Determining the number of measurements required to estimate crop residue cover by different methods

Laamrani, Ahmed; Joosse, Pamela; Feisthauer, Natalie

doi:10.2489/jswc.72.5.471

Cited by 16 publications

(15 citation statements)

References 30 publications

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“…Our study involved fields that had been established as part of a larger project that dealt with the use of multi-temporal remote sensing for mapping and quantification of soil cover on southern Ontario agricultural fields over the Lake Erie basin (see Figure 1 and [ 20 ]). Eighteen square plots (one 15 m × 15 m plot per field) were established throughout the study area and sampled in fall 2014 after harvest.…”

Section: Methodsmentioning

confidence: 99%

“…Specifically, we compared the residue cover estimates derived from the “app” method to those obtained using digital photograph-grid method and an automated residue counting script procedure. In a recent study [ 20 ], the photograph-grid method was found strongly correlated to the line-transect method which is considered a standard and robust method for assessing crop residue and was the “ground truth” in the context of that study. In this study, both photograph-grid and script methods were used to count residue under 100 grid points and are considered as reference methods in this evaluation.…”

Section: Introductionmentioning

confidence: 95%

“…Line-transect and digital photograph-grid methods are the two main approaches that have been widely used to quantify crop residue cover from ground observations. However, the standard ground-based line-transect method requires significant effort to collect an optimal number of samples [ 20 ], is time consuming, labor intensive and cannot provide continuous data over large areas, as percent residue cover is estimated at spatially and temporally disconnected fields. Several studies have found that the digital photograph-grid method can be a suitable alternative to the line-transect method (i.e., [ 5 , 20 ]).…”

Section: Introductionmentioning

confidence: 99%

“…However, the standard ground-based line-transect method requires significant effort to collect an optimal number of samples [ 20 ], is time consuming, labor intensive and cannot provide continuous data over large areas, as percent residue cover is estimated at spatially and temporally disconnected fields. Several studies have found that the digital photograph-grid method can be a suitable alternative to the line-transect method (i.e., [ 5 , 20 ]). However, one of the main issues in the use of photographs to derive percent residue cover is that multiple manipulations are required (i.e., photograph collection, grid preparation, visual counting by different observers, script or spreadsheet calculation of percentage cover).…”

Section: Introductionmentioning

confidence: 99%

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Using a Mobile Device “App” and Proximal Remote Sensing Technologies to Assess Soil Cover Fractions on Agricultural Fields

Laamrani

Lara

Berg

et al. 2018

Sensors

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Quantifying the amount of crop residue left in the field after harvest is a key issue for sustainability. Conventional assessment approaches (e.g., line-transect) are labor intensive, time-consuming and costly. Many proximal remote sensing devices and systems have been developed for agricultural applications such as cover crop and residue mapping. For instance, current mobile devices (smartphones & tablets) are usually equipped with digital cameras and global positioning systems and use applications (apps) for in-field data collection and analysis. In this study, we assess the feasibility and strength of a mobile device app developed to estimate crop residue cover. The performance of this novel technique (from here on referred to as “app” method) was compared against two point counting approaches: an established digital photograph-grid method and a new automated residue counting script developed in MATLAB at the University of Guelph. Both photograph-grid and script methods were used to count residue under 100 grid points. Residue percent cover was estimated using the app, script and photograph-grid methods on 54 vertical digital photographs (images of the ground taken from above at a height of 1.5 m) collected from eighteen fields (9 corn and 9 soybean, 3 samples each) located in southern Ontario. Results showed that residue estimates from the app method were in good agreement with those obtained from both photograph–grid and script methods (R2 = 0.86 and 0.84, respectively). This study has found that the app underestimates the residue coverage by −6.3% and −10.8% when compared to the photograph-grid and script methods, respectively. With regards to residue type, soybean has a slightly lower bias than corn (i.e., −5.3% vs. −7.4%). For photos with residue <30%, the app derived residue measurements are within ±5% difference (bias) of both photograph-grid- and script-derived residue measurements. These methods could therefore be used to track the recommended minimum soil residue cover of 30%, implemented to reduce farmland topsoil and nutrient losses that impact water quality. Overall, the app method was found to be a good alternative to the point counting methods, which are more time-consuming.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Using a Mobile Device “App” and Proximal Remote Sensing Technologies to Assess Soil Cover Fractions on Agricultural Fields

Laamrani

Lara

Berg

et al. 2018

Sensors

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“…This digital method of in-field residue evaluation was found to be highly correlated to traditional line 29 transect methods to accurately estimate post-harvest residue percentages, but in a more efficient manner 30 (Laamrani et al, 2017). 31…”

mentioning

confidence: 96%

Semi-automated roadside image data collection

Pilger

Berg

Joosse

2019

Preprint

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7This article describes the development of a mobile roadside survey procedure for obtaining corroboration 8 data for the remote sensing of agricultural land use practices. The key objective was to produce a dataset of 9 geo-referenced roadside digital images that can be used to compare to in-field photos for measuring 10 agricultural land use and land cover associated with crop residue and cover cropping in the non-growing 11 season. It was concluded that a very high level of correspondence (>90% level of agreement) could be 12 attained using a mobile survey vehicle, as presented in this research, to detailed in-field ground verification 13 data. Classification correspondence was carried out against 114 field sites with a level of agreement at 14 93%. The few discrepancies were in the differentiation of residue levels between 30-60% and >60%, both 15 of which may be considered as achieving conservation practice standards. The mobile roadside image 16 capture has advantages of relatively low cost and insensitivity to cloudy days, which often limits optical 17 remote sensing acquisitions during the study period of interest. We anticipate that this approach can be used 18 to reduce associated field costs for ground surveys, while expanding coverage areas and may be of interest 19 to industry, academic and government organizations for more routine surveys of agricultural soil cover 20 during periods of seasonal cloud cover. 21 region, such as at the county level, in quantifying annual tillage and cover crop use and trends. These 1 methods are also inefficient for situations when generalized classes of landcover are sufficient for program 2 and policy decision making activities. 3 4The common post-harvest activities used in agriculture land management in the southern Ontario study 5 region include conventional (CV), conservation (CS) and no tillage (NT), and potentially cover cropping 6 practices; defined as follows. Conventional tillage is a common post-harvest practice for many large-scale 7 agricultural operations. This tillage practice involves incorporating, or turning residual plant matter into the 8 soil following harvest, and with additional seedbed preparation prior to the following planting cycle. 9Conventional tillage is effective at controlling weeds, however, the burial of residue, and the increased 10

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