On the measurability of change in Amazon vegetation from MODIS

Hilker, Thomas; Lyapustin, A.; Hall, Forrest G.; Myneni, Ranga B.; Knyazikhin, Yuri; Wang, Yujie; Tucker, Compton J.; Sellers, P. J.

doi:10.1016/j.rse.2015.05.020

Cited by 77 publications

(61 citation statements)

References 46 publications

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“…This provides early morning observations, which are unavailable from MODIS or Visible Infrared Imaging Radiometer Suite (VIIRS), for climatically important tropical regions of the world such as Amazonia where tropical convection generates more clouds in the afternoon. A comparison of statistics between MODIS Terra and Aqua shows about 10% more clouds from MODIS Aqua with an equatorial overpass time of 1330 LT as compared to MODIS Terra crossing the equator at 1030 LT (Hilker et al 2015).…”

Section: Products Epic Ozone and Lambert Equivalent Reflectivity Retmentioning

confidence: 99%

Earth Observations from DSCOVR EPIC Instrument

Marshak

Herman

Szabo

et al. 2018

Bulletin of the American Meteorological Society

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The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O3) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO2) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O2 B-band absorption for vegetation properties.

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Section: Products Epic Ozone and Lambert Equivalent Reflectivity Retmentioning

confidence: 99%

Earth Observations from DSCOVR EPIC Instrument

Marshak

Herman

Szabo

et al. 2018

Bulletin of the American Meteorological Society

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136

140

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“…MAIAC's cloud detection technique yields a noise reduction by a factor of 3-10 compared to standard MODIS surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4, and MYD13A2-Vegetation Index) without the conventional assumption of Lambertian land surface behavior [19,20]. The …”

Section: Maiac Datamentioning

confidence: 99%

Leveraging Multi-Sensor Time Series Datasets to Map Short- and Long-Term Tropical Forest Disturbances in the Colombian Andes

2017

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Abstract:The spatial distribution of disturbances in Andean tropical forests and protected areas has commonly been calculated using bi or tri-temporal analysis because of persistent cloud cover and complex topography. Long-term trends of vegetative decline (browning) or improvement (greening) have thus not been evaluated despite their importance for assessing conservation strategy implementation in regions where field-based monitoring by environmental authorities is limited. Using Colombia's Cordillera de los Picachos National Natural Park as a case study, we provide a temporally rigorous assessment of regional vegetation change from 2001-2015 with two remote sensing-based approaches using the Breaks For Additive Season and Trend (BFAST) algorithm. First, we measured long-term vegetation trends using a Moderate Resolution Imaging Spectroradiometer (MODIS)-based Multi-Angle Implementation of Atmospheric Correction (MAIAC) time series, and, second, we mapped short-term disturbances using all available Landsat images. MAIAC-derived trends indicate a net greening in 6% of the park, but in the surrounding 10 km area outside of the park, a net browning trend prevails at 2.5%. We also identified a 12,500 ha area within Picachos (4% of the park's total area) that has shown at least 13 years of consecutive browning, a result that was corroborated with our Landsat-based approach that recorded a 12,642 ha (±1440 ha) area of disturbed forest within the park. Landsat vegetation disturbance results had user's and producer's accuracies of 0.95 ± 0.02 and 0.83 ± 0.18, respectively, and 75% of Landsat-detected dates of disturbance events were accurate within ±6 months. This study provides new insights into the contribution of short-term disturbance to long-term trends of vegetation change, and offers an unprecedented perspective on the distribution of small-scale disturbances over a 15-year period in one of the most inaccessible national parks in the Andes.

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“…Nowadays, satellite monitoring data is used in addition to traditional methods of ground-based observations of vegetation cover [2,3]. The remote sensing data allows monitoring of the state and structure of vegetation over large areas, including those hardly accessible for ground survey due to high water logging.…”

Section: Introductionmentioning

confidence: 99%

“…The remote sensing data allows monitoring of the state and structure of vegetation over large areas, including those hardly accessible for ground survey due to high water logging. In the paper [3] authors discuss the results of using NDVI [2,4], which was calculated with Lansat data (spatial resolution 30m) to evaluate the negative impact of chemical pollution on the state of coniferous trees in the flares' area of influence at Priobskoe oil field. It was shown that the results of remote assessment of the forest vegetation state changes based on vegetation indices sufficiently correspond to these bioindicative ground research results.…”

Section: Introductionmentioning

confidence: 99%

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Using MODIS NDVI products for vegetation state monitoring on the oil production territory in Western Siberia

Kovalev

Tokareva

2016

MATEC Web of Conferences

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Abstract. Article describes the results of using remote sensing data for vegetation state monitoring on the oil field territories in Western Siberia. We used MODIS data product providing the normalized difference vegetation index (NDVI) values. Average NDVI values of each studied area were calculated for the period from 2010 to 2015 with one year interval for June, July and August. Analysis was carried out via an open tool of geographic information system QGIS used for spatial analysis and calculation of statistical parameters within chosen polygons. Results are presented in graphs showing the variation of NDVI for each study area and explaining the changes in trend lines for each field. It is shown that the majority of graphs are similar in shape which is caused by similar weather conditions. To confirm these results, we have conducted data analysis including temperature conditions and information about the accidents for each area. Abnormal changes in NDVI values revealed an emergency situation on the Priobskoe oil field caused by the flood in 2015. To sum up, the research results show that vegetation of studied areas is in a sufficiently stable state.

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On the measurability of change in Amazon vegetation from MODIS

Cited by 77 publications

References 46 publications

Earth Observations from DSCOVR EPIC Instrument

Earth Observations from DSCOVR EPIC Instrument

Leveraging Multi-Sensor Time Series Datasets to Map Short- and Long-Term Tropical Forest Disturbances in the Colombian Andes

Using MODIS NDVI products for vegetation state monitoring on the oil production territory in Western Siberia

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