scholarly journals Normalized Difference Vegetation Index as a Tool for Wheat Crop Coefficient and Evapotranspiration Estimation: A case study of Nankana Sahib District Pakistan

2019 ◽  
Vol 3 (10) ◽  
pp. 32-39
Author(s):  
Qais Yameen ◽  
Muhammad Farhan Arshad ◽  
Muhammad Saqlain
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Coefficient ◽  
Wheat Crop ◽  
Evapotranspiration Estimation

scholarly journals Estimation of wheat crop evapotranspiration using NDVI vegetation index

2016 ◽  
Vol 8 (1) ◽  
pp. 159-166 ◽  
Author(s):  
Sirisha Adamala ◽  
Yogesh Anand Rajwade ◽  
Y.V. Krishna Reddy
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Winter Season ◽  
Estimation Method ◽  
Crop Coefficient ◽  
Wheat Crop ◽  
Command Area ◽  
Crop Evapotranspiration ◽  
Landsat Images ◽  
Air Temperatures

The evapotranspiration of the wheat crop grown in Tarafeni South Main Canal (TSMC) irrigation command area of West Bengal, India was estimated based on Normalized Difference Vegetation Index (NDVI) from LANDSAT images. The crop evapotranspiration (ETc) of wheat crop was estimated using the crop coefficient (Kc) maps and the reference evapotranspiration (ETo) in the TSMC irrigation command area. The ETo was estimated from the well known temperature based ETo estimation method, i.e. FAO-24 modified Blaney-Criddle method using measured maximum and minimum air temperatures data during January 2011 in the command area. The Kc maps were mapped in ARC GIS software using procured LANDSAT images for the study period. The area under wheat crop was clipped from land use/land cover map generated from LANDSAT image of January, 2011 for winter season. Further, the crop evapotranspiration map was obtained by multiplying Kc map with the estimated ETo value i.e., 5.76 mm/day for a particular day. The maximum crop evapotranspiration computed for Rabi crop was 5.57 mm/ day, whereas minimum was 1.59 mm/day for the TSMC command area.

scholarly journals Association between Green Space Structure and the Prevalence of Asthma: A Case Study of Toronto

2021 ◽  
Vol 18 (11) ◽  
pp. 5852
Author(s):  
Yuping Dong ◽  
Helin Liu ◽  
Tianming Zheng
Keyword(s):  
Air Pollution ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Chronic Inflammatory Disease ◽  
Space Structure ◽  
Tree Diversity ◽  
Underlying Mechanisms ◽  
Index Tree

Asthma is a chronic inflammatory disease that can be caused by various factors, such as asthma-related genes, lifestyle, and air pollution, and it can result in adverse impacts on asthmatics’ mental health and quality of life. Hence, asthma issues have been widely studied, mainly from demographic, socioeconomic, and genetic perspectives. Although it is becoming increasingly clear that asthma is likely influenced by green spaces, the underlying mechanisms are still unclear and inconsistent. Moreover, green space influences the prevalence of asthma concurrently in multiple ways, but most existing studies have explored only one pathway or a partial pathway, rather than the multi-pathways. Compared to greenness (measured by Normalized Difference Vegetation Index, tree density, etc.), green space structure—which has the potential to impact the concentration of air pollution and microbial diversity—is still less investigated in studies on the influence of green space on asthma. Given this research gap, this research took Toronto, Canada, as a case study to explore the two pathways between green space structure and the prevalence of asthma based on controlling the related covariates. Using regression analysis, it was found that green space structure can protect those aged 0–19 years from a high risk of developing asthma, and this direct protective effect can be enhanced by high tree diversity. For adults, green space structure does not influence the prevalence of asthma unless moderated by tree diversity (a measurement of the richness and diversity of trees). However, this impact was not found in adult females. Moreover, the hypothesis that green space structure influences the prevalence of asthma by reducing air pollution was not confirmed in this study, which can be attributed to a variety of causes.

scholarly journals A Case Study about the Use of Precision Agriculture Technology Applied to a Zn Biofortification Workflow for Grapevine Vitis vinifera cv Moscatel

2021 ◽  
Vol 3 (1) ◽  
pp. 2
Author(s):  
Diana Daccak ◽  
Inês Carmo Luís ◽  
Ana Coelho Marques ◽  
Ana Rita F. Coelho ◽  
Cláudia Campos Pessoa ◽  
...  
Keyword(s):  
Vitis Vinifera ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Foliar Application ◽  
Fold Increase ◽  
Production Cycle ◽  
Smart Farming ◽  
Reduced Surface

As the human population is growing worldwide, the food demand is sharply increasing. Following this assumption, strategies to enhance the food production are being explored, namely, smart farming, for monitoring crops during the production cycle. In this study, a vineyard of Vitis vinifera cv. Moscatel located in Palmela (N 38°35′47.113′′ O 8°40′46.651) was submitted to a Zn biofortification workflow, through foliar application of zinc oxide (ZnO) or zinc sulfate (ZnSO4) (at a concentration of 60% and 90%—900 g·ha−1 and 1350 g·ha−1, respectively). The field morphology and vigor of the vineyard was performed through Unmanned Aerial Vehicles (UAVs) images (assessed with altimetric measurement sensors), synchronized by GPS. Drainage capacity and slopes showed one-third of the field with reduced surface drainage and a maximum variation of 0.80 m between the extremes (almost flat), respectively. The NDVI (Normalized Difference Vegetation Index) values reflected a greater vigor in treated grapes with treatment SZn90 showing a higher value. These data were interpolated with mineral content, monitored with atomic absorption analysis (showing a 1.3-fold increase for the biofortification index). It was concluded that the used technologies furnishes specific target information in real time about the crops production.

scholarly journals Spatio-temporal variability of biophysical parameters of irrigated maize using orbital remote sensing

2021 ◽  
Vol 42 (4) ◽  
pp. 2181-2202
Author(s):  
Taiara Souza Costa ◽  
◽  
Robson Argolo dos Santos ◽  
Rosângela Leal Santos ◽  
Roberto Filgueiras ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Coefficient ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Biophysical Parameters ◽  
Planting Dates ◽  
Maize Crop ◽  
Spatio Temporal

This study proposes to estimate the actual crop evapotranspiration, using the SAFER model, as well as calculate the crop coefficient (Kc) as a function of the normalized difference vegetation index (NDVI) and determine the biomass of an irrigated maize crop using images from the Operational Land Imager (OLI) and Thermal Infrared (TIRS) sensors of the Landsat-8 satellite. Pivots 21 to 26 of a commercial farm located in the municipalities of Bom Jesus da Lapa and Serra do Ramalho, west of Bahia State, Brazil, were selected. Sowing dates for each pivot were arranged as North and South or East and West, with cultivation starting firstly in one of the orientations and subsequently in the other. The relationship between NDVI and the Kc values obtained in the FAO-56 report (KcFAO) revealed a high coefficient of determination (R2 = 0.7921), showing that the variance of KcFAO can be explained by NDVI in the maize crop. Considering the center pivots with different planting dates, the crop evapotranspiration (ETc) pixel values ranged from 0.0 to 6.0 mm d-1 during the phenological cycle. The highest values were found at 199 days of the year (DOY), corresponding to around 100 days after sowing (DAS). The lowest BIO values occur at 135 DOY, at around 20 DAS. There is a relationship between ETc and BIO, where the DOY with the highest BIO are equivalent to the days with the highest ETc values. In addition to this relationship, BIO is strongly influenced by soil water availability.

scholarly journals Assessing water demand with remote sensing for two coriander varieties

2018 ◽  
Vol 36 (3) ◽  
pp. 266-273
Author(s):  
Euseppe Ortiz ◽  
Enrique A. Torres
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Demand ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Digital Camera ◽  
Crop Coefficient ◽  
Remote Sensors ◽  
The Relationship ◽  
Important Basis

The use of remote sensing to determine water needs has been successfully applied by several authors to different crops, maintaining, as an important basis, the relationship between the normalized difference vegetation index (NDVI) and biophysical variables, such as the fraction of coverage (fc) and the basal crop coefficient (Kcb). Therefore, this study quantified the water needs of two varieties of coriander (UNAPAL Laurena CL and UNAPAL Precoso CP) based on the response of fc and Kcb, using remote sensors and a water balance according to the FAO-56 methodology. A Campbell Scientific meteorological station, a commercial digital camera and a portable spectro radiometer were used to obtain information on the environmental conditions and the crop. By means of remote sensing associated with a water balance, it was found that the water demand was 156 mm for CL and 151 mm for CP until the foliage harvest (41 d after sowing); additionally, the initial Kcb was 0.14, the mean Kcb was 1.16 (approximately) and the final Kcb was 0.71 (approximately).

scholarly journals Sugarcane spatial-temporal monitoring and crop coefficient estimation through NDVI

2019 ◽  
Vol 23 (5) ◽  
pp. 330-335 ◽  
Author(s):  
Angelo B. Alface ◽  
Silvio B. Pereira ◽  
Roberto Filgueiras ◽  
Fernando F. Cunha
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Irrigated Agriculture ◽  
Sugarcane Crop ◽  
Coefficient Estimation ◽  
Sentinel 2A ◽  
The Relationship

ABSTRACT The use of satellite images as a complement in irrigation management constitutes a primordial basis in the decision-making process for irrigated agriculture. In this context, the present study aimed to monitor through Normalized Difference Vegetation Index (NDVI) an irrigated sugarcane field belonging to the Mafambisse company, located at the District of Nhamatanda/Sofala, Republic of Mozambique, and establish its relationship with the crop coefficient established by FAO (kcFAO) and fit a regression model to estimate crop coefficient (kc) from the relationship between NDVI and kcFAO. The study was conducted using a series of Sentinel-2A/MSI images, relative to the period from October 2016 to October 2017. Based on the NDVI images generated, it was possible to monitor the sugarcane crop in the field and analyse the sensitivity of the index to its vegetative vigor. A similar pattern was observed between kcFAO profiles and NDVI values, which allowed the adjustment to be performed, demonstrating that this index is an alternative to obtain the crop coefficient.

scholarly journals Estimation of Crop Water Deficit in Lower Bari Doab, Pakistan Using Reflection-Based Crop Coefficient

2020 ◽  
Vol 9 (3) ◽  
pp. 173
Author(s):  
Muhammad Asif Javed ◽  
Sajid Rashid Ahmad ◽  
Wakas Karim Awan ◽  
Bilal Ahmed Munir
Keyword(s):  
Water Deficit ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Coefficient ◽  
Maximum Temperature ◽  
Filter Method ◽  
Command Area ◽  
Landsat 8 ◽  
Crop Water ◽  
Crop Coefficients

There is a global realization in all governmental setups of the need to provoke the efficient appraisal of crop water budgeting in order to manage water resources efficiently. This study aims to use the satellite remote sensing techniques to determine the water deficit in the crop rich Lower Bari Doab Canal (LBDC) command area. Crop classification was performed using multi-temporal NDVI profiles of Landsat-8 imagery by distinguishing the crop cycles based on reflectance curves. The reflectance-based crop coefficients (Kc) were derived by linear regression between normalized difference vegetation index (NDVI) cycles of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and MYD13Q1 products and Food and Agriculture Organization (FAO) defined crop coefficients. A MODIS 250 m NDVI product of the last 10 years (2004-2013) was used to identify the best performing crop cycle using Fourier filter method. The meteorological parameters including rainfall and temperature substantiated the reference evapotranspiration (ET0) calculated using the Hargreaves method. The difference of potential ET and actual ET, derived from the reflectance-based Kc calculated using reference NDVI and current NDVI, generates the water deficit. Results depict the strong correlation between ET, temperature and rainfall, as the regions having maximum temperature resulted in high ET and low rainfall and vice versa. The derived Kc values were observed to be accurate when compared with the crop calendar. Results revealed maximum water deficit at middle stage of the crops, which were observed to be particularly higher at the tail of the canal command. Moreover, results also depicted that kharif (summer) crops suffer higher deficit in comparison to rabi (winter) crops due to higher ET demand caused by higher temperature. Results of the research can be utilized for rational allocation of canal supplies and guiding farmers towards usage of alternate sources to avoid crop water stress.

scholarly journals Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1364 ◽  
Author(s):  
Spiliotopoulos ◽  
Loukas
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Meteorological Data ◽  
Linear Regression Analysis ◽  
Atmospheric Correction ◽  
Crop Coefficient ◽  
Experimental Period ◽  
Spectral Measurements ◽  
Image File ◽  
Crop Coefficients

The objective of the current study was the investigation of specific relationships between crop coefficients and vegetation indices (VI) computed at the water-limited environment of Lake Karla Watershed, Thessaly, in central Greece. A Mapping ET (evapotranspiration) at high Resolution and with Internalized Calibration (METRIC) model was used to derive crop coefficient values during the growing season of 2012. The proposed methodology was developed using medium resolution Landsat 7 ETM+ images and meteorological data from a local weather station. Cotton, sugar beets, and corn fields were utilized. During the same period, spectral signatures were obtained for each crop using the field spectroradiometer GER1500 (Spectra Vista Corporation, NY, U.S.A.). Relative spectral responses (RSR) were used for the filtering of the specific reflectance values giving the opportunity to match the spectral measurements with Landsat ETM+ bands. Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Enhanced Vegetation Index 2 (EVI2) were then computed, and empirical relationships were derived using linear regression analysis. NDVI, SAVI, and EVI2 were tested separately for each crop. The resulting equations explained those relationships with a very high R2 value (>0.86). These relationships have been validated against independent data. Validation using a new image file after the experimental period gives promising results, since the modeled image file is similar in appearance to the initial one, especially when a crop mask is applied. The CROPWAT model supports those results when using the new crop coefficients to estimate the related crop water requirements. The main benefit of the new approach is that the derived relationships are better adjusted to the crops. The described approach is also less time-consuming because there is no need for atmospheric correction when working with ground spectral measurements.

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