Assessment of the Vegetative Index NDVI as an Indicator of Crop Yield

Rodimtsev, S.A.; Pavlovskaya, Ninel; Vershinin, Stepan; Gorkova, Irina; Gagarina, Irina

doi:10.1007/978-3-031-21219-2_71

Lecture Notes in Networks and Systems

2023

DOI: 10.1007/978-3-031-21219-2_71

|View full text |Cite

Assessment of the Vegetative Index NDVI as an Indicator of Crop Yield

S.A. Rodimtsev

Ninel Pavlovskaya²,

Stepan Vershinin³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Differentiating Cheatgrass and Medusahead Phenological Characteristics in Western United States Rangelands

Benedict,

Boyte,

Dahal

2024

Remote Sensing

View full text Add to dashboard Cite

Expansions in the extent and infestation levels of exotic annual grass (EAG) within the rangelands of the western United States are well documented. Land managers are tasked with developing plans to limit EAG spread and prevent irreversible ecosystem deterioration. The most common EAG species and the subject of extensive study is Bromus tectorum (cheatgrass). Cheatgrass has spread rapidly in western rangelands since its initial invasion more than 100 years ago. Another concerning aggressive EAG, Taeniatherum caput-medusae (medusahead), is also commonly found in some of these areas. To control the spread of EAGs, researchers have investigated applying several control methods during different developmental stages of cheatgrass and medusahead. These control strategies require accurate maps of the timing and spatial patterns of the developmental stages to apply mitigation strategies in the correct areas at the right time. In this study, we developed annual phenological datasets for cheatgrass and medusahead with two objectives. The first objective was to determine if cheatgrass and medusahead can be differentiated at 30 m resolution using their phenological differences. The second objective was to establish an annual phenology metric regression tree model used to map the growing seasons of cheatgrass and medusahead. Harmonized Landsat and Sentinel-2 (HLS)-derived predicted weekly cloud-free 30 m normalized difference vegetation index (NDVI) images were used to develop these metric maps. The result of this effort was maps that identify the start and end of sustained growing season time for cheatgrass and medusahead at 30 m for the Snake River Plain and Northern Basin and Range ecoregions. These phenological datasets also identify the start and end-of-season NDVI values, along with maximum NDVI throughout the study period. These metrics may be utilized to characterize annual growth patterns for cheatgrass and medusahead. This approach can be utilized to plan time-sensitive control measures such as herbicide applications or cattle grazing.

show abstract

Differentiating Cheatgrass and Medusahead Phenological Characteristics in Western United States Rangelands

Benedict,

Boyte,

Dahal

2024

Remote Sensing

View full text Add to dashboard Cite

show abstract

Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis

Rhymee,

Shams,

Ratanyake

et al. 2024

intij

View full text Add to dashboard Cite

This study presents a novel approach to predicting paddy yields in Brunei's Wasan Rice Scheme using projected normalized difference vegetation index (NDVI) values derived from climate projections under three time periods: near future (2020–2046), mid-future (2047–2073), and far future (2074–2100). Employing CMIP6 socioeconomic pathways (SSP245, SSP370, SSP585), random forest (RF) and multiple linear regression (MLR) models were utilised to link historical NDVI with meteorological factors such as rainfall and temperature. Results indicate that main-season yields are expected to decline or stabilize across scenarios, while off-season NDVI consistently increases, reflecting robust vegetation recovery. These findings emphasise the differential impacts of climate change across growing seasons, providing critical insights for agricultural planning and adaptation strategies. By integrating scenario-based NDVI projections and predictive modeling, this study offers a comprehensive framework for understanding future crop dynamics under changing climatic conditions.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Assessment of the Vegetative Index NDVI as an Indicator of Crop Yield

Cited by 2 publications

References 19 publications

Differentiating Cheatgrass and Medusahead Phenological Characteristics in Western United States Rangelands

Differentiating Cheatgrass and Medusahead Phenological Characteristics in Western United States Rangelands

Exploring Rice Yield Variability Under Climate Change Through NDVI Analysis

Contact Info

Product

Resources

About