scholarly journals Spatially Weighted Estimation of Broadacre Crop Growth Improves Gap-Filling of Landsat NDVI

2021 ◽  
Vol 13 (11) ◽  
pp. 2128
Author(s):  
Fiona H. Evans ◽  
Jianxiu Shen
Keyword(s):  
Growth Curve ◽  
Cropping Systems ◽  
Crop Growth ◽  
Growth And Yield ◽  
Landsat 8 ◽  
Gap Filling ◽  
Landsat Images ◽  
Curve Estimation ◽  
Spatial Weights ◽  
Weighted Estimation

Seasonal climate is the main driver of crop growth and yield in broadacre grain cropping systems. With a 40-year record of 30 m resolution images and 16-day revisits, the Landsat satellite series is ideal for producing long-term records of remotely sensed phenology to build understanding of how climate affects crop growth. However, the time-series of Landsat images exhibits gaps caused by cloud cover, which is common in wet periods when crops reach maximum growth. We propose a novel spatial–temporal approach to gap-filling that avoids data fusion. Crop growth curve estimation is used to perform temporal smoothing and incorporation of spatial weights allows spatial smoothing. We tested our approach using Landsat NDVI data acquired for an 8000 ha study area in Western Australia using a train/test approach where 157 available Landsat-7 images between 2013 and 2019 were used to train the model, and 95 at least 80% cloud-free Landsat-8 images from the same period were used to test its performance. We found that compared to nonspatial estimation, use of spatial weights in growth curve estimation improved correlation between observed and predicted NDVI by 75%, MAE by 31% and RMSE by 75%. For cropland, the correlation is improved by 58%, the MAE by 36% and the RMSE by 76%. We conclude that spatially weighted estimation of crop growth curves can be used to fill spatial and temporal gaps in Landsat NDVI for the purpose of within-field monitoring. Our approach is also applicable to other data sources and vegetation indices.

scholarly journals To Blend or Not to Blend? A Framework for Nationwide Landsat–MODIS Data Selection for Crop Yield Prediction

2020 ◽  
Vol 12 (10) ◽  
pp. 1653
Author(s):  
Yang Chen ◽  
Tim R. McVicar ◽  
Randall J. Donohue ◽  
Nikhil Garg ◽  
François Waldner ◽  
...  
Keyword(s):  
Crop Yield ◽  
Temporal Frequency ◽  
Management Strategies ◽  
Crop Growth ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Landsat Images ◽  
Yield Model ◽  
Pixel Resolution ◽  
Country Level

The onus for monitoring crop growth from space is its ability to be applied anytime and anywhere, to produce crop yield estimates that are consistent at both the subfield scale for farming management strategies and the country level for national crop yield assessment. Historically, the requirements for satellites to successfully monitor crop growth and yield differed depending on the extent of the area being monitored. Diverging imaging capabilities can be reconciled by blending images from high-temporal-frequency (HTF) and high-spatial-resolution (HSR) sensors to produce images that possess both HTF and HSR characteristics across large areas. We evaluated the relative performance of Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat, and blended imagery for crop yield estimates (2009–2015) using a carbon-turnover yield model deployed across the Australian cropping area. Based on the fraction of missing Landsat observations, we further developed a parsimonious framework to inform when and where blending is beneficial for nationwide crop yield prediction at a finer scale (i.e., the 25-m pixel resolution). Landsat provided the best yield predictions when no observations were missing, which occurred in 17% of the cropping area of Australia. Blending was preferred when <42% of Landsat observations were missing, which occurred in 33% of the cropping area of Australia. MODIS produced a lower prediction error when ≥42% of the Landsat images were missing (~50% of the cropping area). By identifying when and where blending outperforms predictions from either Landsat or MODIS, the proposed framework enables more accurate monitoring of biophysical processes and yields, while keeping computational costs low.

scholarly journals Potato Growth and Yield Characteristics under Different Cropping System Management Strategies in Northeastern U.S.

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 165
Author(s):  
Robert P. Larkin ◽  
C. Wayne Honeycutt ◽  
Timothy S. Griffin ◽  
O. Modesto Olanya ◽  
Zhongqi He
Keyword(s):  
Cover Crops ◽  
Management Practices ◽  
Cropping Systems ◽  
Potato Crop ◽  
Organic Amendments ◽  
Cropping System ◽  
Crop Growth ◽  
Disease Suppression ◽  
Growth And Yield ◽  
Green Manures

Cropping systems and management practices that improve soil health may greatly enhance crop productivity. Four different potato cropping systems designed to address specific management goals of soil conservation (SC), soil improvement (SI), disease suppression (DS), and a status quo (SQ) standard rotation, along with a non-rotation (PP) control, were evaluated for their effects on potato crop growth, nutrient, and yield characteristics under both irrigated and non-irrigated (rainfed) conditions in field trials in Maine, USA, from 2004 to 2010. Both cropping system and irrigation significantly (p < 0.05) affected most potato crop parameters associated with growth and yield. All rotations increased tuber yield relative to the non-rotation PP control, and the SI system, which included yearly compost amendments, resulted in overall higher yields and a higher percentage of large-size tubers than all other systems with no irrigation (increases of 14 to 90%). DS, which contained disease-suppressive green manures and cover crops, produced the highest yields overall under irrigation (increases of 11 to 35%). Irrigation increased tuber yields in all cropping systems except SI (average increase of 27–37%). SI also resulted in significant increases in leaf area duration and chlorophyll content (as indicators of photosynthetic potential) and root and shoot biomass relative to other cropping systems, particularly under non-irrigated conditions. SI also resulted in higher shoot and tuber tissue concentrations of N, P, and K, but not most micronutrients. Overall, cropping systems that incorporate management practices such as increased rotation length and the use of cover crops, green manures, reduced tillage, and particularly, organic amendments, can substantially improve potato crop growth and yield. Irrigation also substantially increased growth and yield under normal field conditions in Maine, but SI, with its large organic amendments, was essentially a substitute for irrigation, producing comparable results without irrigation.

Effects of rundown in soil hydraulic condition on crop productivity in south-eastern Queensland - a simulation study

Soil Research ◽  
2001 ◽  
Vol 39 (5) ◽  
pp. 1111 ◽  
Author(s):  
R. D. Connolly ◽  
D. M. Freebairn ◽  
M. J. Bell ◽  
G. Thomas
Keyword(s):  
Organic Matter ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Crop Growth ◽  
Growth And Yield ◽  
Gross Margin ◽  
South Eastern ◽  
The Past ◽  
Hydraulic Condition ◽  
Soil Hydraulic

Declining soil organic matter levels because of cropping have been shown to reduce crop growth and yield, but the effects of changing infiltration and soil hydraulic properties on crop productivity have not been widely evaluated. Cropping systems in south-eastern Queensland have, in the past, involved intense tillage, trafficking with heavy machinery, and changed organic matter cycling, affecting soil aggregation, permeability, water-holding characteristics, and organic matter. The aim of this paper is to determine how important infiltration and soil hydraulic condition has been to the water balance, crop growth, and yield in the past, and may be in the future if management is not changed. Change in physical and chemical condition of the 5 most commonly cropped soils in south-east Queensland (Sodosols, Vertosols with ≤55% clay, Vertosols with >55% clay, Red Ferrosols and Red Chromosols/Kandosols) was measured over 0–70 years of cropping and estimated up to 200 years. The APSIM model was used to predict effects of changing soil condition in a rain-fed, fertilised, wheat-summer fallow cropping system with intense tillage. Decline in infiltration, restricted internal redistribution of water, and increased evaporation reduced water supply to the crop, causing simulated yield to decline by 29, 38, 25, 17, and 13% for the 5 soils, respectively, after 50 years of cropping. Gross margin declined at a faster rate, falling by 36, 50, 40, 20, and 21%, respectively after 50 years because of increasing fertiliser requirement to compensate for declining soil fertility. Crop productivity on most soils continued to steadily decline as period of cropping increased to 200 years. To arrest or reverse this downward trend, it is likely that substantial changes to current cropping systems will be needed, including reducing tillage and trafficking, and improving organic matter levels.

Book review

2003 ◽  
Vol 51 (3) ◽  
pp. 369
Author(s):  
Z. Berzsenyi
Keyword(s):  
New York ◽  
Mathematical Models ◽  
Crop Growth ◽  
Growth And Yield ◽  
Madison Avenue

A. R. Overman and R. V. Scholtz III.: Mathematical Models of Crop Growth and Yield. Marcel Dekker, 270 Madison Avenue, New York, NY 10016. 2002. Hardcover, 344 pp., 150.00. ISBN 0-8247-0825-3.

scholarly journals Modeling the Impact of Atmospheric Warming on Staple Crop Growth in China in the 1960s and 2000s

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 36
Author(s):  
Qing Zhang ◽  
Wen Zhang ◽  
Yongqiang Yu ◽  
Tingting Li ◽  
Lijun Yu
Keyword(s):  
Winter Wheat ◽  
Climate Warming ◽  
Northeast China ◽  
Cropping Systems ◽  
Crop Growth ◽  
East China ◽  
Frequency Distributions ◽  
Before And After ◽  
The 1960S ◽  
The Impact

Responses of crop growth to climate warming are fundamental to future food security. The response of crops to climate change may be subtly different at their growing stages. Close insights into the differentiated stage-dependent responses of crops are significantly important in making adaptive adjustments of crops’ phenological optimization and cultivar improvement in diverse cropping systems. Using the Agro-C model, we studied the influence of past climate warming on crops in typical cropping systems in China. The results showed that while the temperature had increased distinctly from the 1960s to 2000s, the temperature frequency distributions in the growth season of crops moved to the high-temperature direction. The low temperature days during the crop growth periods that suppress crop growth decreased in the winter wheat area in North and East China, rice and maize areas in Northeast China, and the optimum temperature days increased significantly. As a result, the above ground biomass (AGB) of rice and maize in Northeast China and winter wheat in North and East China increased distinctly, while that of rice in South China had no significant change. A comparison of the key growth periods before and after heading (silking) showed that the warming before heading (silking) made a great contribution to the increase in the AGB, especially for winter wheat.

scholarly journals A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

2021 ◽  
Vol 13 (15) ◽  
pp. 2869
Author(s):  
MohammadAli Hemati ◽  
Mahdi Hasanlou ◽  
Masoud Mahdianpari ◽  
Fariba Mohammadimanesh
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Policy Development ◽  
Atmospheric Correction ◽  
Open Data ◽  
Detection Methods ◽  
Landsat 8 ◽  
Landsat Images ◽  
Detection Analysis ◽  
The Impact

With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready data (especially those with atmospheric correction), and use of cloud computing platforms, all over increasing large areas. The nature of change methods has evolved from representative bi-temporal pairs to time series of images capturing dynamics and trends, capable of revealing both gradual and abrupt changes. The result also revealed a greater use of nonparametric classifiers for Landsat change detection analysis. Landsat-9, to be launched in September 2021, in combination with the continued operation of Landsat-8 and integration with Sentinel-2, enhances opportunities for improved monitoring of change over increasingly larger areas with greater intra- and interannual frequency.

Estimation of Evapotranspiration using Remote Sensing and Surface Energy Balance Algorithm for Land (SEBAL) in Canal Command

2021 ◽  
Vol 58 (03) ◽  
pp. 274-285
Author(s):  
H. V. Parmar ◽  
N. K. Gontia
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Crop Growth ◽  
Growth Stages ◽  
Landsat 8 ◽  
Surface Temperatures ◽  
Canal Command

Remote sensing based various land surface and bio-physical variables like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), surface albedo, transmittance and surface emissivity are useful for the estimation of spatio-temporal variations in evapotranspiration (ET) using Surface Energy Balance Algorithm for Land (SEBAL) method. These variables were estimated under the present study for Ozat-II canal command in Junagadh district, Gujarat, India, using Landsat-7 and Landsat-8 images of summer season of years 2014 and 2015. The derived parameters were used in SEBAL to estimate the Actual Evapotranspiration (AET) of groundnut and sesame crops. The lower values NDVI observed during initial (March) and end (May) stages of crop growth indicated low vegetation cover during these periods. With full canopy coverage of the crops, higher value of NDVI (0.90) was observed during the mid-crop growth stage. The remote sensing-based LST was lower for agricultural areas and the area near banks of the canal and Ozat River, while higher surface temperatures were observed for rural settlements, road and areas with exposed dry soil. The maximum surface temperatures in the cropland were observed as 311.0 K during March 25, 2014 and 315.8 K during May 31, 2015. The AET of summer groundnut increased from 3.75 to 7.38 mm.day-1, and then decreased to 3.99 mm.day-1 towards the end stage of crop growth. The daily AET of summer sesame ranged from 1.06 to 7.72 mm.day-1 over different crop growth stages. The seasonal AET of groundnut and sesame worked out to 358.19 mm and 346.31 mm, respectively. The estimated AET would be helpful to schedule irrigation in the large canal command.

Growth and yield differences between triazine-tolerant and non-triazine-tolerant cultivars of canola

2002 ◽  
Vol 53 (6) ◽  
pp. 643 ◽  
Author(s):  
M. J. Robertson ◽  
J. F. Holland ◽  
S. Cawley ◽  
T. D. Potter ◽  
W. Burton ◽  
...  
Keyword(s):  
Harvest Index ◽  
Growth Analysis ◽  
Oil Content ◽  
Cropping Systems ◽  
Growth And Yield ◽  
Physiological Basis ◽  
Use Efficiency ◽  
The Difference ◽  
Radiation Extinction ◽  
Radiation Use

Canola tolerant to the triazine group of herbicides is grown widely in Australian broad-acre cropping systems. Triazine-tolerant (TT) cultivars are known to have a yield and oil content penalty compared with non-TT cultivars. This study was designed to elucidate the crop physiological basis for the yield differences between the two types. Two commercial cultivars, near-isogenic for the TT trait, were compared in a detailed growth analysis in the field, and 22 crops were compared for phenology and crop attributes at maturity. In the growth analysis study, the TT trait was found to lower radiation use efficiency, which carried through to less biomass at maturity. There were minimal effects on leaf area development and harvest index, and no effect on canopy radiation extinction. Across the 22 crops, where yield varied from 240 to 3400 kg/ha in the non-TT cultivar, yield was on average 26% less in the TT cultivar due to less biomass produced, as there was no significant effect on harvest index. The difference in oil content (2-5%) was greater in low oil content environments. Flowering was delayed by 2-10 days with a greater delay being in later flowering environments. Quantification of the physiological attributes of TT canola allows the assessment of the productivity of different cultivar types across environments.

Growth and Yield of Flax (Linum usitatissimum) Injured by Trifluralin

Weed Science ◽  
1992 ◽  
Vol 40 (3) ◽  
pp. 460-464
Author(s):  
Ken M. Nawolsky ◽  
Ian N. Morrison ◽  
George M. Marshall ◽  
Allen E. Smith
Keyword(s):  
Stem Elongation ◽  
Crop Growth ◽  
Growth And Yield ◽  
Flax Seed ◽  
Growing Seasons ◽  
Matter Production ◽  
Initial Injury ◽  
Net Assimilation ◽  
Bud Initiation ◽  
Number Of Branches

The relationships between the actual amount of spring-applied trifluralin detected in soil at seeding, initial injury to flax, and crop growth and yield were investigated in southern Manitoba over three growing seasons. As the amount of trifluralin in the soil increased, flax density and dry matter production decreased, such that at a soil concentration equivalent to 1 kg ai ha−1trifluralin, the two were reduced by 40 and 49%, respectively. Recovery from early-season injury was characterized by enhanced crop growth rates (CGRs) and net assimilation rates (NARs) of surviving plants during the remainder of the growing season. Maximum recovery occurred in plots where trifluralin levels in the soil were between 0.8 and 1 kg ha−1at seeding. During the interval between stem elongation and bud initiation, CGRs and NARs of flax in the trifluralin-treated plots exceeded those of flax in the untreated plots by up to 1.5 and 1.2 times, respectively. Additionally, the number of branches per plant increased linearly as trifluralin amounts in the soil increased. Flax seed yield was decreased by trifluralin as described by the equation: flax seed (% of untreated control) = 104.9 - 13.3[trifluralin detected (kg ha−1) at seeding]. Based on this equation, trifluralin levels in the soil of up to 0.7 kg ai ha−1caused less than a 5% reduction in flax yield under weed-free conditions.

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