scholarly journals Identifying drought events in sugarcane using drought indices derived from Modis sensor

2017 ◽  
Vol 52 (11) ◽  
pp. 1063-1071 ◽  
Author(s):  
Michelle Cristina Araujo Picoli ◽  
Daniel Garbellini Duft ◽  
Pedro Gerber Machado
Keyword(s):  
Near Infrared ◽  
Sensor Data ◽  
Drought Indices ◽  
Spectral Indices ◽  
Seasonal Fluctuations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aqua Satellite ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Shortwave Infrared

Abstract: The objective of this work was to evaluate the potential of several spectral indices, used on moderate resolution imaging spectroradiometer (Modis) images, in identifying drought events in sugarcane. Images of Terra and Aqua satellites were used to calculate the spectral indices, using visible (red), near infrared, and shortwave infrared bands, and eight indices were selected: NDVI, EVI2, GVMI, NDI6, NDI7, NDWI, SRWI, and MSI. The indices were calculated using images between October and April of the crop years 2007/08, 2008/09, 2009/10, and 2013/14. These indices were then correlated with the standardized precipitation-evapotranspiration index (SPEI), calculated for 1, 3, and 6 months. Four of them had significant correlations with SPEI: GVMI, MSI, NDI7, and NDWI. Spectral indices from Modis sensor on board the Aqua satellite (MYD) were more suited for drought detection, and March provided the most relevant indices for that purpose. Drought indices calculated from Modis sensor data are effective for detecting sugarcane drought events, besides being able to indicate seasonal fluctuations.

Test of a Modified Infrared-Only ABI Cloud Mask Algorithm for AHI Radiance Observations

2016 ◽  
Vol 55 (11) ◽  
pp. 2529-2546 ◽  
Author(s):  
X. Zhuge ◽  
X. Zou
Keyword(s):  
Near Infrared ◽  
Extended System ◽  
Clear Sky ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask ◽  
Very High ◽  
Lower False Alarm Rate ◽  
Infrared Channel

AbstractAssimilation of infrared channel radiances from geostationary imagers requires an algorithm that can separate cloudy radiances from clear-sky ones. An infrared-only cloud mask (CM) algorithm has been developed using the Advanced Himawari Imager (AHI) radiance observations. It consists of a new CM test for optically thin clouds, two modified Advanced Baseline Imager (ABI) CM tests, and seven other ABI CM tests. These 10 CM tests are used to generate composite CMs for AHI data, which are validated by using the Moderate Resolution Imaging Spectroradiometer (MODIS) CMs. It is shown that the probability of correct typing (PCT) of the new CM algorithm over ocean and over land is 89.73% and 90.30%, respectively and that the corresponding leakage rates (LR) are 6.11% and 4.21%, respectively. The new infrared-only CM algorithm achieves a higher PCT and a lower false-alarm rate (FAR) over ocean than does the Clouds from the Advanced Very High Resolution Radiometer (AVHRR) Extended System (CLAVR-x), which uses not only the infrared channels but also visible and near-infrared channels. A slightly higher FAR of 7.92% and LR of 6.18% occurred over land during daytime. This result requires further investigation.

scholarly journals Inter-calibration of polar imager solar channels using SEVIRI

2013 ◽  
Vol 6 (2) ◽  
pp. 3215-3247 ◽  
Author(s):  
J. F. Meirink ◽  
R. A. Roebeling ◽  
P. Stammes
Keyword(s):  
High Resolution ◽  
Spectral Response ◽  
Calibration Method ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aqua Satellite ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Direct Inter ◽  
Very High

Abstract. Accurate calibration of satellite imagers is a prerequisite for using their measurements in climate applications. Here we present a method for the inter-calibration of geostationary and polar-orbiting imager solar channels based on regressions of collocated near-nadir radiances. Specific attention is paid to correcting for differences in spectral response between instruments. The method is used to calibrate the solar channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the geostationary Meteosat satellite with corresponding channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the polar-orbiting Aqua satellite. The SEVIRI operational calibration is found to be stable during the years 2004 to 2009 but off by −8, −6, and +3.5% for channels 1 (0.6 μm), 2 (0.8 μm), and 3 (1.6 μm), respectively. These results are robust for a range of choices that can be made regarding data collocation and selection, as long as the viewing and illumination geometries of the two instruments are matched. Uncertainties in the inter-calibration method are estimated to be 1% for channel 1 and 1.5% for channels 2 and 3. A specific application of the method is the inter-calibration of polar imagers using SEVIRI as a transfer instrument. This offers an alternative to direct inter-calibration, which in general has to rely on high-latitude collocations. Using this method we have tied MODIS-Terra and Advanced Very High Resolution Radiometer (AVHRR) instruments on National Oceanic and Atmospheric Administration (NOAA) satellites 17 and 18 to MODIS-Aqua for the years 2007 to 2009. While reflectances of the two MODIS instruments differ less than 2% for all channels considered, deviations of an existing AVHRR calibration from MODIS-Aqua reach −3.5 and +2.5% for the 0.8 and 1.6 μm channels, respectively.

scholarly journals Estimation of spatio-temporal distribution of precipitable water using MODIS and AVHRR data: a case study for Cyprus

2011 ◽  
Vol 30 ◽  
pp. 23-29 ◽  
Author(s):  
D. Hadjimitsis ◽  
Z. Mitraka ◽  
I. Gazani ◽  
A. Retalis ◽  
N. Chrysoulakis ◽  
...  
Keyword(s):  
Near Infrared ◽  
Temporal Distribution ◽  
Grid Cell ◽  
Precipitable Water ◽  
Avhrr Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. In this paper, the atmospheric precipitable water (PW) over the area of Cyprus was estimated by means of Advanced Very High Resolution Radiometer (AVHRR) thermal channels brightness temperature difference (ΔT). The AVHRR derived ΔT was calculated in a grid of 5 × 5 km cells; the corresponding PW value in each grid cell was extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 product (near-infrared algorithm). Once the PW – ΔT relationship coefficients corresponding to the area of Cyprus were calculated, the relationship was applied to AVHRR data for one month period. Radiosonde derived PW values, as well as MODIS independent PW values were used to validate the estimations and a good agreement was noted.

scholarly journals Critical evaluation of cloud contamination in the MISR aerosol products using MODIS cloud masking products

2013 ◽  
Vol 6 (6) ◽  
pp. 10057-10079 ◽  
Author(s):  
Y. Shi ◽  
J. Zhang ◽  
J. S. Reid ◽  
B. Liu ◽  
E. J. Hyer
Keyword(s):  
High Latitude ◽  
Near Infrared ◽  
Critical Evaluation ◽  
Mean Value ◽  
Screening Methods ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
One Year ◽  
Cloud Screening

Abstract. For the first time, using the Terra Moderate Resolution Imaging Spectroradiometer (MODIS)-based cloud screening methods, we have evaluated the impacts of cloud contamination on the Terra Multi-angle Imaging Spectroradiometer (MISR) aerosol optical depth (AOD) product. Our study, based on one year of collocated MISR and MODIS data, suggests that cloud contamination exists in both over-water and over-land MISR AOD data with heavier cloud contamination occurring over the high latitude Southern hemispheric oceans. On average globally, our study shows that thin cirrus cloud contamination introduces a possible ~0.01 high bias for the over-water MISR AOD retrievals. Over the mid to high latitude oceans and Southeast Asia, this number increases to 0.015–0.02. However, biases much larger than this mean value are found in individual retrievals. This study suggests that cloud-clearing methods using observations from MISR alone, which has only visible and near infrared channels, may not be sufficient. Measurements from MODIS can be applied to assist cloud-clearing of the MISR aerosol retrievals. Cloud screening algorithms based on multi-sensor approaches are feasible and should be considered for current and future satellite aerosol studies.

scholarly journals MISR calibration issues in high-contrast scenes, and empirical corrections

2015 ◽  
Vol 8 (3) ◽  
pp. 2521-2554 ◽  
Author(s):  
J. A. Limbacher ◽  
R. A. Kahn
Keyword(s):  
Near Infrared ◽  
High Contrast ◽  
Green Band ◽  
Validation Data ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Satellite ◽  
Cloud Screening

Abstract. We diagnose the potential causes for the Multi-angle Imaging SpectroRadiometer's (MISR) persistent high aerosol optical depth (AOD) bias at low AOD with the aid of coincident MODerate-resolution Imaging Spectroradiometer (MODIS) imagery from NASA's Terra satellite. Internal reflections within the MISR instrument are responsible for a large portion of the high AOD bias in high-contrast scenes, which are especially common as broken-cloud situations over ocean. Discrepancies between MODIS and MISR nadir-viewing near-infrared (NIR) images are used to optimize nine parameters, along with a background reflectance modulation term (that was modeled separately), to represent the observed features. Independent, surface-based AOD measurements from the AErosol RObotic NETwork (AERONET) and the Marine Aerosol Network (MAN) are compared with MISR Research Algorithm (RA) AOD retrievals for 1118 coincidences to validate the corrections when applied to the nadir and off-nadir cameras. Additionally, the calibration coefficients for the red and NIR channels used for MISR over-water aerosol retrievals were reassessed with the RA to be consistent on a camera-by-camera basis. With these corrections, plus the baseline RA corrections applied (except enhanced cloud screening), the median AOD bias in the mid-visible (green) band decreases from 0.010 to 0.002, the RMSE decreases by ~ 10%, and the slope and correlation of the MISR vs. sun photometer Ångström Exponent improves. For AOD558 nm < 0.10 and with additional cloud screening, the median bias for the RA-retrieved AOD in the green band decreases from 0.011 to 0.003, compared to ~ 0.023 for the Standard Algorithm (SA). RMSE decreases by ~ 20% compared to the baseline (uncorrected) RA and by 17–53% compared to the SA. After all corrections and cloud screening are implemented, for AOD558 nm < 0.10, which includes about half the validation data, 68% absolute AOD errors for the RA have dropped to < 0.02 (~ 0.018).

scholarly journals Assessment of the relative accuracy of hemispheric-scale snow-cover maps

2002 ◽  
Vol 34 ◽  
pp. 24-30 ◽  
Author(s):  
Dorothy K. Hall ◽  
Richard E. J. Kelly ◽  
George A. Riggs ◽  
Alfred T. C. Chang ◽  
James L. Foster
Keyword(s):  
Snow Cover ◽  
Near Infrared ◽  
Passive Microwave ◽  
Defense Meteorological Satellite Program ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Microwave Imager ◽  
Meteorological Satellite ◽  
Microwave Data

AbstractThere are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period 23 October–25 December 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and operational snow maps from the U.S. National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), both of which rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS maps with Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps for the same period. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, but discrepancies exist as to the location and extent of the snow cover even between operational snow maps. The MODIS snow-cover maps show more snow in each of the 8 day periods than do the NOHRSC maps, in part because MODIS maps the effects of fleeting snowstorms due to its frequent coverage. The large (~30 km) footprint of the SSM/I pixel, and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.33 x 106 km2 in the amount of snow mapped using MODIS vs SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping capability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

scholarly journals Inter-calibration of polar imager solar channels using SEVIRI

2013 ◽  
Vol 6 (9) ◽  
pp. 2495-2508 ◽  
Author(s):  
J. F. Meirink ◽  
R. A. Roebeling ◽  
P. Stammes
Keyword(s):  
High Resolution ◽  
Spectral Response ◽  
Calibration Method ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aqua Satellite ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Direct Inter ◽  
Very High

Abstract. Accurate calibration of satellite imagers is a prerequisite for using their measurements in climate applications. Here we present a method for the inter-calibration of geostationary and polar-orbiting imager solar channels based on regressions of collocated near-nadir reflectances. Specific attention is paid to correcting for differences in spectral response between instruments. The method is used to calibrate the solar channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the geostationary Meteosat satellite with corresponding channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the polar-orbiting Aqua satellite. The SEVIRI operational calibration is found to be stable during the years 2004 to 2009, but offset by −8, −6, and +3.5 % for channels 1 (0.6 μm), 2 (0.8 μm), and 3 (1.6 μm), respectively. These results are robust for a range of choices that can be made regarding data collocation and selection, as long as the viewing and illumination geometries of the two instruments are matched. Uncertainties in the inter-calibration method are estimated to be 1 % for channel 1 and 1.5 % for channels 2 and 3. A specific application of our method is the inter-calibration of polar imagers using SEVIRI as a transfer instrument. This offers an alternative to direct inter-calibration, which in general has to rely on high-latitude collocations. Using this method we have tied MODIS-Terra and Advanced Very High Resolution Radiometer (AVHRR) instruments on National Oceanic and Atmospheric Administration (NOAA) satellites 17 and 18 to MODIS-Aqua for the years 2007 to 2009. While reflectances of the two MODIS instruments differ less than 2 % for all channels considered, deviations of an existing AVHRR calibration from MODIS-Aqua reach −3.5 and +2.5 % for the 0.8 and 1.6 μm channels, respectively.

scholarly journals Combination of Cross- and Inter-Band Radiometric Calibrations for a Hyperspectral Sensor Using Model-Based Spectral Band Adjustment

2020 ◽  
Vol 12 (12) ◽  
pp. 2011
Author(s):  
Hiroki Mizuochi ◽  
Satoshi Tsuchida ◽  
Kenta Obata ◽  
Hirokazu Yamamoto ◽  
Satoru Yamamoto
Keyword(s):  
Near Infrared ◽  
Spectral Band ◽  
Space Station ◽  
Infrared Region ◽  
Band Adjustment ◽  
Moderate Resolution ◽  
Satellite Sensors ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cross Calibration ◽  
Shortwave Infrared

Recently, the growing number of hyperspectral satellite sensors have increased the demand for a flexible and robust approach to their calibration. This paper proposes an operational method for the simultaneous correction of inter-sensor and inter-band biases in hyperspectral sensors via the soil line concept for spectral band adjustment. Earth Observing-1 Hyperion was selected as an example, with the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference. The results over the Railroad Valley Playa calibration site indicated that the discrepancy in the analogous bands between Hyperion and MODIS during 2001–2008 was approximately 4–6% and 7–9% of the root-mean-square error in the top-of-atmosphere (TOA) radiance at the visible and near-infrared region and shortwave infrared region, respectively. For all Hyperion bands, the relative cross-calibration coefficients during this period were calculated (typically ranging from 0.9 to 1.1) to correct the Hyperion TOA radiance to be consistent with the MODIS and the other Hyperion bands. The application of the proposed approach could allow for more flexible cross-calibration of irregular-orbit sensors aboard the International Space Station.

scholarly journals Prototype Downscaling Algorithm for MODIS Satellite 1 km Daytime Active Fire Detections

Fire ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 29 ◽  
Author(s):  
Sanath Sathyachandran Kumar ◽  
Joshua J. Picotte ◽  
Birgit Peterson
Keyword(s):  
Spatial Uncertainty ◽  
Point Spread Functions ◽  
Active Fire ◽  
High Resolution Imagery ◽  
Moderate Resolution ◽  
Science Community ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Shortwave Infrared ◽  
Sky Conditions

This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as compared to the non-burning neighborhood components. Active fire presence probability class for each of the 500 m pixels within the 1 km footprint is assigned by locally adaptive contextual tests against its surrounding neighborhood pixels. Accuracy is assessed using gas flares and wildfires in conjunction with available high-resolution imagery. Proof of concept results using MODIS observations over two sites show that under clear sky conditions, over 84% of the 500 m locations that had active fires were correctly assigned to high to medium probabilities, and correspondingly low to poor probabilities were assigned to locations with no visible flaming fronts. Factors limiting the algorithm performance include fire size/temperature distributions, cloud and smoke obscuration, sensor point spread functions, and geolocation errors. Despite these limitations, the resulting finer spatial scale of active fire detections will not only help first responders and managers to locate actively burning fire fronts more precisely but will also be useful for the fire science community.

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