Estimating Biophysical Parameters of Native Grasslands Using Spectral Data Derived from Close Range Hyperspectral and Satellite Data

Frank, Thiago; Smith, A. M.; Houston, Bill; Yang, Xiaohui; Guo, Xulin

doi:10.1080/07038992.2022.2088486

Cited by 2 publications

(1 citation statement)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although conducting in situ measurements can be time-consuming and costly, they provide the most dependable information for a specific date and present researchers with an opportunity to gain a comprehensive understanding of the studied environment (Frank et al, 2022). In recent years, a significant effort has been made to determine the water content at the canopy level using in situ remotely sensed data (Feng et al, 2023;Frank et al, 2022;García-Haro et al, 2020). These research studies are based on two approaches: a physically based approach and a statistical one (Liang, 2004).…”

Section: Introductionmentioning

confidence: 99%

Evaluating canopy water content in grasslands by using in situ hyperespectral data

Karakoç,

Karabulut

2023

Mediterr. Bot.

View full text Add to dashboard Cite

The water content of vegetation is considered a key parameter for ecological analysis as well as for agricultural and forestry applications. Remote sensing methods offer significant advantages over traditional field methods for determining the water content of vegetation at the leaf, canopy, and landscape levels. In this study, the potential of hyperspectral vegetation indices in predicting canopy water content in grasslands was evaluated. For this purpose, data were collected from 3 several grasslands located at ~500 m, ~1200 m and ~1400 m altitudes. 71 samples were collected from each study area, and a total of 213 samples were analyzed. In this context, 59 ratio-based hyperspectral vegetation indices were tested. The relationship between canopy water content and hyperspectral vegetation indices was evaluated with linear, exponential, logarithmic and power regression models. The results showed that the NW-3 (920,970) index significantly represents the canopy water content variable. It was determined that the exponential regression model created with this index was able to explain the variations in canopy water content up to 85%. On the other hand, it has been detected that the high level of water content in the vegetation creates a significant saturation problem. Another finding of this study is that the predictive power reaches higher levels in low canopy water content characteristics. The results of this study show that in situ hyperspectral data has a very high potential in determining vegetation water content in grasslands.

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluating canopy water content in grasslands by using in situ hyperespectral data

Karakoç,

Karabulut

2023

Mediterr. Bot.

View full text Add to dashboard Cite

show abstract

Index Insurance for Forage, Pasture, and Rangeland: A Review of Developed (USA and Canada) and Developing (Kenya and Ethiopia) Countries

Maina,

Miller,

Torell

et al. 2024

Sustainability

View full text Add to dashboard Cite

Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable ecosystems. Index insurance, which avoids market failures such as moral hazard, adverse selection, and transactional cost, has been piloted and implemented all over the world. To support future development and research on index-based insurance in livestock systems, operational index insurance for forage, pasture, and rangeland systems in developed (USA and Canada) and developing (Kenya and Ethiopia) countries are reviewed and compared. This paper finds some similar characteristics (huge subsidy payments—ranging from 50 to 100 percent, significant government role, low adoption, insufficient payouts, data challenges, etc.), of this product between the two regions. A major difference between the PRF and NDVI is the number of choices available to users of rainfall index insurance who face close to 3000 choice options, while NDVI users have less than 5 choice options available for them. Based on these insights, we highlight opportunities where the two regions can benchmark and improve upon their respective index insurance schemes—index-based livestock insurance (IBLI) in developing and rainfall index insurance for forage in developed regions.

show abstract

Estimating Biophysical Parameters of Native Grasslands Using Spectral Data Derived from Close Range Hyperspectral and Satellite Data

Cited by 2 publications

References 52 publications

Evaluating canopy water content in grasslands by using in situ hyperespectral data

Evaluating canopy water content in grasslands by using in situ hyperespectral data

Index Insurance for Forage, Pasture, and Rangeland: A Review of Developed (USA and Canada) and Developing (Kenya and Ethiopia) Countries

Contact Info

Product

Resources

About