The Use of NASA LANCE Imagery and Data for Near Real-Time Applications

Davies, David K.; Murphy, Kevin J.; Conover, H.; Regner, K.; Beaumont, B.; Masuoka, E.; Vollmer, Bruce; Theobald, Michael; Durbin, P.; Michael, K.; Boller, R. A.; Schmaltz, J. E.; Horrocks, K.; Ilavajhala, S.; Ullah, A.; Teague, M. J.; Thompson, C. K.; Bingham, Andrew

doi:10.1007/978-1-4939-2602-2_11

Cited by 8 publications

(1 citation statement)

References 18 publications

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“…Coarse resolution data from the advanced very high resolution radiometer from 1981 and the moderate resolution imaging spectroradiometer (MODIS) on board the Earth Observing System Terra satellite from 2000 can be used to monitor changes in agricultural yield in both labor-and capital-intensive agricultural systems due to the weather (Brown & Mata, 2016). Operational, satellite-derived rainfall datasets such as National Oceanic and Atmospheric Administration's Rainfall Estimate and the Climate Hazard Infrared Precipitation data with Stations (CHIRPS) are widely used in food security analyses and crop monitoring (Davies et al, 2015;Funk, Peterson, et al, 2015). Satellite data provide daily images of the globe and are able to measure rainfall, vegetation, and land surface temperature conditions resulting from abnormally wet, dry, or cold weather.…”

Section: Remote Sensing Of Yield and Cropped Areamentioning

confidence: 99%

Remote sensing technology and land use analysis in food security assessment

Brown

2016

Journal of Land Use Science

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Climate change and a rapidly growing human population have put ever greater strains on the global food system. Although the number of food insecure people in the world has reached a record low, changing land use and climate variability will threaten our ability to maintain this progress. Profound changes in the structure of economies around the world have affected agricultural production and how food is delivered to the consumer. This paper explores connections between land use, environmental change and food availability, access, and utilization. Each of these elements of food security has vulnerabilities to changing environmental conditions and land use that can be explored using satellite remote sensing observations. Technology is a key way environmental changes can be quantified and used in food security assessment. ARTICLE HISTORY

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Section: Remote Sensing Of Yield and Cropped Areamentioning

confidence: 99%

Remote sensing technology and land use analysis in food security assessment

Brown

2016

Journal of Land Use Science

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Software Tools for Satellite Laser Altimetry Data Processing, Analysis, and Visualization: An Overview and Assessment

Silva

Lopes

Campos

2022

Algorithms for Intelligent Systems

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Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring

Skakun

Justice

Vermote

et al. 2017

International Journal of Remote Sensing

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The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02 to 0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual dataset.

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The Use of NASA LANCE Imagery and Data for Near Real-Time Applications

Cited by 8 publications

References 18 publications

Remote sensing technology and land use analysis in food security assessment

Remote sensing technology and land use analysis in food security assessment

Software Tools for Satellite Laser Altimetry Data Processing, Analysis, and Visualization: An Overview and Assessment

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring

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