scholarly journals Applicability of the Normalized Difference Vegetation Index (NDVI) in Index-Based Crop Insurance Design

2012 ◽  
Vol 4 (4) ◽  
pp. 271-284 ◽  
Author(s):  
Calum G. Turvey ◽  
Megan K. Mclaurin
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Yields ◽  
Low Cost ◽  
Crop Insurance ◽  
The United States ◽  
Extreme Heat ◽  
Precipitation Extreme ◽  
Regression Equations ◽  
Agricultural Insurance

Abstract Index insurance is becoming increasingly popular because of its ability to provide low-cost, relatively easy to implement agricultural insurance for vegetation types whose productivity has been notoriously difficult to measure and to farmers in less-developed nations where traditional crop insurance schemes are not reasonable to implement. This study examines if the remotely sensed normalized difference vegetation index (NDVI) can be an effective basis for index-based crop insurance over a diverse set of locations. To do this the authors compare Advanced Very High Resolution Radiometer (AVHRR) values to cumulative precipitation, extreme heat, and crop yields for 60 locations across the United States for the years 1982–2003. Quadratic regression equations are used to explore these relationships. The findings suggest that the relationship between NDVI, precipitation, extreme heat, and crop yields is highly variable and dependent on location-specific characteristics. Without site-specific calibration, NDVI should not be widely applied to index-based insurance product design. However, NDVI may still be a useful tool in insurance design under certain circumstances. This may be disappointing to proponents of NDVI as a risk transfer mechanism but the authors believe it important to report negative results as a caveat, and to give researchers and practitioners pause before investing time and money into the proposition.

Monitoring rainfed cereals under different soils and rainfall pattern

2020 ◽  
Author(s):  
Ana Maria Tarquis ◽  
David Rivas-Tabares ◽  
Juan J. Martín-Sotoca ◽  
Antonio Saa-Requejo
Keyword(s):  
Soil Properties ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Yields ◽  
Remote Sensing Data ◽  
Weather Conditions ◽  
Observation Data ◽  
Self Organizing Map ◽  
Agricultural Insurance ◽  
Crop Condition

<p>In most Mediterranean climate regions drought events are of great importance and their effects on rainfed crops are evident. Crop yields of rainfed cereal are highly dependent of the soil-plant-atmosphere system, especially referred to the weather conditions and soil properties. However, very few studies are found on the importance of both factors on crop condition.</p><p>Several plots were localized in the midlands of Eresma-Adaja watershed. Combining remote sensing data and agricultural survey work those with monocrop cereal sequences were identify. These plots were clustered based on which soil class were allocated based on a Self-Organizing Map and precipitation regimen elaborated in the area (Rivas-Tabares et al., 2019). Within this area, two contrasting soil properties sites were selected to assess plots with at least 20 years of rainfed monocropping sequences but under similar weather regime. This allows us to analyze the effect and relationships of soil type and rainfall with Normalized Difference Vegetation Index (NDVI) in time.</p><p>The NDVI average from both areas are statistically different in the growing season suggesting that soils and weather conditions are motivating the spectral variability of sites. The influence of soil texture and rainfall regimen related to NDVI values and interannual variability during the crop growth are discussed.</p><p><strong>References</strong></p><p>Rivas-Tabares, D., AM Tarquis, B Willaarts, Á De Miguel. 2019. An accurate evaluation of water availability in sub-arid Mediterranean watersheds through SWAT: Cega-Eresma-Adaja. Agricultural Water Management 212, 211-225.</p><p> </p><p><strong>ACKNOWLEDGEMENTS</strong></p><p>Finding for this work was partially provided by Boosting agricultural Insurance based 465 on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020. The authors also acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish <em>Ministerio de Ciencia Innovación y Universidades</em> of Spain. The data provided by ITACyL and AEMET is greatly appreciated.</p>

scholarly journals Nature inequity and higher COVID-19 case rates in less-green neighbourhoods in the United States

2021 ◽  
Author(s):  
Erica N. Spotswood ◽  
Matthew Benjamin ◽  
Lauren Stoneburner ◽  
Megan M. Wheeler ◽  
Erin E. Beller ◽  
...  
Keyword(s):  
United States ◽  
Low Income ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
The United States ◽  
Incidence Rates ◽  
Lower Income ◽  
Urban Nature ◽  
Urbanized Areas ◽  
Block Groups

AbstractUrban nature—such as greenness and parks—can alleviate distress and provide space for safe recreation during the COVID-19 pandemic. However, nature is often less available in low-income populations and communities of colour—the same communities hardest hit by COVID-19. In analyses of two datasets, we quantified inequity in greenness and park proximity across all urbanized areas in the United States and linked greenness and park access to COVID-19 case rates for ZIP codes in 17 states. Areas with majority persons of colour had both higher case rates and less greenness. Furthermore, when controlling for sociodemographic variables, an increase of 0.1 in the Normalized Difference Vegetation Index was associated with a 4.1% decrease in COVID-19 incidence rates (95% confidence interval: 0.9–6.8%). Across the United States, block groups with lower income and majority persons of colour are less green and have fewer parks. Our results demonstrate that the communities most impacted by COVID-19 also have the least nature nearby. Given that urban nature is associated with both human health and biodiversity, these results have far-reaching implications both during and beyond the pandemic.

scholarly journals Regrowth and ornamental traits of bermudagrass fertilized with sewage sludge

2020 ◽  
Vol 26 (3) ◽  
pp. 390-398
Author(s):  
Philippe Solano Toledo Silva ◽  
Alessandro Reinaldo Zabotto ◽  
Patrick Luan Ferreira dos Santos ◽  
Matheus Vinícius Leal do Nascimento ◽  
Armando Reis Tavares ◽  
...  
Keyword(s):  
Sewage Sludge ◽  
Soil Solution ◽  
Digital Image Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Aesthetic Aspect ◽  
Positive Correlations ◽  
The Aesthetic ◽  
Ornamental Traits

Abstract The sewage sludge is a low-cost material and sustainable alternative to substitute chemical fertilizers on ornamental lawns and gardens. Thus, the objective was to evaluate the effects of the application of sewage sludge on the regrowth and ornamental traits of DiscoveryTM bermudagrass. The experiment was carried out during the fall/winter of 2019. The turf was removed and left the soil exposed for a new grass regrowth. The treatments applied were 0, 357, 714, 1,071 and 1,428 g m-2 sewage sludge spread evenly on the lawn in a single dose. The evaluations were carried out after 120 days and the soil solution (EC and NO3 -), Normalized difference vegetation index, root length, root + rhizome + stolon + leaves volume and digital image analysis were evaluated. The results showed that the increase of sewage sludge positively influenced the turfgrass development, both in the aesthetic aspect and on bermudagrass regrowth. The soil solution can show that the sludge increased the electrical conductivity and NO3- ions; however, it did not hinder the development of the lawn, even having positive correlations between these variables and the biometric evaluations of the plant. It is concluded that the dose of 1,428 g m-2 presented the best results for the evaluated characteristics, being the recommended one for use in the fertilization of bermudagrass DiscoveryTM.

scholarly journals Statistical analysis for satellite-index-based insurance to define damaged pasture thresholds

2019 ◽  
Vol 19 (8) ◽  
pp. 1685-1702 ◽  
Author(s):  
Juan José Martín-Sotoca ◽  
Antonio Saa-Requejo ◽  
Rubén Moratiel ◽  
Nicolas Dalezios ◽  
Ioannis Faraslis ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Damage Threshold ◽  
Threshold Value ◽  
Likelihood Method ◽  
Agricultural Insurance ◽  
Gev Distribution ◽  
Normal Distributions

Abstract. Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used in countries like the USA, Canada and Spain for damaged pasture and forage insurance over the last few years. This type of agricultural insurance is called satellite-index-based insurance (SIBI). In SIBI, the occurrence of damage is defined as normal distributions. In this work a pasture area at the north of the Community of Madrid (Spain) has been delimited by means of Moderate Resolution Imaging Spectroradiometer (MODIS) images. A statistical analysis of NDVI histograms was applied to seek for alternative distributions using the maximum likelihood method and χ2 test. The results show that the normal distribution is not the optimal representation and the generalized extreme value (GEV) distribution presents a better fit through the year based on a quality estimator. A comparison between normal and GEV is shown with respect to the probability under a NDVI threshold value throughout the year. This suggests that an a priori distribution should not be selected and a percentile methodology should be used to define a NDVI damage threshold rather than the average and standard deviation, typically of normal distributions. Highlights. The GEV distribution provides better fit to the NDVI historical observations than the normal one. Differences between normal and GEV distributions are higher during spring and autumn, which are transition periods in the precipitation regimen. NDVI damage threshold shows evident differences using normal and GEV distributions both covering the same probability (24.20 %). NDVI damage threshold values based on percentile calculation are proposed as an improvement in the index-based insurance in damaged pasture.

Evaluation of a Low-cost Camera for Agricultural Applications

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Abdon Francisco Aureliano Netto ◽  
Rodrigo Nogueira Martins ◽  
Guilherme Silverio Aquino De Souza ◽  
Fernando Ferreira Lima Dos Santos ◽  
Jorge Tadeu Fim Rosas
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Vegetation Indices ◽  
Paspalum Notatum ◽  
Crop Canopy ◽  
N Application ◽  
Satisfactory Accuracy ◽  
Agricultural Applications

This study aimed to modify a webcam by replacing its near-infrared (NIR) blocking filter to a low-cost red, green and blue (RGB) filter for obtaining NIR images and to evaluate its performance in two agricultural applications. First, the sensitivity of the webcam to differentiate normalized difference vegetation index (NDVI) levels through five nitrogen (N) doses applied to the Batatais grass (Paspalum notatum Flugge) was verified. Second, images from maize crops were processed using different vegetation indices, and thresholding methods with the aim of determining the best method for segmenting crop canopy from the soil. Results showed that the webcam sensor was capable of detecting the effect of N doses through different NDVI values at 7 and 21 days after N application. In the second application, the use of thresholding methods, such as Otsu, Manual, and Bayes when previously processed by vegetation indices showed satisfactory accuracy (up to 73.3%) in separating the crop canopy from the soil.

Improving the analysis of the soil-plant-atmosphere system thought earth observations in large monocrop cereal sequences

2020 ◽  
Author(s):  
David Rivas-Tabares ◽  
Juan J. Martín-Sotoca ◽  
Antonio Saa-Requejo ◽  
Ana María Tarquis
Keyword(s):  
Time Series ◽  
Soil Properties ◽  
Vegetation Index ◽  
Crop Yields ◽  
Observation Data ◽  
Precipitation Regime ◽  
Agricultural Insurance ◽  
Residual Time ◽  
Earth Observations ◽  
Atmosphere System

<p>Crop yields of rainfed cereal are highly dependent of the soil-plant-atmosphere system, especially referred to the weather conditions and soil properties. The study of this interaction is feasible through the earth observations of historical data. Remote sensing data and agricultural survey work together identifying and analyzing plots with monocrop cereal sequences. In this research, we investigate the relation of the Normalized Difference Vegetation Index (NDVI) residual time series behavior relative to soil classes from Self-Organizing Maps (SOM) and the precipitation residual time series.</p><p>The midlands of Eresma-Adaja watershed (Dueros’ River basin, Spain) is historically depicted to rainfed cereal agriculture, some evidence of monocropping sequences are worrisome the water availability in the area. Within this area, two contrasting soil properties sites were selected to assess plots with at least 20 years of rainfed monocropping sequences but under similar weather regime. This allows analyzing the effect and relationships of this practice by soil type in time. For this, we treat the NDVI and precipitation time residual series as signals. The use of the Generalized Structure Function applied to these residual time series and the Hurst exponent, serve to confirm the soil properties differences from SOM and to reinforce the scaling properties of soil-climate interaction in semiarid regions for cereals in monocrop. As a result, the NDVI and precipitation series present an antipersistence behavior supporting that precipitation regime is influencing as the same manner the NDVI residual time series among complimentary factors.</p><p><strong>ACKNOWLEDGEMENTS</strong></p><p>Finding for this work was partially provided by Boosting agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020_EU, DT-SPACE-01-EO-2018-2020. The authors also acknowledge support from Project No. PGC2018-093854-B-I00 of the Spanish <em>Ministerio de Ciencia Innovación y Universidades</em> of Spain. The data provided by ITACyL and AEMET is greatly appreciated.</p><p> </p>

scholarly journals A New Approach for Land Degradation and Desertification Assessment Using Geospatial Techniques

2017 ◽  
Author(s):  
Masoud Masoudi ◽  
Parviz Jokar ◽  
Biswajeet Pradhan
Keyword(s):  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evaluation Method ◽  
Low Cost ◽  
United Nations Environment Programme ◽  
Geospatial Techniques ◽  
New Approach ◽  
Khuzestan Province ◽  
Current State

Abstract. Land degradation reduces production of biomass and vegetation cover in every land uses. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of current state of land degradation or desertification is very difficult because this phenomena includes several complex processes. For that reason, there is no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment based on its current state by modifying of FAO1/UNEP2 index and normalized difference vegetation index (NDVI) index in Khuzestan province, placed in the southwestern part of Iran. The proposed evaluation method is easy to understand the degree of destruction due to low cost and save time. Results showed that based on percent of hazard classes in current condition of land degradation, the most widespread and minimum area of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. While results in the desert area of study area showed that severe class is much widespread than other hazard classes, showing environmentally bad situation in the study area. Statistical results indicated that degradation is highest in desert and then rangeland compared to dry cultivation and forest. Also statistical test showed average of degradation amount in the arid region is higher than other climates. It is hoped that this attempt using geospatial techniques will be found applicable for other regions of the world and better planning and management of lands, too. 1 Food and Agriculture Organization 2 United Nations Environment Programme

Assessing Hemlock Decline Using Visible and Near-Infrared Spectroscopy: Indices Comparison and Algorithm Development

2005 ◽  
Vol 59 (6) ◽  
pp. 836-843 ◽  
Author(s):  
Jennifer Pontius ◽  
Richard Hallett ◽  
Mary Martin
Keyword(s):  
Linear Regression ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Accuracy Assessment ◽  
Stress Index ◽  
Regression Equations ◽  
Near Infrared Reflectance ◽  
Full Spectrum ◽  
Hemlock Decline

Near-infrared reflectance spectroscopy was evaluated for its effectiveness at predicting pre-visual decline in eastern hemlock trees. An ASD FieldSpec Pro FR field spectroradiometer measuring 2100 contiguous 1-nm-wide channels from 350 nm to 2500 nm was used to collect spectra from fresh hemlock foliage. Full spectrum partial least squares (PLS) regression equations and reduced stepwise linear regression equations were compared. The best decline predictive model was a 6-term linear regression equation ( R2 = 0.71, RMSE = 0.591) based on: Carter Miller Stress Index (R694/R760), Derivative Chlorophyll Index (FD705/FD723), Normalized Difference Vegetation Index ((R800 – R680)/(R800 + R680)), R950, R1922, and FD1388. Accuracy assessment showed that this equation predicted an 11-class decline rating with a 1-class tolerance accuracy of 96% and differentiated healthy trees from those in very early decline with 72% accuracy. These results indicate that narrow-band sensors could be developed to detect very early stages of hemlock decline, before visual symptoms are apparent. This capability would enable land managers to identify early hemlock woolly adelgid infestations and monitor forest health over large areas of the landscape.

scholarly journals USE OF GREENDRONE UAS SYSTEM FOR MAIZE CROP MONITORING

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 263-268 ◽  
Author(s):  
A. K. Nasir ◽  
M. Tharani
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Research Work ◽  
Aerial Images ◽  
Stress Index ◽  
Maize Crop ◽  
Crop Monitoring ◽  
Water Stress Index ◽  
Long Endurance

This research work presents the use of a low-cost Unmanned Aerial System (UAS) – GreenDrone for the monitoring of Maize crop. GreenDrone consist of a long endurance fixed wing air-frame equipped with a modified Canon camera for the calculation of Normalized Difference Vegetation Index (NDVI) and FLIR thermal camera for Water Stress Index (WSI) calculations. Several flights were conducted over the study site in order to acquire data during different phases of the crop growth. By the calculation of NDVI and NGB images we were able to identify areas with potential low yield, spatial variability in the plant counts, and irregularities in nitrogen application and water application related issues. Furthermore, some parameters which are important for the acquisition of good aerial images in order to create quality Orthomosaic image are also discussed.

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