Relevant bibliographies by topics / Precision farming (PF) remote sensing

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Precision farming (PF) remote sensing'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Precision farming (PF) remote sensing"

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Tripathi, Rahul, Anjani Kumar, P. Guru, et al. "Precision farming technologies for water and nutrient management in rice: Challenges and opportunities." Oryza-An International Journal on Rice 58, Special (2021): 126–42. http://dx.doi.org/10.35709/ory.2021.58.spl.5.

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Enhancing the productivity of crops while reducing the environmental footprint are the major challenges especially for rice farming. Precison farming helps in optimising inputs such as fertilizers and water in tune with crop requirement recognizing the spatial and temporal variabilities within and across field. The precision tools viz. Remote sensing, site specific nutrient management systems, global positioning system (GPS), geographical information system (GIS), variable rate applicator, models and decision support system are used for implementing precision rice farming. The precision nutrie
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Yadav, Ravina, Shivam Yadav, Krishna, Geeta Devi, and Jyoti. "Advancements in Precision Farming: Enhancing Agricultural Sustainability through Technology – A Review." International Journal of Plant & Soil Science 37, no. 2 (2025): 133–53. https://doi.org/10.9734/ijpss/2025/v37i25312.

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Precision Farming (PF), often referred to as Precision Agriculture (PA) or Site-Specific Land Management (SSLM), is a result of significant knowledge in crop and soil management and advances in agricultural technology. Using a variety of methods, including as GPS, GIS, Remote Sensing, Yield Monitoring, Variable Rate Application, Yield Mapping, and the creation of Site-Specific Management Zones (SSMZ), this novel strategy aims to increase soil and crop productivity while reducing effort and expenses. SSMZ is essential for efficient PF because it enhances soil function management by accurately e
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Triantafyllou, Anna, Panagiotis Sarigiannidis, and Stamatia Bibi. "Precision Agriculture: A Remote Sensing Monitoring System Architecture †." Information 10, no. 11 (2019): 348. http://dx.doi.org/10.3390/info10110348.

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Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farmin
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Shaytura, S. V., N. S. Shaytura, A. S. Prudkiy, Yu P. Kozhaev, and V. M. Feoktistova. "Remote sensing for monitoring of fields in precision farming." Zemleustrojstvo, kadastr i monitoring zemel' (Land management, cadastre and land monitoring), no. 8 (July 13, 2023): 485–92. http://dx.doi.org/10.33920/sel-04-2308-06.

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The relevance of the study is determined by the need to move to precision farming due to the lack of land resources and the increasing population of the Earth. The article describes the sequence of work for the transition to precision farming based on geographic information systems, global positioning systems and field monitoring using remote sensing. The sequence of work is as follows: firstly, initial survey of the fields and the sections of the fields, drawing up a map of the fields, and assessing the features of the fields are carried out; the second step – the selection of crops and sowin
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FAKHAR, MI, and MN KHALID. "SATELLITES TO AGRICULTURAL FIELDS: THE ROLE OF REMOTE SENSING IN PRECISION AGRICULTURE." Biological and Agricultural Sciences Research Journal 2023, no. 1 (2023): 14. http://dx.doi.org/10.54112/basrj.v2023i1.14.

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Precision agriculture, driven by the growing demand for sustainable farming practices, relies heavily on technologies such as remote sensing. Despite its critical role, a comprehensive review of remote sensing within the context of precision agriculture remains sparse. This paper aims to bridge this gap by providing a thorough overview of remote sensing technologies, their applications, challenges, future trends, and potential impact on precision agriculture. Employing a literature review methodology, we analyzed key studies to comprehend precision agriculture's evolution and remote sensing te
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Зацерковний, Віталій, and Віктор Ворох. "ERS technologies in precision farming." TECHNICAL SCIENCES AND TECHNOLOGIES, no. 2(36) (2024): 266–77. http://dx.doi.org/10.25140/2411-5363-2024-2(36)-266-277.

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One of the urgent tasks of modern agricultural production is the problem of further development for ensuring the growing demand for food and other agricultural products on an innovative platform of precision agriculture. Precision farming involves the use of geographic information technologies, earth remote sensing (ERS) technologies, the Internet of Things (IoT), big data technologies and artificial intelligence (AI) aimed at increasing crop production and reducing costs. The use of ERS technologies for precision farming tasks is due to the unprecedented availability of high spatial diversity
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Metrikaitytė Gudelė, G., and J. Sužiedelytė Visockienė. "REMOTE SENSING DATA APPLICATION TO MONITOR CARBON FARMING PRACTICES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W9-2024 (March 8, 2024): 257–65. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w9-2024-257-2024.

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Abstract. Carbon farming, a crucial strategy in mitigating climate change and promoting sustainable agriculture, requires precise monitoring to assess its effectiveness. This study explores the transformative potential of remote sensing data, with a focus on the fusion of Multispectral and Synthetic Aperture Radar satellite data, to enhance the precision and efficiency of carbon farming monitoring. Our research addresses the fundamental question: How can remote sensing data optimize the monitoring of carbon farming practices? This question drives our investigation into the practical applicatio
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Gawande, Vaishnavi, D. R. K. Saikanth, B. S. Sumithra, et al. "Potential of Precision Farming Technologies for Eco-Friendly Agriculture." International Journal of Plant & Soil Science 35, no. 19 (2023): 101–12. http://dx.doi.org/10.9734/ijpss/2023/v35i193528.

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Precision farming technologies have the potential to revolutionize agriculture by promoting eco-friendly practices. The review explores the potential advantages of precision farming technologies in achieving sustainable and environmentally conscious agriculture. The application of precision farming techniques allows for the targeted use of resources such as water, fertilizers, and pesticides, minimizing waste and reducing environmental impact. By incorporating advanced technologies like GPS, GIS, remote sensing, and data analytics, precision farming enables farmers to make informed decisions b
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Han, Yuyao. "Application of Unmanned Aerial Vehicle Remote Sensing for Agricultural Monitoring." E3S Web of Conferences 553 (2024): 02022. http://dx.doi.org/10.1051/e3sconf/202455302022.

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Precision agriculture and Smart farming have become the essential backbone for sustainable agricultural production by leveraging cutting-edge remote sensing and communication technologies. With the remarkable development in recent decades, Unmanned Aerial Vehicles (UAV) based sensing technologies have gained rapid proliferation and exploitation in precision agriculture. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications, including crop monitoring, irrigation management, nutrient appl
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Kumar, Vinay, Shiv Kumar Lohan, and Neeraj Kumar Singh. "Remote sensing applications in precision farming for mapping research farm boundaries." International Journal of Geography, Geology and Environment 5, no. 2 (2023): 32–37. http://dx.doi.org/10.22271/27067483.2023.v5.i2a.170.

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Dissertations / Theses on the topic "Precision farming (PF) remote sensing"

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Elmetwalli, Adel M. H. "Remote sensing as a precision farming tool in the Nile Valley, Egypt." Thesis, University of Stirling, 2008. http://hdl.handle.net/1893/844.

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Detecting stress in plants resulting from different stressors including nitrogen deficiency, salinity, moisture, contamination and diseases, is crucial in crop production. In the Nile Valley, crop production is hindered perhaps more fundamentally by issues of water supply and salinity. Predicting stress in crops by conventional methods is tedious, laborious and costly and is perhaps unreliable in providing a spatial context of stress patterns. Accurate and quick monitoring techniques for crop status to detect stress in crops at early growth stages are needed to maximize crop productivity. In t
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Pires, Sandra Maria Garcia Morais. "Proximal remote sensing of soil physical conditions and water availability for precision farming." Thesis, Cranfield University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420680.

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Belal, Abdelaziz Belal Abdel Elmontalbe. "Precision farming in the small farmland in the eastern Nile Delta Egypt using remote sensing and GIS." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980583543.

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Rabe, Nicole J., and University of Lethbridge Faculty of Arts and Science. "Remote sensing of crop biophysical parameters for site-specific agriculture." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2003, 2003. http://hdl.handle.net/10133/195.

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Support for sustainable agriculture by farmers and consumers is increasing as environmental and socio-economic issues rise due to more intensive farm practices. Site-specific crop management is an important component of sutainable agriculture, within which remote sensing can play an integral role. Field and image data were acquired over a farm in Saskatchewan as part of a national research project to demonstrate the advantages of site-specific agriculture for farmers. This research involved the estimation of crop biophysical parameters from airborne hyperspectral imagery using Spectral Mixture
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Goel, Pradeep Kumar. "Hyper-spectral remote sensing for weed and nitrogen stress detection." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82882.

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This study investigated the possibility of using data, acquired from airborne multi-spectral or hyper-spectral sensors, to detect nitrogen status and presence of weeds in crops; with the ultimate aim of contributing towards the development of a decision support system for precision crop management (PCM).<br>A 24-waveband (spectrum range 475 to 910 nm) multi-spectral sensor was used to detect weeds in corn (Zea mays L.) and soybean ( Glycine max (L.) Merr.) in 1999. Analysis of variance (ANOVA), followed by Scheffe's test, were used to determine which wavebands displayed significant diff
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Duchsherer, Christopher Joseph. "On the Profitability of UAS-Based NDVI Imagery for Variable Rate Nitrogen Prescriptions in Corn and Wheat in North Dakota." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28747.

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This study examines the grower’s decision to invest in precision agriculture technologies especially in-season variable rate nitrogen applications based on NDVI data collected from UAVs. NDVI, yield, soil, and other field data were collected from multiple corn and wheat fields located throughout North Dakota. Each field was divided into management zones to determine profitability of utilizing the technology based on in-season nitrogen applications for the grower’s field practice, high, low, and no applications. Results show that using the NDVI data collected from UAVs can be profitable when th
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Araújo, João Célio de. "Determinação de zonas de manejo e estimativa da produtividade de culturas de grãos por meio de videografia aérea digital multiespectral." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/11/11143/tde-05112004-140548/.

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O emprego de câmeras digitais multiespectrais torna possível a utilização de índices de vegetação, obtidos por meio de operações matemáticas entre bandas espectrais de uma mesma imagem. Estes índices podem ser empregados na estimativa de produtividade de culturas agrícolas e no delineamento de zonas de manejo, por apresentarem relação com o vigor da cultura. Algumas variáveis obtidas no campo, como o índice de área foliar (IAF), a altura de plantas e o número de plantas por metro linear, também podem ser empregadas na avaliação do vigor da cultura. O objetivo principal deste trabalho foi avali
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Coppa, Isabel Patricia Maria, and Isabel coppa@csw com au. "The use of remote sensing data for broad acre grain crop monitoring in Southeast Australia." RMIT University. Mathematical and Geospatial Sciences, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070201.095831.

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In 2025, there will be almost 8 billion people to feed as the worlds population rapidly increases. To meet domestic and export demands, Australian grain productivity needs to approximately triple in the next 20 years, and this production needs to occur in an environmentally sustainable manner. The advent of Hi-tech Precision Farming in Australia has shown promise in recent time to optimize the use of resources. Most
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Waheed, Tahir. "Artificial intelligence analysis of hyperspectral remote sensing data for management of water, weed, and nitrogen stresses in corn fields." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86060.

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This study investigated the possibility of using ground-based remotely sensed hyperspectral observations with a special emphasis on detection of water, weed and nitrogen stresses contributing towards in-season decision support for precision crop management (PCM).<br>A three factor split-split-plot experiment, with four randomized blocks as replicates, was established during the growing seasons of 2003 and 2004. Corn (Zea mays L.) hybrid DKC42-22 was grown because this hybrid is a good performer on light soils in Quebec. There were twelve 12 x 12m plots in a block (one replication per tr
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Gargiulo, Juan Ignacio. "Investigations into the applications and impacts of automation in pasture-based dairy systems." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27216.

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Feed and labour together account for between 50 to 75% of the dairy farm costs in pasture-based systems. Optimised grazing management through remote (satellite-based) monitoring of pastures can potentially reduce feed costs, whereas automatic milking systems (AMS) can potentially reduce labour requirements by automating the whole milking process. The overarching objective of this thesis was to identify the limitations to the uptake of these technologies and explore opportunities to make them more efficient and productive. The literature review in Chapter 2 highlighted that low accuracy in the
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Books on the topic "Precision farming (PF) remote sensing"

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Grenzdorffer, Gorres. Konzeption, Entwicklung und Erprobung eines digitalen integrierten flugzeuggetragenen Fernerkundungssystems fur Precision Farming (PFIFF). Verlag der Bayerischen Akademie der Wissenschaften in Kommission bei der C.H. Beck'schen Verlagsbuchhandlung, 2002.

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Oerke, E. C. Precision Crop Protection - the Challenge and Use of Heterogeneity. Springer Science+Business Media B.V., 2010.

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Zhang, Qin. Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2015.

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Zhang, Qin. Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2015.

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Qin, Zhang. Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2021.

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Qin, Zhang. Precision Agriculture Technology for Crop Farming. Taylor & Francis, 2016.

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Qin, Zhang. Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2015.

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Qin, Zhang. Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2015.

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Precision Agriculture Technology for Crop Farming. Taylor & Francis Group, 2015.

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Smart machines, Remote Sensing, Precision Farming, Processes, Mechatronic, Materials and Policies for Safety and Health Aspects. MDPI, 2018. http://dx.doi.org/10.3390/books978-3-03842-866-4.

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Book chapters on the topic "Precision farming (PF) remote sensing"

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Nagavelli, Umarani, T. Sreeja, V. Srilakshmi, and M. Vijay Kumar. "Precision Agriculture with Remote Sensing." In Sustainable Farming through Machine Learning. CRC Press, 2024. http://dx.doi.org/10.1201/9781003484608-14.

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Mulla, D. J. "Geostatistics, Remote Sensing and Precision Farming." In Novartis Foundation Symposia. John Wiley & Sons, Ltd., 2007. http://dx.doi.org/10.1002/9780470515419.ch7.

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Johannsen, C. J., P. G. Carter, P. R. Willis, et al. "Applying Remote Sensing Technology to Precision Farming." In Proceedings of the Fourth International Conference on Precision Agriculture. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1999.precisionagproc4.c43b.

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Vásquez, J. A. Hassán, F. Maroto Molina, and J. E. Guerrero Ginel. "Chapter 11: Integration of precision livestock farming and remote sensing to enhance grazing management in agrosilvopastoral systems: practical considerations." In Practical Precision Livestock Farming. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3_11.

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Mani, Pabitra Kumar, Agniva Mandal, Saikat Biswas, Buddhadev Sarkar, Tarik Mitran, and Ram Swaroop Meena. "Remote Sensing and Geographic Information System: A Tool for Precision Farming." In Geospatial Technologies for Crops and Soils. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6864-0_2.

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Pande, Chaitanya B., and Kanak N. Moharir. "Application of Hyperspectral Remote Sensing Role in Precision Farming and Sustainable Agriculture Under Climate Change: A Review." In Climate Change Impacts on Natural Resources, Ecosystems and Agricultural Systems. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19059-9_21.

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Kapari, M., M. Sibanda, J. Magidi, L. Nhamo, S. Mpandeli, and Tafadzwanashe Mabhaudhi. "Remote Sensing Maize Water Stress in Smallholder Farms: A Systematic Review of Progress, Challenges, and the Way Forward Using Earth Observation Data." In Enhancing Water and Food Security Through Improved Agricultural Water Productivity. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1848-4_4.

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Abstract Maize (Zea mays L.) is a staple food crop that smallholder farmers mostly cultivate under rain-fed conditions in Southern Africa. Despite significant contributions to food production by smallholder farmers, they face climate change-related challenges such as drought, resulting in crop water stress and significant yield losses. This is exacerbated by the lack of financial resources, mechanical skills, and sound climate change adaptation strategies, increasing the yield gaps. This could potentially be addressed through technological advancements such as precision farming systems. Remote
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"Precision Farming." In Remote Sensing Handbook - Three Volume Set. CRC Press, 2018. http://dx.doi.org/10.1201/b19355-68.

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"Precision Farming." In Land Resources Monitoring, Modeling, and Mapping with Remote Sensing. CRC Press, 2015. http://dx.doi.org/10.1201/b19322-15.

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"- Remote Sensing Applications to Precision Farming." In Remote Sensing of Natural Resources. CRC Press, 2013. http://dx.doi.org/10.1201/b15159-23.

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Conference papers on the topic "Precision farming (PF) remote sensing"

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Jena, Pradesh, Francis Dutta, Bijoy K. Handique, and S. P. Aggarwal. "Farm Level Monitoring Through UAV Remote Sensing: a Novel Approach Towards Precision Farming." In 2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2024. https://doi.org/10.1109/ingarss61818.2024.10984389.

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Koroleva, Polina, Dmitry Rukhovich, Alexey Rukhovich, and Galina Chernousenko. "DETECTION OF AGATE-LIKE SOIL COVER STRUCTURES USING NEURAL NETWORK FILTERING OF BIG REMOTE SENSING DATA." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/3.1/s13.26.

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Agate-like soil cover structures (ASCS) of leached chernozems are common in some regions of Russia with a total area of 425 242 km2 (the republics of Tatarstan and Bashkortostan, Orenburg, Samara, and Ulyanovsk regions). The term �agate-like structures� was proposed due to the fact that on remote sensing data they resemble a section of the Timan agate. The structures are formed on loamy and clayey Quaternary sediments with a thickness of 0.5-5 m, overlying Permian sediments (bedrock). It is possible to identify the location of agate-like structures within the framework of the theory of multi-t
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Essen, H., D. Nüßler, C. Krebs, H. Schimpf, W. Johannes, and A. Wahlen. "Polarimetric millimetre wave SAR for precision farming applications." In Remote Sensing, edited by Christopher M. U. Neale and Antonino Maltese. SPIE, 2010. http://dx.doi.org/10.1117/12.863519.

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Garcia Cidad, V., Els Vrindts, and Josse De Baerdemaeker. "Use of very high resolution satellite images for precision farming: recommendations on nitrogen fertilization." In Europto Remote Sensing, edited by Manfred Owe, Guido D'Urso, and Eugenio Zilioli. SPIE, 2001. http://dx.doi.org/10.1117/12.413941.

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Fahsi, Ahmed, Teferi D. Tsegaye, John L. Boggs, Wubishet Tadesse, and Tommy L. Coleman. "Precision agriculture with hyperspectral remotely sensed data, GIS, and GPS technology: a step toward environmentally responsible farming." In Remote Sensing, edited by Edwin T. Engman. SPIE, 1998. http://dx.doi.org/10.1117/12.332759.

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Zilberman, Arkadi, Jiftah Ben Asher, and Norman S. Kopeika. "Remote sensing in precision farming: real-time monitoring of water and fertilizer requirements of agricultural crops." In SPIE Remote Sensing, edited by Christopher M. U. Neale and Antonino Maltese. SPIE, 2016. http://dx.doi.org/10.1117/12.2242724.

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Shaw, David R., and Charles L. Hill. "Remote Sensing Applications in Precision Farming for the Mississippi Delta." In Seventh International Conference and Exposition on Engineering, Construction, Operations, and Business in Space. American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40479(204)20.

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Makedonska, I. O., V. I. Zatserkovnyi, and L. V. Tustanovska. "Application of GIS technologies and remote sensing in precision farming." In 17th International Conference on Geoinformatics - Theoretical and Applied Aspects. EAGE Publications BV, 2018. http://dx.doi.org/10.3997/2214-4609.201801835.

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Amy L. Kaleita and Lei Tian. "Remote Sensing Of Site-Specific Soil Characteristics for Precision Farming." In 2002 Chicago, IL July 28-31, 2002. American Society of Agricultural and Biological Engineers, 2002. http://dx.doi.org/10.13031/2013.9317.

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Reyniers, Mieke, Els Vrindts, Koenraad Dumont, and Josse De Baerdemaeker. "Precision farming through variable fertilizer application by automated detailed tracking of in-season crop properties." In International Symposium on Remote Sensing, edited by Manfred Owe and Guido D'Urso. SPIE, 2002. http://dx.doi.org/10.1117/12.454210.

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Reports on the topic "Precision farming (PF) remote sensing"

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McNairn, H., J. C. Deguise, J. Secker, and J. Shang. Development of Remote Sensing Image Products for Use in Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219750.

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Pacheco, A., A. Bannari, J. C. Deguise, H. McNairn, and K. Staenz. Application of Hyperspectral Remote Sensing for LAI Estimation in Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219855.

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McNairn, H., J. C. Deguise, and A. Pacheco. Remote sensing derived products for precision farming: report on results from Clinton '99. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219916.

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Agassi, Menahem, Michael J. Singer, Eyal Ben-Dor, et al. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7586479.bard.

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The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is
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