Estimation of sugar beet biomass and yield comparing NDVI measurements and physical soil parameters

2021 ◽  
pp. 100-109
Author(s):  
Koç Mehmet Tuğrul
Keyword(s):  
Sugar Beet ◽  
Soil Sample ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Analysis ◽  
Soil Parameters ◽  
Growing Seasons ◽  
Relationship Of ◽  
The Relationship ◽  
Moderate Positive Correlation

This study was conducted to estimate the relationship of soil sample analysis and satellite imagery with sugar beet yield (BY). The red NDVI obtained monthly from Landsat OLI satellite images during the 2017 and 2018 sugar beet growing seasons were used to establish relationships between imagery and georeferenced soil sample analyses and sugar beet harvest sites. The study was carried out in the field of Sugar Institute Ilgın Experiment Station, Turkey, in 2017 and 2018. Soil samples were obtained in a 0.4 ha grid, and sugar beet yield and recoverable sugar yield (RSY) were obtained from the same sampling areas. The results showed that there were relationships between some soil analysis factors and BY and beet quality. The overall results showed that the amount of clay, electric conductivity (EC), and organic matter in the field might be indicators of BY and beet quality. A statistically significant moderate positive correlation was also obtained between NDVI (Normalized Difference Vegetation Index) images and BY and RSY values in all images obtained by satellite near the harvest date.

Relationship of soil moisture with solar-induced chlorophyll fluorescence and normalized difference vegetation index in different phenological stages

2020 ◽  
Author(s):  
Qiu Shen ◽  
Jianjun Wu ◽  
Leizhen Liu ◽  
Wenhui Zhao
Keyword(s):  
Soil Moisture ◽  
Chlorophyll Fluorescence ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Maturity Stage ◽  
Phenological Stages ◽  
Active Radiation ◽  
Relationship Of ◽  
The Relationship

<p>As an important part of water cycle in terrestrial ecosystem, soil moisture (SM) provides essential raw materials for vegetation photosynthesis, and its changes can affect the photosynthesis process and further affect vegetation growth and development. Thus, SM is always used to detect vegetation water stress and agricultural drought. Solar-induced chlorophyll fluorescence (SIF) is signal with close ties to photosynthesis and the normalized difference vegetation index (NDVI) can reflect the photosynthetic characteristics and photosynthetic yield of vegetations. However, there are few studies looking at the sensitivity of SIF and NDVI to SM changes over the entire growing season that includes multiple phenological stages. By making use of GLDAS-2 SM products along with GOME-2 SIF products and MODIS NDVI products, we discussed the detailed differences in the relationship of SM with SIF and NDVI in different phenological stages for a case study of Northeast China in 2014. Our results show that SIF integrates information from the fraction of photosynthetically active radiation (fPAR), photosynthetically active radiation (PAR) and SIF<sub>yield</sub>, and is more effective than NDVI for monitoring the spatial extension and temporal dynamics of SM on a short time scale during the entire growing season. Especially, SIF<sub>PAR_norm</sub> is the most sensitive to SM changes for eliminating the effects of seasonal variations in PAR. The relationship of SM with SIF and NDVI varies for different vegetation cover types and phenological stages. SIF is more sensitive to SM changes of grasslands in the maturity stage and  rainfed croplands  in the senescence stage than NDVI, and it has significant sensitivities to SM changes of forests in different phenological stages. The sensitivity of SIF and NDVI to SM changes in the senescence stages stems from the fact that vegetation photosynthesis is relatively weaker at this time than that in the maturity stage, and vegetations in the reproductive growth stage still need much water. Relevant results are of great significance to further understand the application of SIF in SM detection.</p>

scholarly journals Normalized Difference Vegetation Index Temporal Responses to Temperature and Precipitation in Arid Rangelands

2021 ◽  
Vol 13 (5) ◽  
pp. 840
Author(s):  
Ernesto Sanz ◽  
Antonio Saa-Requejo ◽  
Carlos H. Díaz-Ambrona ◽  
Margarita Ruiz-Ramos ◽  
Alfredo Rodríguez ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Lag ◽  
Vegetation Indices ◽  
Aridity Index ◽  
Rangeland Degradation ◽  
Temperature And Precipitation ◽  
Lag Effect ◽  
Relationship Of ◽  
The Relationship

Rangeland degradation caused by increasing misuses remains a global concern. Rangelands have a remarkable spatiotemporal heterogeneity, making them suitable to be monitored with remote sensing. Among the remotely sensed vegetation indices, Normalized Difference Vegetation Index (NDVI) is most used in ecology and agriculture. In this paper, we research the relationship of NDVI with temperature, precipitation, and Aridity Index (AI) in four different arid rangeland areas in Spain’s southeast. We focus on the interphase variability, studying time series from 2002 to 2019 with regression analysis and lagged correlation at two different spatial resolutions (500 × 500 and 250 × 250 m2) to understand NDVI response to meteorological variables. Intraseasonal phases were defined based on NDVI patterns. Strong correlation with temperature was reported in phases with high precipitations. The correlation between NDVI and meteorological series showed a time lag effect depending on the area, phase, and variable observed. Differences were found between the two resolutions, showing a stronger relationship with the finer one. Land uses and management affected the NDVI dynamics heavily strongly linked to temperature and water availability. The relationship between AI and NDVI clustered the areas in two groups. The intraphases variability is a crucial aspect of NDVI dynamics, particularly in arid regions.

Relationship of Neighborhood Greenness to Alzheimer’s Disease and Non-Alzheimer’s Dementia Among 249,405 U.S. Medicare Beneficiaries

2021 ◽  
pp. 1-10
Author(s):  
William W. Aitken ◽  
Joanna Lombard ◽  
Kefeng Wang ◽  
Matthew Toro ◽  
Margaret Byrne ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Odds Ratio ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Based ◽  
Dade County ◽  
Medicare Beneficiaries ◽  
Relationship Of ◽  
The Relationship

Background: Neighborhood greenness (vegetative presence) has been linked to multiple health outcomes, but its relationship to Alzheimer’s disease (AD) and non-Alzheimer’s (non-AD) dementia has been less studied. Objective: This study examines the relationship of greenness to both AD and non-AD dementia in a population-based sample of Medicare beneficiaries. Methods: Participants were 249,405 US Medicare beneficiaries aged >  65 living in Miami-Dade County, FL, from 2010 to 2011. Multi-level analyses examined the relationship of greenness, assessed by mean Census block level Normalized Difference Vegetation Index (NDVI), to odds of each of AD, Alzheimer’s disease and related dementias (ADRD), and non-AD dementia, respectively. Covariates included age, gender, race/ethnicity, number of comorbid health conditions, and neighborhood income. Results: Higher greenness was associated with reduced risk of AD, ADRD, and non-AD dementia, respectively, adjusting for individual and neighborhood sociodemographics. Compared to the lowest greenness tertile, the highest greenness tertile was associated with reduced odds of AD by 20%(odds ratio, 0.80; 95%CI, 0.75–0.85), ADRD by 18%(odds ratio, 0.82; 95%CI, 0.77–0.86), and non-AD dementia by 11%(odds ratio, 0.89; 95%CI, 0.82–0.96). After further adjusting for number of comorbidities, compared to the lowest greenness tertile, the highest greenness tertile was associated with reduced odds of AD (OR, 0.94; 95%CI, 0.88–1.00) and ADRD (OR, 0.93; 95%CI, 0.88–0.99), but not non-AD dementia (OR, 1.01; 95%CI, 0.93–1.08). Conclusion: High neighborhood greenness may be associated with lower odds of AD and ADRD. Environmental improvements, such as increasing neighborhood vegetation, may be a strategy to reduce risk for AD and possibly other dementias.

Keterkaitan parameter nilai pH, C-organik, N-Total, C/N dan alofan pada beberapa Andisols di Jawa Barat

SoilREns ◽  
2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Rina Devnita ◽  
Mahfud Arifin ◽  
Ridha Hudaya ◽  
Ade Setiawan ◽  
Apong Sandrawati
Keyword(s):  
Organic Carbon ◽  
Carbon Content ◽  
Total Nitrogen ◽  
Soil Analysis ◽  
Volcanic Eruptions ◽  
Soil Parameters ◽  
Organic Carbon Content ◽  
Ph Values ◽  
Relationship Of ◽  
The Relationship

The correlation of chemical parameters and soil mineralogy one to another in Andisols were interesting to be studied, to increase the understanding of soil reactions, nutrient availability and soil mineral content. Andisols from three locations and derived from three different volcanic eruptions namely G. Tangkuban Parahu, G. Patuha and G. Tilu, with andesite, andesite-basalt and basalt parent materials respectively, were examined the correlation of several soil parameters. The values of pH, organic carbon, total nitrogen, C/N and allophane content were obtained from the soil analysis of every horizon of the soil profiles at each site. Correlation analyses were used to see the relationship of the parameters. The results showed a negative correlation between pH and organic carbon (r = -590 *). The soil pH values were positively correlated with the amount of allophane (r = 0.687 *). The pH values were correlated positively with imogolite content (r = 0.356 *). The pH values were negatively correlated with organic carbon (r = -0.590 *). The organic carbon content was negatively correlated with depth (r = - 0.582 *). The organic carbon content was negatively correlated with allophane (r = 0.707 *). Total nitrogen values were negatively correlated with increasing depth (r = -0.531 *).Keywords: Mt. Tangkuban Parahu, Mt. Patuha, Mt. Tilu, andesit, andesit-basalan, alophane

Association Analysis of NDVI Changes and Topographic Factors

2013 ◽  
Vol 333-335 ◽  
pp. 1205-1208
Author(s):  
De Li Liu ◽  
Ya Shuang Zhang ◽  
Nan Lin
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Topographic Factors ◽  
Gis Software ◽  
Relationship Of ◽  
The Relationship ◽  
Slope Direction

Based on the TM remote sensing data of the Huadian city in 1991 and 2011 and based on the DEM data,using the normalized difference vegetation index (NDVI) change classification method,to Extraction the elevation,slope,slope direction data and the vegetation index data of the study area.Then using the spatial analysis function of GIS software to overlay the two different period NDVI data and analysis the NDVI change of area and spatial. Using the same method to overlay and analysis the relationship of NDVI data and elevation,slope,slope direction.Research shows that the variation of NDVI in the study area has relationship with the topographic factors change.

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

scholarly journals The Effect of Surrounding Greenness on Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort in Taiwan

2020 ◽  
Vol 18 (1) ◽  
pp. 267
Author(s):  
Hui-Ju Tsai ◽  
Chia-Ying Li ◽  
Wen-Chi Pan ◽  
Tsung-Chieh Yao ◽  
Huey-Jen Su ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Based ◽  
Research Database ◽  
Individual Level ◽  
The Relationship

This study determines whether surrounding greenness is associated with the incidence of type 2 diabetes Mellitus (T2DM) in Taiwan. A retrospective cohort study determines the relationship between surrounding greenness and the incidence of T2DM during the study period of 2001–2012 using data from the National Health Insurance Research Database. The satellite-derived normalized difference vegetation index (NDVI) from the global MODIS database in the NASA Earth Observing System is used to assess greenness. Cox proportional hazard models are used to determine the relationship between exposure to surrounding greenness and the incidence of T2DM, with adjustment for potential confounders. A total of 429,504 subjects, including 40,479 subjects who developed T2DM, were identified during the study period. There is an inverse relationship between exposure to surrounding greenness and the incidence of T2DM after adjustment for individual-level covariates, comorbidities, and the region-level covariates (adjusted HR = 0.81, 95% CI: 0.79–0.82). For the general population of Taiwan, greater exposure to surrounding greenness is associated with a lower incidence of T2DM.

scholarly journals Modeling the Radial Stem Growth of the Pine (Pinus sylvestris L.) Forests Using the Satellite-Derived NDVI and LST (MODIS/AQUA) Data

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Yulia Ivanova ◽  
Anton Kovalev ◽  
Vlad Soukhovolsky
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Stem Growth ◽  
Forest Growth ◽  
Parabolic Approximation ◽  
New Approach ◽  
The Relationship ◽  
Tree Increment

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.

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