Estimating forage crop production: a technique adaptable to remote sensing

1978 ◽  
Vol 7 (1) ◽  
pp. 77-80 ◽  
Author(s):  
Robert J. Reginato ◽  
Sherwood B. Idso ◽  
Ray D. Jackson
2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.


Soil Research ◽  
2017 ◽  
Vol 55 (8) ◽  
pp. 778
Author(s):  
G. S. A. Castro ◽  
C. A. C. Crusciol ◽  
C. A. Rosolem ◽  
J. C. Calonego ◽  
K. R. Brye

This work aimed to evaluate the effects of crop rotations and soil acidity amelioration on soil physical properties of an Oxisol (Rhodic Ferralsol or Red Ferrosol in the Australian Soil Classification) from October 2006 to September 2011 in Botucatu, SP, Brazil. Treatments consisted of four soybean (Glycine max)–maize (Zea mays)–rice (Oryza sativa) rotations that differed in their off-season crop, either a signal grass (Urochloa ruziziensis) forage crop, a second crop, a cover crop, or fallow. Two acid-neutralising materials, dolomitic lime (effective calcium carbonate equivalent (ECCE) = 90%) and calcium-magnesium silicate (ECCE = 80%), were surface applied to raise the soil’s base saturation to 70%. Selected soil physical characteristics were evaluated at three depths (0–0.1, 0.1–0.2, and 0.2–0.4 m). In the top 0.1 m, soil bulk density was lowest (P < 0.05) and macroporosity and aggregate stability index were greatest (P < 0.05) in the forage crop compared with all other production systems. Also, bulk density was lower (P < 0.05) and macroporosity was greater (P < 0.05) in the acid-neutralising-amended than the unamended control soil. In the 0.1–0.2-m interval, mean weight diameter and mean geometric diameter were greater (P < 0.05) in the forage crop compared with all other production systems. All soil properties evaluated in this study in the 0.2–0.4-m interval were unaffected by production system or soil amendment after five complete cropping cycles. Results of this study demonstrated that certain soil physical properties can be improved in a no-tillage soybean–maize–rice rotation using a forage crop in the off-season and with the addition of acid-neutralising soil amendments. Any soil and crop management practices that improve soil physical properties will likely contribute to sustaining long-term soil and crop productivity in areas with highly weathered, organic matter-depleted, acidic Oxisols.


2007 ◽  
Vol 6 (sup2) ◽  
pp. 1226-1229 ◽  
Author(s):  
P. Martiniello ◽  
G. Gesualdo ◽  
E. Sabia ◽  
G.M. Terzano ◽  
C. Pacelli ◽  
...  
Keyword(s):  

2020 ◽  
Vol 175 ◽  
pp. 01004
Author(s):  
Sergey Garkusha ◽  
Mikhail Skazhennik ◽  
Evgeny Kiselev ◽  
Vitaliy Chizhikov ◽  
Alexey Petrushin

The concept of digitalization of agricultural production in the Russian Federation provides for the implementation of measures to develop and create a system of geographic information monitoring and decision support in crop production. The aim of the research was to conduct geoinformation monitoring of rice crops to develop methods for automated mapping of their condition and yield forecasting. The studies were carried out on a test site of the Federal State Budgetary Scientific Institution “Federal Scientific Rice Centre” with an area of 274 hectares. The survey was performed by a quadcopter with a MicaSense RedEdge-M multispectral camera mounted on a fixed suspension. The shooting period using an unmanned aerial vehicle (UAV) was limited to early June and additionally used the Sentinel-2A satellite. To assess the state of rice crops, the normalized relative vegetative index NDVI was used. Based on the NDVI distribution and yield information from the combine TUCANO 580 (CLAAS), a statistical analysis was carried out in fields 7 and 9. Testing of the experimental methodology for monitoring crops in 2019 on the basis of remote sensing of test plots and geoinformation modeling and the statistical apparatus should be considered satisfactory.


2020 ◽  
Vol 12 (18) ◽  
pp. 2949
Author(s):  
Megan Blatchford ◽  
Chris M. Mannaerts ◽  
Yijian Zeng ◽  
Hamideh Nouri ◽  
Poolad Karimi

This paper analyses the effect of the spatial assessment scale on irrigation performance indicators in small and medium-scale agriculture. Three performance indicators—adequacy (i.e., sufficiency of water use to meet the crop water requirement), equity (i.e., fairness of irrigation distribution), and productivity (i.e., unit of physical crop production/yield per unit water consumption)—are evaluated in five irrigation schemes for three spatial resolutions—250 m, 100 m, and 30 m. Each scheme has varying plot sizes and distributions, with average plot sizes ranging from 0.2 ha to 13 ha. The datasets are derived from the United Nations Food and Agricultural Organization (FAO) water productivity through open access of remotely sensed–derived data (the Water Productivity Open Access Portal—WaPOR) database. Irrigation indicators performed differently in different aspects; for adequacy, all three resolutions show similar spatial trends for relative evapotranspiration (ET) across levels for all years. However, the estimation of relative ET is often higher at higher resolution. In terms of equity, all resolutions show similar inter-annual trends in the coefficient of variation (CV); higher resolutions usually have a higher CV of the annual evapotranspiration and interception (ETIa) while capturing more spatial variability. For productivity, higher resolutions show lower crop water productivity (CWP) due to higher aboveground biomass productivity (AGBP) estimations in lower resolutions; they always have a higher CV of CWP. We find all resolutions of 250 m, 100 m, and 30 m suitable for inter-annual and inter-scheme assessments regardless of plot size. While each resolution shows consistent temporal trends, the magnitude of the trend in both space and time is smoothed by the 100 m and 250 m resolution datasets. This frequently results in substantial differences in the irrigation performance assessment criteria for inter-plot comparisons; therefore, 250 m and 100 m are not recommended for inter-plot comparison for all plot sizes, particularly small plots (<2 ha). Our findings highlight the importance of selecting the spatial resolution appropriate to scheme characteristics when undertaking irrigation performance assessment using remote sensing.


2020 ◽  
Vol 289 ◽  
pp. 106733 ◽  
Author(s):  
Wei Hu ◽  
Mike Beare ◽  
Craig Tregurtha ◽  
Richard Gillespie ◽  
Kathryn Lehto ◽  
...  

2020 ◽  
Vol 12 (24) ◽  
pp. 4030
Author(s):  
Gohar Ghazaryan ◽  
Simon König ◽  
Ehsan Eyshi Rezaei ◽  
Stefan Siebert ◽  
Olena Dubovyk

Drought is one of the extreme climatic events that has a severe impact on crop production and food supply. Our main goal is to test the suitability of remote sensing-based indices to detect drought impacts on crop production from a global to regional scale. Moderate resolution imaging spectroradiometer (MODIS) based imagery, spanning from 2001 to 2017 was used for this task. This includes the normalized difference vegetation index (NDVI), land surface temperature (LST), and the evaporative stress index (ESI), which is based on the ratio of actual to potential evapotranspiration. These indices were used as indicators of drought-induced vegetation conditions for three main crops: maize, wheat, and soybean. The start and end of the growing season, as observed at 500 m resolution, were used to exclude the time steps that are outside of the growing season. Based on the three indicators, monthly standardized anomalies were estimated, which were used for both analyses of spatiotemporal patterns of drought and the relationship with yield anomalies. Anomalies in the ESI had higher correlations with maize and wheat yield anomalies than other indices, indicating that prolonged periods of low ESI during the growing season are highly correlated with reduced crop yields. All indices could identify past drought events, such as the drought in the USA in 2012, Eastern Africa in 2016–2017, and South Africa in 2015–2016. The results of this study highlight the potential of the use of moderate resolution remote sensing-based indicators combined with phenometrics for drought-induced crop impact monitoring. For several regions, droughts identified using the ESI and LST were more intense than the NDVI-based results. We showed that these indices are relevant for agricultural drought monitoring at both global and regional scales. They can be integrated into drought early warning systems, process-based crop models, as well as can be used for risk assessment and included in advanced decision-support frameworks.


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