Improving crop yield estimation by applying higher resolution satellite NDVI imagery and high-resolution cropland masks

Roznik, Mitchell; Porth, Lysa

doi:10.1016/j.rsase.2022.100693

Cited by 35 publications

(27 citation statements)

References 36 publications

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“…The NDVI is often used to estimate crop yields 123 and NDVI values are made publicly available for the agricultural region of Canada from Statistics Canada's Crop Condition Assessment Program (https://www35.statcan.gc.ca/CCAP/en/index). The NDVI is calculated during the growing season from 1000 m resolution digital data from the National Oceanographic and Atmospheric Administration (NOAA) series of satellites and the 250 m MODIS digital data to monitor the changing vegetation conditions on a 7-day cycle.…”

Section: Agricultural Yieldsmentioning

confidence: 99%

The unprecedented Pacific Northwest heatwave of June 2021

et al. 2023

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In late June 2021 a heatwave of unprecedented magnitude impacted the Pacific Northwest region of Canada and the United States. Many locations broke all-time maximum temperature records by more than 5 °C, and the Canadian national temperature record was broken by 4.6 °C, with a new record temperature of 49.6 °C. Here, we provide a comprehensive summary of this event and its impacts. Upstream diabatic heating played a key role in the magnitude of this anomaly. Weather forecasts provided advanced notice of the event, while sub-seasonal forecasts showed an increased likelihood of a heat extreme with lead times of 10-20 days. The impacts of this event were catastrophic, including hundreds of attributable deaths across the Pacific Northwest, mass-mortalities of marine life, reduced crop and fruit yields, river flooding from rapid snow and glacier melt, and a substantial increase in wildfires—the latter contributing to landslides in the months following. These impacts provide examples we can learn from and a vivid depiction of how climate change can be so devastating.

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Section: Agricultural Yieldsmentioning

confidence: 99%

The unprecedented Pacific Northwest heatwave of June 2021

et al. 2023

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“…Several studies have used NDVI to detect, assess, and monitor drought (Nanzad et al, 2019) and land degradation (Higginbottom and Symeonakis, 2014;Kumar et al, 2022). This index also estimates agricultural production (Roznik et al, 2022) and map fire risk (Michael et al, 2021). The NDVI calculation is based on the difference between the visible red band and the near-infrared band (Eq.…”

Section: Methodsmentioning

confidence: 99%

Exploring the land use and land cover change in the period 2005–2020 in the province of Errachidia, the pre-sahara of Morocco

et al. 2022

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The study investigates the land use and land cover (LULC) in Errachidia province (Pre-Saharan of Morocco) in the period 2005–2020. To this end, remote sensing (RS) tools such as LULC, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), the Enhanced Vegetation Index (EVI), Gravity Recovery and Climate Experiment (GRACE) satellite data, and precipitations were processed and combined. The monitoring of LULC over this period reveals different changes in this area. Generally, for water bodies, two trends can be observed, an increasing trend since 2006 and a decreasing trend from 2011 to the present. However, an increasing trend was recorded for the urban-and-built-up-lands and the grasslands categories. NDVI, NDWI, and EVI showed three major peaks recorded in the same periods (in 2007, 2009, and 2015). In terms of water storage, three phases were found. The first depicted the lowest groundwater quantities with a decreasing trend, which corresponds to a period of drought and/or human pressure. The second phase, the most important that recorded the greatest storage of water while the third phase corresponds to low storage with a decreasing trend. LULC of croplands reveals a slightly increasing trend from 2012 to 2020, which shows an orientation to an extension of crops mainly of date palm encouraged by government programs. A strong correlation between the seasonal NDVI and water storage using GRACE-Data for the period was found. In the end, recommendations on the adaptation to CC were proposed. The findings demonstrate that RS techniques are useful tools to detect hydrological droughts, observe, and conserve land resources. In arid areas such as Errachidia, the solution lies in rationalizing the use of water resources protecting them from uncontrolled anthropogenic events, which may alleviate the pressure. To support local sustainable development, environmental scientists and decision-makers may use the outputs of this study.

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“…A mask operation is applied that selects pixels located in cropland areas. This reduces the amount of measurement error in the NDVI index caused by NDVI signals from unwanted locations such as rocks, trees, and urban areas (Roznik et al, 2022). NDVI is closely related to crop yield and markers of crop development, such as biomass.…”

Section: Satellite Ndvi Datamentioning

confidence: 99%

Using a machine learning approach and big data to augment WASDE forecasts: Empirical evidence from US corn yield

Roznik

Mishra

2023

Journal of Forecasting

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This paper investigates the accuracy of corn yield forecasts using machine learning with satellite and weather data. In addition, the study examines the incremental value of these forecasts to augment the World Agricultural Supply and Demand Estimates (WASDE) forecast. To illustrate the potential of machine learning methods for agricultural forecasting, publicly available data are collected from 1984 to 2021 for national corn yield, state corn yield, satellite variables, and weather variables and used with the XGBoost algorithm. The results show that the XGBoost model performed about the same but did not outperform the WASDE corn yield forecasts over a 12‐year out‐of‐sample period. The incremental value analysis results suggest that the XGBoost and WASDE forecasts capture similar information, and no incremental information exits. Although the XGBoost model does not outperform the WASDE August forecast, it is near real‐time and can be produced using publicly available data. The results indicate that the XGBoost machine learning models can produce reasonably accurate crop yield forecasts.

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Improving crop yield estimation by applying higher resolution satellite NDVI imagery and high-resolution cropland masks

Cited by 35 publications

References 36 publications

The unprecedented Pacific Northwest heatwave of June 2021

The unprecedented Pacific Northwest heatwave of June 2021

Exploring the land use and land cover change in the period 2005–2020 in the province of Errachidia, the pre-sahara of Morocco

Using a machine learning approach and big data to augment WASDE forecasts: Empirical evidence from US corn yield

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