Crop Monitoring Using Microwave Remote Sensing

Srikanth, P.; Chakraborty, Abhishek; Murthy, C. S.

doi:10.1007/978-981-15-6864-0_5

Cited by 2 publications

(4 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many agricultural sensors and tools are available to assess spatial crop, soil and weather data (Kassim, Mat, and Harun 2014;Kumar and Ilango 2018;Srikanth, Chakraborty, and Murthy 2021;Yin et al 2021;Hallik et al 2022). These in situ and on-the-go sensors are: LIDAR and RADAR sensors (Esch et al 2018); UAV drones (Inoue 2020;Awais et al 2022); electromagnetic induction (EMI) sensor; airborne imageries (Tack et al 2019); hyperspectral sensing systems (Jin et al 2019) and field sensors (Svotwa et al 2013).…”

Section: Components Of Site-specific Crop Managementmentioning

confidence: 99%

Section: Components Of Site‐specific Crop Managementmentioning

confidence: 99%

“…2019; Liu et al. 2021; Perez‐Ruiz, Martínez‐Guanter, and Upadhyaya 2021; Srikanth, Chakraborty, and Murthy 2021; Yin et al. 2021; Awais et al.…”

Section: Introductionmentioning

confidence: 99%

“…For SSCM, monitoring spatial crop, soil and weather data is very crucial. This becomes feasible thanks to GNSS-based technologies, GPS mounted crop harvesters, crop and soil sensing systems and digital sensors (Long et al 2016;Jin et al 2019;Liu et al 2021;Perez-Ruiz, Martínez-Guanter, and Upadhyaya 2021;Srikanth, Chakraborty, and Murthy 2021;Yin et al 2021;Awais et al 2022;Hallik et al 2022).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Broad Scope of Site‐Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review

Ali,

Hassan,

Kaul

2024

J Agronomy Crop Science

View full text Add to dashboard Cite

Precision agriculture (PA) has great potential to increase agricultural productivity and profitability while reducing input costs and environmental impacts. Within PA, site‐specific crop management (SSCM) is considered the main premise, in which tillage operations and precise crop inputs (such as seed, fertiliser, water, pesticide and agrochemical) are applied according to field variability. The main aim of this review was to highlight the methods and tools used for spatial crop monitoring, soil and weather data influencing crop productivity and to support the adoption of SSCM technology. To achieve this goal: we discussed the main five components of SSCM, methods for monitoring crop and soil data, delineating field management zones (FMZs) and variable rate technologies (VRT) such as precision planting and digital smart sensors used for SSCM application. The review summarised that recent advances in plant and soil sensing systems, artificial intelligence (AI) and machine learning should be used in retrieving and analysing GIS big data for optimised crop inputs supply. Within VRT, light‐bar systems, automatic controllers and sensors are user‐friendly technologies that should be employed in SSCM solution. The authors highlight that adoption of PA can be increased through proper training and education of the farmers, and developing simple, affordable and efficient PA technologies. The review suggests five criteria that should be strictly adopted to get maximum benefits from SSCM: (i) all factors influencing crop yields can be identified; (ii) their effects on crop yields can be determined by using appropriate digital tools and crop modelling; (iii) variable rate crop inputs (VRCIs) should be calculated based on accurate information obtained from plant, soil and environment; (iv) targeted crop inputs should be exercised through global positioning system (GPS) enabled automatic controllers or wireless sensors network (WSN); and (v) right doses of crop inputs (e.g., nitrogen and irrigation) must be applied at the right time and place.

show abstract