learning, deep learning, image classification, machine learning, explainable artificial intelligence, wildfire, risk assessment, Naïve bayes, transmission-line corridors, image encryption, compressive sensing, plaintext related, chaotic system, convolutional neural network, color prior model, object detection, piston error detection, segmented telescope, BP artificial neural network, modulation transfer function, computer vision, intelligent vehicles, extrinsic camera calibration, structure from motion, convex optimization, temperature estimation, BLDC, electric machine protection, touchscreen, capacitive, display, SNR, stylus, laser cutting, quality monitoring, artificial neural network, burr formation, cut interruption, fiber laser, semi-supervised, fuzzy, noisy, real-world, plankton, marine, activity recognition, wearable sensors, imbalanced activities, sampling methods, path planning, Q-learning, neural network, YOLO algorithm, robot arm, target reaching, obstacle avoidance, Technology: general issues, History of engineering and technology

File Description: image/jpeg

Access URL: https://directory.doabooks.org/handle/20.500.12854/80994
https://mdpi.com/books/pdfview/book/5335

Analysis of RapidEye imagery for agricultural land cover and land use mapping

Authors: Huiyong Sang, Jixian Zhang, Liang Zhai, Chengji Qiu, Xiaoxia Sun

Source: 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA) Earth Observation and Remote Sensing Applications (EORSA), 2014 3rd International Workshop on. :366-369 Jun, 2014

Relation: 2014 3rd International Workshop on Earth Observation and Remote Sensing Applications (EORSA)

Application of red edge band in remote sensing extraction of surface water body: a case study based on GF-6 WFV data in arid area

Authors: Zhao Lu, Daqing Wang, Zhengdong Deng, Yue Shi, Zhibin Ding, Hao Ning, Hongfei Zhao, Jiazheng Zhao, Haoli Xu, Xiaoning Zhao

Source: Hydrology Research, Vol 52, Iss 6, Pp 1526-1541 (2021)

Subject Terms: decision tree, gf-6 wfv data, red edge band, surface water body extraction, River, lake, and water-supply engineering (General), TC401-506, Physical geography, GB3-5030

File Description: electronic resource

Relation: http://hr.iwaponline.com/content/52/6/1526; https://doaj.org/toc/1998-9563; https://doaj.org/toc/2224-7955

Access URL: https://doaj.org/article/53b2832bf5ad4d04a3b0ee9f5a250dcf

Assessment of Carbon Sequestration Capacity of E. ulmoides in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6

Authors: Juan Wang, Xinxin Wei, Shuying Sun, Minhui Li, Tingting Shi, Xiaobo Zhang

Source: Sensors, Vol 23, Iss 18, p 7895 (2023)

Subject Terms: E. ulmoides, GF-6 WFV, red-edge band, random forest, net primary productivity, ecological suitability, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/23/18/7895; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/1f8f78a0b012469e9e1d77e41fd0eb78

Remote sensing retrieval of winter wheat leaf area index and canopy chlorophyll density at different growth stages

Authors: Naichen Xing, Wenjiang Huang, Huichun Ye, Yingying Dong, Weiping Kong, Yu Ren, Qiaoyun Xie

Source: Big Earth Data, Vol 0, Iss 0, Pp 1-23 (2021)

Subject Terms: growth stages, hyperspectral, red-edge band, sentinel-2, vegetation index, Geography. Anthropology. Recreation, Geology, QE1-996.5

File Description: electronic resource

Relation: https://doaj.org/toc/2096-4471; https://doaj.org/toc/2574-5417

Access URL: https://doaj.org/article/de19264ecd4e4289a62181af0640421f

Extraction of fractional vegetation cover in arid desert area based on Chinese GF-6 satellite

Authors: Deng Zhengdong, Lu Zhao, Wang Guangyuan, Wang Daqing, Ding Zhibin, Zhao Hongfei, Xu Haoli, Shi Yue, Cheng Zijian, Zhao Xiaoning

Source: Open Geosciences, Vol 13, Iss 1, Pp 416-430 (2021)

Subject Terms: vegetation index, pixel dichotomy model, fractional vegetation cover, red edge band, Geology, QE1-996.5

File Description: electronic resource

Relation: https://doaj.org/toc/2391-5447

Access URL: https://doaj.org/article/39bc0a26fdc7494581fc5501477c3b73

Effect of the Red-Edge Band from Drone Altum Multispectral Camera in Mapping the Canopy Cover of Winter Wheat, Chickweed, and Hairy Buttercup

Authors: Clement E. Akumu, Sam Dennis

Source: Drones, Vol 7, Iss 4, p 277 (2023)

Subject Terms: drone, Altum multispectral camera, red-edge band, mapping, winter wheat, chickweed, Motor vehicles. Aeronautics. Astronautics, TL1-4050

File Description: electronic resource

Relation: https://www.mdpi.com/2504-446X/7/4/277; https://doaj.org/toc/2504-446X

Access URL: https://doaj.org/article/5825123efde941ecae7632bc42d7523b

Estimating mangrove leaf area index based on red-edge vegetation indices: A comparison among UAV, WorldView-2 and Sentinel-2 imagery

Authors: Xianxian Guo, Mao Wang, Mingming Jia, Wenqing Wang

Source: International Journal of Applied Earth Observations and Geoinformation, Vol 103, Iss , Pp 102493- (2021)

Subject Terms: Mangrove, Leaf area index, Red-edge band, Vegetation index, Unmanned Aerial Vehicle, WorldView-2, Physical geography, GB3-5030, Environmental sciences, GE1-350

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S0303243421002002; https://doaj.org/toc/1569-8432

Access URL: https://doaj.org/article/95dc37d3fa2a4eb19c9993d7c267daa2

Leaf chlorophyll content retrieval of wheat by simulated RapidEye, Sentinel-2 and EnMAP data

Authors: Bei CUI, Qian-jun ZHAO, Wen-jiang HUANG, Xiao-yu SONG, Hui-chun YE, Xian-feng ZHOU

Source: Journal of Integrative Agriculture, Vol 18, Iss 6, Pp 1230-1245 (2019)

Subject Terms: leaf chlorophyll content, RapidEye, Sentinel-2, EnMAP, red-edge band, Agriculture (General), S1-972

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2095311918620933; https://doaj.org/toc/2095-3119

Access URL: https://doaj.org/article/3128da59746c469ea20fdde7b19654d0

Remote Sensing Monitoring of Rice Fields: Towards Assessing Water Saving Irrigation Management Practices

Authors: Isabel Pedroso de Lima, Romeu Gerardo Jorge, João L. M. P de Lima

Source: Frontiers in Remote Sensing, Vol 2 (2021)

Subject Terms: UAS (unmanned aerial system), vegetation indices, Red edge band, precision agriculture, rice irrigation, satellite images, Geophysics. Cosmic physics, QC801-809, Meteorology. Climatology, QC851-999

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/frsen.2021.762093/full; https://doaj.org/toc/2673-6187

Access URL: https://doaj.org/article/16d708d6bef9459c8f873033933f964d

Improved Surface Soil Moisture Estimation Model in Semi-Arid Regions Using the Vegetation Red-Edge Band Sensitive to Plant Growth

Authors: Rencai Lin, He Chen, Zheng Wei, Yinong Li, Baozhong Zhang, Haoran Sun, Minghan Cheng

Source: Atmosphere, Vol 13, Iss 6, p 930 (2022)

Subject Terms: Sentinel-1, Sentinel-2, surface soil moisture, water cloud model, red-edge band, vegetation water content, Meteorology. Climatology, QC851-999

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Relation: https://www.mdpi.com/2073-4433/13/6/930; https://doaj.org/toc/2073-4433

Access URL: https://doaj.org/article/4f30b4f876ef4d9994c821f26adc0546

Mapping Mangrove Density from Rapideye Data in Central America

Authors: Son Nguyen-Thanh, Chen Chi-Farn, Chen Cheng-Ru

Source: Open Geosciences, Vol 9, Iss 1, Pp 211-220 (2017)

Subject Terms: rapdideye, red-edge band, mangrove forests, svm, central america, Geology, QE1-996.5

File Description: electronic resource

Relation: https://doaj.org/toc/2391-5447

Access URL: https://doaj.org/article/777d52b698964e2eaead43f24731eef4