Relevant bibliographies by topics / Early crop mapping

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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 'Early crop mapping'

Author: Grafiati
Published: 10 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Early crop mapping"

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You, Nanshan, Jinwei Dong, Jing Li, Jianxi Huang, and Zhenong Jin. "Rapid early-season maize mapping without crop labels." Remote Sensing of Environment 290 (May 2023): 113496. http://dx.doi.org/10.1016/j.rse.2023.113496.

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Mirzaei, Saham, Simone Pascucci, Maria Francesca Carfora, et al. "Early-Season Crop Mapping by PRISMA Images Using Machine/Deep Learning Approaches: Italy and Iran Test Cases." Remote Sensing 16, no. 13 (2024): 2431. http://dx.doi.org/10.3390/rs16132431.

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Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with Sentinel-2 multispectral imagery to produce early- and in-season crop maps using consolidated machine and deep learning algorithms. Results show that the accuracy of crop type classification using Sentinel-2 images is meaningfully poor compared with PRISMA (14% in overall accuracy (OA)). The 1D-CNN algorithm, with 89%
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Li, Kaiyuan, Wenzhi Zhao, Jiage Chen, Liqiang Zhang, Duoduo Hu, and Qiao Wang. "Predicting Crop Growth Patterns with Spatial–Temporal Deep Feature Exploration for Early Mapping." Remote Sensing 15, no. 13 (2023): 3285. http://dx.doi.org/10.3390/rs15133285.

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The timely and accurate mapping of crops over large areas is essential for alleviating food crises and formulating agricultural policies. However, most existing classical crop mapping methods usually require the whole-year historical time-series data that cannot respond quickly to the current planting information, let alone for future prediction. To address this issue, we propose a novel spatial–temporal feature and deep integration strategy for crop growth pattern prediction and early mapping (STPM). Specifically, the STPM first learns crop spatial–temporal evolving patterns from historical d
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Wang, Yiqun, Hui Huang, and Radu State. "Early Crop Mapping Using Dynamic Ecoregion Clustering: A USA-Wide Study." Remote Sensing 15, no. 20 (2023): 4962. http://dx.doi.org/10.3390/rs15204962.

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Mapping target crops earlier than the harvest period is an essential task for improving agricultural productivity and decision-making. This paper presents a new method for early crop mapping for the entire conterminous USA (CONUS) land area using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data with a dynamic ecoregion clustering approach. Ecoregions, geographically distinct areas with unique ecological patterns and processes, provide a valuable framework for large-scale crop mapping. We conducted our dynamic ecoregion clustering by analyzing soil, cli
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Yi, Zhiwei, Li Jia, Qiting Chen, Min Jiang, Dingwang Zhou, and Yelong Zeng. "Early-Season Crop Identification in the Shiyang River Basin Using a Deep Learning Algorithm and Time-Series Sentinel-2 Data." Remote Sensing 14, no. 21 (2022): 5625. http://dx.doi.org/10.3390/rs14215625.

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Timely and accurate crop identification and mapping are of great significance for crop yield estimation, disaster warning, and food security. Early-season crop identification places higher demands on the quality and mining of time-series information than post-season mapping. In recent years, great strides have been made in the development of deep-learning algorithms, and the emergence of Sentinel-2 data with a higher temporal resolution has provided new opportunities for early-season crop identification. In this study, we aimed to fully exploit the potential of deep-learning algorithms and tim
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Wei, Peng, Huichun Ye, Shuting Qiao, et al. "Early Crop Mapping Based on Sentinel-2 Time-Series Data and the Random Forest Algorithm." Remote Sensing 15, no. 13 (2023): 3212. http://dx.doi.org/10.3390/rs15133212.

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Early-season crop mapping and information extraction is essential for crop growth monitoring and yield prediction, and it facilitates agricultural management and rapid response to agricultural disasters. However, training classifiers by remote sensing classification features for early crop prediction can be challenging, as early-season mapping can only use remote sensing image data during part of the crop growth period. In order to overcome this limitation, this study takes the Sanjiang Plain as an example to investigate the earliest identification time of rice, maize and soybean based on Sent
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Osman, Julien, Jordi Inglada, and Jean-François Dejoux. "Assessment of a Markov logic model of crop rotations for early crop mapping." Computers and Electronics in Agriculture 113 (April 2015): 234–43. http://dx.doi.org/10.1016/j.compag.2015.02.015.

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Wen, Caiyun, Miao Lu, Ying Bi, et al. "Customized crop feature construction using genetic programming for early- and in-season crop mapping." Computers and Electronics in Agriculture 231 (April 2025): 109949. https://doi.org/10.1016/j.compag.2025.109949.

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Luo, Jiansong, Min Xie, Qiang Wu, et al. "Early Crop Identification Study Based on Sentinel-1/2 Images with Feature Optimization Strategy." Agriculture 14, no. 7 (2024): 990. http://dx.doi.org/10.3390/agriculture14070990.

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The timely and accurate mapping of crop types is crucial for agricultural insurance, futures, and assessments of food security risks. However, crop mapping is currently focused on the post-harvest period, and less attention has been paid to early crop mapping. In this study, the feasibility of using Sentinel-1 (S1) and Sentinel-2 (S2) data for the earliest identifiable time (EIT) for major crops (sunflower, maize, spring wheat, and melon) was explored in the Hetao Irrigation District (HID) of China, based on the Google Earth Engine (GEE) platform. An early crop identification strategy based on
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Wang, Yiqun, Hui Huang, and Radu State. "Cross Domain Early Crop Mapping with Label Spaces Discrepancies using MultiCropGAN." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1-2024 (May 9, 2024): 241–48. http://dx.doi.org/10.5194/isprs-annals-x-1-2024-241-2024.

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Abstract. Mapping target crops before the harvest season for regions lacking crop-specific ground truth is critical for global food security. Utilizing multispectral remote sensing and domain adaptation methods, prior studies strive to produce precise crop maps in these regions (target domain) with the help of the crop-specific labelled remote sensing data from the source regions (source domain). However, existing approaches assume identical label spaces across those domains, a challenge often unmet in reality, necessitating a more adaptable solution. This paper introduces the Multiple Crop Ma
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Dissertations / Theses on the topic "Early crop mapping"

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CROCI, MICHELE. "Telerilevamento per il settore agroalimentare: Metodi e Applicazioni." Doctoral thesis, Università Cattolica del Sacro Cuore, 2022. http://hdl.handle.net/10280/120588.

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Nell'ultimo decennio, il settore agroalimentare e le autorità locali hanno investito in nuove tecnologie per affrontare le crescenti sfide sociali, economiche e ambientali legate al cibo e alla sua sostenibilità. L'intelligenza artificiale (AI) e il Machine Learning (ML) alimentate con dati ad alta risoluzione spaziale e temporale (es. telerilevamento, sensori prossimali, dati meteorologici e mappe del suolo) permettono lo sviluppo di nuovi strumenti in grado di monitorare l'intera catena agroalimentare consentendo a sua volta l'ottimizzazione dei processi produttivi e la loro sostenibilità. I
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Books on the topic "Early crop mapping"

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Snider, Jill D. Lucean Arthur Headen. University of North Carolina Press, 2020. http://dx.doi.org/10.5149/northcarolina/9781469654355.001.0001.

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Born in Carthage, North Carolina, Lucean Arthur Headen (1879-1957) grew up amid former slave artisans. Inspired by his grandfather, a wheelwright, and great-uncle, a toolmaker, he dreamed as a child of becoming an inventor. His ambitions suffered the menace of Jim Crow and the reality of a new inventive landscape in which investment was shifting from lone inventors to the new “industrial scientists.” But determined and ambitious, Headen left the South, and after toiling for a decade as a Pullman porter, risked everything to pursue his dream. He eventually earned eleven patents, most for innova
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Book chapters on the topic "Early crop mapping"

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da Silva Pereira, Guilherme, Carla Cristina da Silva, João Ricardo Bachega Feijó Rosa, et al. "New Analytical Tools for Molecular Mapping of Quantitative Trait Loci in Sweetpotato." In Compendium of Plant Genomes. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65003-1_6.

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AbstractQuantitative trait loci(QTL) mapping is an important tool in sweetpotato research, contributing to the understanding of genetic architecture of various traits, including dry matter, nematode resistance, and flesh color. Early QTL work was carried out by using marker information alone via single marker analysis (SMA), or based on parent-specific linkage map using interval mapping (IM), composite interval mapping (CIM), and multiple interval mapping (MIM). Initially developed for inbred diploid species populations, these methods did not fully consider the complex autopolyploid, outcrossi
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Singh, Balwant, Shefali Mishra, Deepak Singh Bisht, and Rohit Joshi. "Growing Rice with Less Water: Improving Productivity by Decreasing Water Demand." In Rice Improvement. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66530-2_5.

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AbstractRice is a staple food for more than half of the global population. With the increasing population, the yield of rice must correspondingly increase to fulfill the requirement. Rice is cultivated worldwide in four different types of ecosystems, which are limited by the availability of irrigation water. However, water-limiting conditions negatively affect rice production; therefore, to enhance productivity under changing climatic conditions, improved cultivation practices and drought-tolerant cultivars/varieties are required. There are two basic approaches to cultivation: (1) plant based
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Adhikary, Saju, Benukar Biswas, Manish Kumar Naskar, Bishal Mukherjee, Aditya Pratap Singh, and Kousik Atta. "Remote Sensing for Agricultural Applications." In Arid Environment - Perspectives, Challenges and Management [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106876.

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The application of remote sensing in quantifying the crop health status is trending. Sensors can serve as early warning systems for countering climatic or biological aberrations before having negative impacts on crop yield. Remote sensing applications have been playing a significant role in agriculture sector for evaluating plant health, yield and crop loss (%) estimation, irrigation management, identification of crop stress, weed and pest detection, weather forecasting, gathering crop phenological informations etc. Forecast of crop yields by using remote sensing inputs in conjunction with cro
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O'Hara, Patrick F. "Early Proterozoic Gold Mineralization, Alteration Assemblages, and Geochemistry of the Huron-Montezuma Prospect, Yavapai County, Arizona." In Proterozoic Ore Deposits of the Southwestern U.S. Society of Economic Geologists, 1987. http://dx.doi.org/10.5382/gb.01.23.

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Abstract Metavolcanic and metasedimentary rocks of the Yavapai Series (Anderson and Creasey, 1958) crop out within the area described in this study. These rocks were originally subdivided into the Ash Creek Group and Alder Group (Anderson and Blacet, 1972). Isotopic data led Anderson and others (1971) to replace the name Alder Group with the Big Bug Group, which includes all the rocks of the Yavapai Series exposed in the Prescott-Jerome area. The Big Bug Group is divided into three formations. From oldest to youngest they are: 1) Green Gulch Volcanics; 2) Spud Mountain Volcanics; and 3) Iron K
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Mróz Marek and Mleczko Magdalena. "The Synergy of Optical VHR/HR Satellite Images and TerraSAR-X StripMap Data in Early and Rapid Agricultural Crops Mapping." In Imagin[e,g] Europe. IOS Press, 2010. https://doi.org/10.3233/978-1-60750-494-8-271.

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The paper presents the methodology and results of early agricultural crops mapping achieved with TerraSAR-X StripMap images acquired at single and dual polarization mode, during spring and summer 2008 over test site Malbork in Northern Poland. Two types of images in time sequence were ordered and acquired: stripNear_013R, VV/VH and strip_007R, VV. The first TSX observations and Rapid Field Visits started at the moment just after spring cereals have been emerging over the soil but not yet influencing radar backscattered signal coming from soil. Two short-time TSX series were analyzed from crops
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Conference papers on the topic "Early crop mapping"

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Gené-Mola, Jordi, Magí Pamies-Sans, César Minuesa, Jaume Casadesús, and Joaquim Bellvert. "Early Crop Type Classification and Mapping Using Sparse and Multi-Year Remote Sensing Data." In 2024 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). IEEE, 2024. https://doi.org/10.1109/metroagrifor63043.2024.10948773.

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Sandeepanie, W. D. Nilakshi, Samadhi Rathnayake, and Amali Gunasinghe. "Disease Identification and Mapping using CNN in Paddy Fields." In SLIIT International Conference on Advancements in Sciences and Humanities 2023. Faculty of Humanities and Sciences, SLIIT, 2023. http://dx.doi.org/10.54389/nkkj6476.

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Rice, a globally vital staple crop, sustains over half of the world’s caloric needs while supporting the livelihoods of small-scale farmers and landless laborers. The escalating global population has led to an increased demand for rice production. Sri Lanka, renowned for its premium rice quality, has a rich history of paddy cultivation. However, a substantial portion of the country’s 708,000 hectares of paddy land remains underutilized due to water scarcity and unstable terrain. The objective of this project is to enhance paddy crop quality during the critical vegetative phase by employing mac
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Mohite, Jayantrao, Suryakant Sawant, Ankur Pandit, and Srinivasu Pappula. "Integration of Sentinel 1 and 2 Observations for Mapping Early and Late Sowing of Soybean and Cotton Crop Using Deep Learning." In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2020. http://dx.doi.org/10.1109/igarss39084.2020.9323482.

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Savidis, Anthony, and Anthony Peris. "Rapid Interactive Software-Architecture Design with Split-n-Join Actions." In 8th International Conference on Human Interaction and Emerging Technologies. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002770.

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The architecture design process is an essential and critical part of the overall software development lifecycle. During the early design phases it is imperative to ensure that an optimal architecture is outlined, reflecting the requirements of the target software product. Then, continuous refinement, syncing and maintenance is needed, in order to guarantee that the software architecture precisely reflects the particular state of the source code base and vice versa. Both processes involve elements and activities at an abstract level and require support for easy and quick experimentation, explor
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Aminoff, Hedvig. "Mapping Human-Centred Design in innovation-driven Projects: an HRL assessment of an autonomous ferry and remote operations centre concept." In Human Interaction and Emerging Technologies (IHIET 2025). AHFE International, 2025. https://doi.org/10.54941/ahfe1006747.

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The rapid pace of technological development in the maritime sector is driving transformative changes across sociotechnical systems,as autonomous vessel, remote operations, and control infrastructures are developed. However, innovation efforts often focus on the technology itself, leaving critical human factors (HF) aspects underdeveloped. This extended abstract presents a case study from the development of an autonomous urban passenger ferry and its associated remote operations center (ROC), in which the Human Readiness Level (HRL) framework (HFES/ANSI 400-2021) was applied to assess human-sys
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Reports on the topic "Early crop mapping"

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no
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Zhang, Hongbin B., David J. Bonfil, and Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7586464.bard.

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The goals of this project were to develop essential genomic tools for modern chickpea genetics and genomics research, map the genes and quantitative traits of importance to chickpea production and generate DNA markers that are well-suited for enhanced chickpea germplasm analysis and breeding. To achieve these research goals, we proposed the following research objectives in this period of the project: 1) Develop an ordered BAC library with an average insert size of 150 - 200 kb (USA); 2) Develop 300 simple sequence repeat (SSR) markers with an aid of the BAC library (USA); 3) Develop SSR marker
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Feldman, Moshe, Eitan Millet, Calvin O. Qualset, and Patrick E. McGuire. Mapping and Tagging by DNA Markers of Wild Emmer Alleles that Improve Quantitative Traits in Common Wheat. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7573081.bard.

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The general goal was to identify, map, and tag, with DNA markers, segments of chromosomes of a wild species (wild emmer wheat, the progenitor of cultivated wheat) determining the number, chromosomal locations, interactions, and effects of genes that control quantitative traits when transferred to a cultivated plant (bread wheat). Slight modifications were introduced and not all objectives could be completed within the human and financial resources available, as noted with the specific objectives listed below: 1. To identify the genetic contribution of each of the available wild emmer chromosom
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Opportunities, challenges and evidence needs for investing in smallholder farming. Commercial Agriculture for Smallholders and Agribusiness (CASA), 2019. http://dx.doi.org/10.1079/20240191176.

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Commercial Agriculture for Smallholders and Agribusiness (CASA) is a flagship programme financed by the UK Department for International Development (DFID), which seeks to increase economic opportunities for smallholders to step and trade into growing commercial markets. The programme aims to increase investments in agribusinesses which source from smallholder farmers and to generate new evidence and research that amplifies the case for doing business with smallholders. During the inception phase, CASA conducted a survey of 25 investors and investing support stakeholders, to determine key const
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