Works matching DE "AGRICULTURAL remote sensing"
Results: 316
Investigating the Effect of Spectral Bands and Vegetation Indices Selection on Agricultural Crop Classification (Especially for Double Cropping Regions).
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- Turkish Journal of Agricultural & Natural Sciences, 2025, v. 12, n. 1, p. 197, doi. 10.30910/turkjans.1586291
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AI Algorithms in the Agrifood Industry: Application Potential in the Spanish Agrifood Context.
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- Applied Sciences (2076-3417), 2025, v. 15, n. 4, p. 2096, doi. 10.3390/app15042096
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COMPORTAMENTO ESPECTRAL DA CANA-DE-AÇÚCAR UTILIZANDO IMAGENS SENTINEL-2.
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- Revista Foco (Interdisciplinary Studies Journal), 2023, v. 16, n. 5, p. 1, doi. 10.54751/revistafoco.v16n5-062
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Assessment of the gross primary production dynamics of a Mediterranean holm oak forest by remote sensing time series analysis.
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- Agroforestry Systems, 2015, v. 89, n. 3, p. 491, doi. 10.1007/s10457-015-9786-x
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Resilient botany: Innovation in the face of limited mobility and resources.
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- Applications in Plant Sciences, 2024, v. 12, n. 2, p. 1, doi. 10.1002/aps3.11577
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Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives.
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- Frontiers in Plant Science, 2017, p. 1, doi. 10.3389/fpls.2017.01111
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The Role of Remote Sensing in Agriculture and Future Vision.
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- Agris On-Line Papers in Economics & Informatics, 2022, v. 14, n. 1, p. 107, doi. 10.7160/aol.2022.140109
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ResNet50 in remote sensing and agriculture: evaluating image captioning performance for high spectral data.
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- Environmental Earth Sciences, 2024, v. 83, n. 23, p. 1, doi. 10.1007/s12665-024-11950-2
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Development of a low-cost quadrotor UAV based on ADRC for agricultural remote sensing.
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- International Journal of Agricultural & Biological Engineering, 2019, v. 12, n. 4, p. 82, doi. 10.25165/j.ijabe.20191204.4641
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Ground-based hyperspectral remote sensing for weed management in crop production.
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- International Journal of Agricultural & Biological Engineering, 2016, v. 9, n. 2, p. 98, doi. 10.3965/j.ijabe.20160902.2137
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A Sensitive Band to Optimize Winter Wheat Crop Residue Cover Estimation by Eliminating Moisture Effect.
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- Sustainability (2071-1050), 2019, v. 11, n. 11, p. 3032, doi. 10.3390/su11113032
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Potentiality of Landsat-9 for early-season mapping of winter garlic and winter wheat.
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- Geo-Spatial Information Science, 2024, v. 27, n. 6, p. 2199, doi. 10.1080/10095020.2024.2311868
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Spatiotemporal dynamics of agricultural drought and food insecurity in Asia.
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- Journal of Positive School Psychology, 2023, v. 7, n. 2, p. 89
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ContexNestedU-Net: Efficient Context-Aware Semantic Segmentation Architecture for Precision Agriculture Applications Based on Multispectral Remote Sensing Imagery.
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- Traitement du Signal, 2024, v. 41, n. 5, p. 2425, doi. 10.18280/ts.410517
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Artificial Intelligence (AI) as a complementary technology for agricultural Remote Sensing (RS) in plant physiology teaching.
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- REiDoCrea: Revista Electrónica de Investigación y Docencia Creativa, 2022, v. 11, p. 695
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Toward Cloud‐Native, Machine Learning Base Detection of Crop Disease With Imaging Spectroscopy.
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- Journal of Geophysical Research. Biogeosciences, 2023, v. 128, n. 6, p. 1, doi. 10.1029/2022JG007342
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Imputation of Missing Parts in UAV Orthomosaics Using PlanetScope and Sentinel-2 Data: A Case Study in a Grass-Dominated Area.
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- ISPRS International Journal of Geo-Information, 2023, v. 12, n. 2, p. 41, doi. 10.3390/ijgi12020041
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Development of a New Phenology Algorithm for Fine Mapping of Cropping Intensity in Complex Planting Areas Using Sentinel-2 and Google Earth Engine.
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- ISPRS International Journal of Geo-Information, 2021, v. 10, n. 9, p. 587, doi. 10.3390/ijgi10090587
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Monitoring and Assessment of Salinity and Chemicals in Agricultural Lands by a Remote Sensing Technique and Soil Moisture with Chemical Index Models.
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- Geosciences (2076-3263), 2020, v. 10, n. 6, p. 207, doi. 10.3390/geosciences10060207
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Normalized difference vegetation index analysis reveals increase of biomass production and stability during the conversion from conventional to organic farming.
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- Global Change Biology, 2024, v. 30, n. 8, p. 1, doi. 10.1111/gcb.17461
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The spatial sensitivity of the spectral diversity–biodiversity relationship: an experimental test in a prairie grassland.
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- Ecological Applications, 2018, v. 28, n. 2, p. 541, doi. 10.1002/eap.1669
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Digital insights: bridging the phenotype-to-genotype divide.
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- Journal of Experimental Botany, 2021, v. 72, n. 8, p. 2807, doi. 10.1093/jxb/erab108
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County‐Level Evaluation of Large‐Scale Gridded Data Sets of Irrigated Area Over China.
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- Journal of Geophysical Research. Atmospheres, 2024, v. 129, n. 5, p. 1, doi. 10.1029/2023JD040333
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Investigating capability of open archive multispectral and SAR datasets for Wheat crop monitoring and acreage estimation studies.
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- Earth Science Informatics, 2021, v. 14, n. 4, p. 2017, doi. 10.1007/s12145-021-00656-9
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Estimation of summer maize biomass based on a crop growth model.
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- Emirates Journal of Food & Agriculture (EJFA), 2021, v. 33, n. 9, p. 742, doi. 10.9755/ejfa.2021.v33.i9.2757
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Sub-pixel crops mapping using random forest by integrating multi-source remote sensing and agricultural inventory data.
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- Geophysical Research Abstracts, 2019, v. 21, p. 1
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New technologies as a basis to improve N fertilization.
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- Geophysical Research Abstracts, 2019, v. 21, p. 1
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Assessment of farmland afforestation in the upstream Yangtze River, China.
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- Outlook on Agriculture, 2012, v. 41, n. 2, p. 97, doi. 10.5367/oa.2012.0080
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Precision farming in India – a review.
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- Outlook on Agriculture, 2012, v. 41, n. 2, p. 139, doi. 10.5367/oa.2012.0082
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Remote Sensing for Sustainable Crop Water Management in a Changing Climate.
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- Environmental Science & Sustainable Development, 2024, v. 9, n. 4, p. 1, doi. 10.21625/essd.v9i4.1120
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Applicability and efficiency of remote sensing of agricultural areas.
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- Bulgarian Journal of Agricultural Science, 2022, v. 28, n. 5, p. 933
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Precision Agriculture: A Remote Sensing Monitoring System Architecture †.
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- Information (2078-2489), 2019, v. 10, n. 11, p. 348, doi. 10.3390/info10110348
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Analysis of Synthetic Aperture Radar for Agriculture Applications: A Review.
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- ProEnvironment Promediu, 2019, v. 12, n. 38, p. 240
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Notes on UAS and Remote Sensing of Insect Damage.
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- American Journal of Potato Research, 2021, v. 98, n. 1, p. 16, doi. 10.1007/s12230-020-09816-x
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Novel artificial intelligence assisted Landsat-8 imagery analysis for mango orchard detection and area mapping.
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- PLoS ONE, 2024, v. 19, n. 6, p. 1, doi. 10.1371/journal.pone.0304450
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Extraction and spatio-temporal analysis of phenological dates of winter wheat in north Henan Province of China from 2003 to 2018 based on MODIS NDVI time series.
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- PLoS ONE, 2024, v. 19, n. 4, p. 1, doi. 10.1371/journal.pone.0300486
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Advancing crop classification in smallholder agriculture: A multifaceted approach combining frequency-domain image co-registration, transformer-based parcel segmentation, and Bi-LSTM for crop classification.
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- PLoS ONE, 2024, v. 19, n. 2, p. 1, doi. 10.1371/journal.pone.0299350
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Análise de dados Harmonized Landsat Sentinel para mapeamento de uso e cobertura da terra em área de expansão agrícola no Cerrado.
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- Boletim de Geografia, 2023, v. 41, p. 38, doi. 10.4025/bolgeogr.v41.a2023.e64865
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Long wavelength type-II superlattice barrier infrared detector for CubeSat hyperspectral thermal imager.
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- Opto-Electronics Review, 2023, v. 31, p. 1, doi. 10.24425/opelre.2023.144569
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Minimizing the adverse effects of agriculture on the environment: the case of Russia.
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- Environment, Development & Sustainability, 2024, v. 26, n. 7, p. 17837, doi. 10.1007/s10668-023-03366-y
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РАЗРАБОТКА АЛГОРИТМА ДОЛГОВРЕМЕННОГО УЧЕТА ИСПОЛЬЗОВАНИЯ СЕЛЬХОЗЗЕМЕЛЬ С ПРИМЕНЕНИЕМ ГИС-ТЕХНОЛОГИИ И ПРОМЕЖУТОЧНЫХ ДАННЫХ ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ
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- Journal of Geography & Environmental Management, 2024, v. 72, n. 1, p. 61, doi. 10.26577/JGEM.2024.v72.i1.05
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偏振光谱在大田作物农学参量反演中的研究进展.
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- Acta Agriculturae Zhejiangensis, 2024, v. 36, n. 11, p. 2596, doi. 10.3969/j.issn.1004-1524.20231352
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融合YOLOvSs与Criminisi算法的农业 遥感图像去云方法研究.
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- Journal of Northwest A & F University - Natural Science Edition, 2023, v. 51, n. 3, p. 143, doi. 10.13207/j.cnki.jnwafu.2023.03.015
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Detection of Crop Damage in Maize Using Red–Green–Blue Imagery and LiDAR Data Acquired Using an Unmanned Aerial Vehicle.
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- Agronomy, 2025, v. 15, n. 1, p. 238, doi. 10.3390/agronomy15010238
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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models.
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- Agronomy, 2025, v. 15, n. 1, p. 205, doi. 10.3390/agronomy15010205
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High-Precision Tea Plantation Mapping with Multi-Source Remote Sensing and Deep Learning.
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- Agronomy, 2024, v. 14, n. 12, p. 2986, doi. 10.3390/agronomy14122986
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Harnessing Data-Driven Technologies for Sustainable Farming Practices.
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- Agronomy, 2024, v. 14, n. 12, p. 2969, doi. 10.3390/agronomy14122969
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Artificial Intelligence Applied to Support Agronomic Decisions for the Automatic Aerial Analysis Images Captured by UAV: A Systematic Review.
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- Agronomy, 2024, v. 14, n. 11, p. 2697, doi. 10.3390/agronomy14112697
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Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification.
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- Agronomy, 2024, v. 14, n. 11, p. 2670, doi. 10.3390/agronomy14112670
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Research on Path Planning of Agricultural UAV Based on Improved Deep Reinforcement Learning.
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- Agronomy, 2024, v. 14, n. 11, p. 2669, doi. 10.3390/agronomy14112669
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