S-NPP VIIRS Research Articles

Assessment of oceanographic services for the monitoring of highly anthropised coastal lagoons: The Mar Menor case study

Ocean monitoring systems are designed for continuous monitoring of the seas and oceans to track their evolution and thus anticipate environmental issues. However, they are often based on Internet of Things (IoT) systems that are expensive, hard to maintain, and offer little spatial coverage. An emerging alternative is Satellite Remote Sensing (SRS) systems that offer good geographical coverage but, as a reliable and real-time monitoring system, they also face several challenges such as environmental conditions, spatio-temporal granularity, terrain oleography, etc. This paper introduces an easy-to-use software tool to crawl water-quality data from up to 6 satellite instruments (i.e. Sentinel 3A, Sentinel-3B, NOAA VIIRS, SNPP VIIRS, Aqua MODIS, Terra MODIS) of the European Space Agency's (ESA) Coopernicus system and NASA's Marine Environmental Monitoring Service. We also provide an in-depth analysis in terms of reliability and data coverage for the chlorophyll-a (Chl-a) in a highly anthropised local/regional context like the Mar Menor lagoon (Murcia, Spain), where serious socio-environmental issues are arising due to the eutrophication process. Our results show a good linear correlation between in situ data, obtained by several Spanish public institutions since 2016, and data generated by the IRTM-NN (Inverse Radiative Transfer Model-Neural Network) algorithm of Sentinel 3 in general, reaching coefficient correlation values close to 0.9. They also show that organic matter inputs from ephemeral streams are relevant in determining Chl-a concentrations. Moreover, the temporal coverage using a single instrument is rather limited, as no data were recorded for 80% of the days studied. This figure decreases to 30% when data from the 6 satellite instruments are combined, increasing the temporal granularity of the measurements from approximately 5 to 1.5 days, suggesting the need for a combination of these systems for a robust SRS system.

Determining the primary sources of uncertainty in the retrieval of marine remote sensing reflectance from satellite ocean color sensors II. Sentinel 3 OLCI sensors

Uncertainties in remote sensing reflectance Rrs for the Ocean Color sensors strongly affect the quality of the retrieval of concentrations of chlorophyll-a and water properties. By comparison of data from SNPP VIIRS and several AERONET-OC stations and MOBY, it was recently shown that the main uncertainties come from the Rayleigh-type spectral component (Gilerson et al., 2022), which was associated with small variability in the Rayleigh optical thickness in the atmosphere and/or its calculation. In addition, water variability spectra proportional to Rrs were found to play a significant role in coastal waters, while other components including radiances from aerosols and glint were small. This work expands on the previous study, following a similar procedure and applying the same model for the characterization of uncertainties to the Sentinel-3A and B OLCI sensors. It is shown that the primary sources of uncertainties are the same as for VIIRS, i.e., dominated by the Rayleigh-type component, with the total uncertainties for OLCI sensors typically higher in coastal areas than for VIIRS.

Estimating the Wind Dependency of Aerosol Optical Depth at Remote Oceanic Regions

In this article, the applicability of India’s indigenously developed scatterometer, Scatsat-1 for marine aerosol characterization and wind dependency of aerosol optical depth (AOD) was investigated using 3 years of satellite data. Wind data from Scatsat-1 and AOD with its size fraction from SNPP VIIRS from 2017 to 2019 were used for the investigation. A technique has been demonstrated for identifying remote oceanic regions with mostly marine aerosol using certain criteria like distance from land, higher fraction of coarse AOD, lower variation of AOD with wind direction, and so forth. Daily wind and AOD from 2017 to 2019 were used for studying the relationship between wind speed and AOD at remote oceanic locations away from terrestrial and anthropogenic influence. Five regions of interest (ROIs) of 5° by 5° were identified in different oceanic regions for carrying out the regression analysis. A linear increase of coarse mode AOD and total AOD with an increase in wind speed was observed for all five remote locations while fine mode AOD was unrelated. The slope of the linear relation agreed with Kiliyanpilakkil and Meskhidze (2011) for intermediate wind values. The remote regions also had a lower variation of AOD with change in wind direction implying less transport of aerosol from nearby landmasses.

Analyzing Rainfall and Greenness Vegetation Level on Forest/Land Fire Area in Jambi and Central Kalimantan Provinces using Remote Sensing Data

El-Nino, which occurred in 2019 in Indonesia, caused longer dry conditions than usual. Low rainfall and vegetation drought cause widespread forest/land fires. This study aims to know the relationship between drought conditions and forest/land fires from the parameters of rainfall and vegetation greenness level. The study located in Jambi and Central Kalimantan Provinces during the peak months of fires which is September 2019. To see fluctuations in the peak of fires, eight daily data were taken for this period. Extraction of rainfall information is derived from the Himawari-8 infrared band L1 image into L2 rainfall rate data. Vegetation greenness level information is derived from Terra/Aqua MODIS red and near-infrared band images into L2 Enhance Vegetation Index (EVI) data. Hotspot data comes from the images of Terra, Aqua MODIS, SNPP VIIRS, and NOAA20. Fire data was extracted from hotspot data and delineation of MODIS RGB image smoke. Rainfall fluctuation affects the number of forest/land fire hotspots. The decrease in rainfall was followed by an increase of hotspot numbers and vice versa. In Jambi Province, rainfall decreased in first to second period i.e. 40 to 0 mm was followed by an increase of hotspot number which dominated by high confidence level. In Central Kalimantan rainfall increased from third to fourth period i.e. 0 to 100-400 mm followed by the decreasing of hotspot number which dominated by medium confidence level. Meanwhile, the TKV variable had little effect on the number of hotspots but related with rainfall data. In Central Kalimantan Province, the driest TKV (0.1) on September 14-21, 2019, was influenced by low rainfall in the previous period which also has highest number of fire hotspots. In Jambi Province, the driest TKV happened on third period which also the result of lowest rainfall and highest number of fire hotspot in the previous period.

The Potential Mapping of Land Fire Using SNPP VIIRS as a Basis for Environmental Damage Mitigation

The Potential Mapping of Land Fire Using SNPP VIIRS as a Basis for Environmental Damage Mitigation

Burned area monitoring based on multiresolution and multisensor remote sensing image in Muaro Jambi, Jambi

Forest and land fires are one of the disasters that occur regularly every year in the dry season. In 2019, it is estimated that the spread of forest and land fires will continue to expand due to the weak el nino potential faced by Indonesia. Monitoring burned area is important to be done quickly and accurately to find out the distribution and extent of the burned area to be followed up by relevant parties. This study aims to monitor burned area in Muaro Jambi, Jambi Province based on remote sensing imagery from optical sensors and radar sensors, namely Landsat 8, Sentinel 2, and Sentinel 1 satellite imagery. The method of identifying the burned area is based on the hotspot location and the different land cover images before and after the fire. Hotspot data used are Terra / Aqua MODIS, SNPP VIIRS, and NOAA 20 with confidence level high, medium, low while the satellite imagery used is Landsat RGB 6 5 4, Sentinel 2 RGB 11 8a 4, and Sentinel 1 RGB VV VH VV / VH. Based on this monitoring, the results of multisensor and multiresolution image show that the burned area continues to increase during the fire period from 30 July (217 Ha) - 5 August 2019 (1027 Ha).

북한 지역의 SNPP VIIRS DNB 야간영상에 나타난 이례적 복사도 분포의 시공간적 특성

최근 지구 궤도에 발사된 SNPP 위성에 탑재된 VIIRS 센서는 야간에 지표에서 방사된 인공조명의 세기를 DNB 영상에 기록할 수 있다. VIIRS DNB 영상은 인구 및 국내총생산과 같은 사회경제적 지표의 추정을 위한 공간적 대안 자료로 이용되고 있다. 그러나 음의 값과 널값(null radiance)을 포함한 이례적 복사도가 이 자료에 나타날 수 있다. 이에 본 연구는 북한을 포함한 월 단위 VIIRS DNB 영상에 내재할 수 있는 비정상적 복사 휘도의 시공간적 분포 특성을 조사하였다. 북한 지역의 이례적 복사도는 시간적 편중과 공간적 불균형에 따른 분포 특성을 보였다. 이뿐 아니라 월 단위 영상에서는 감지기 오작동에 의한 국지적 잡음이 확인되기도 했다. 이러한 비정상적 복사 휘도는 북한 지역에 대한 사회경제지표의 추정 결과에 왜곡을 초래할 수 있다. 따라서 이례적 복사도 존재 가능성을 고려한 VIIRS DNB 영상 분석이 향후 연구에서 고려되어야 한다.

Mesoscale and synoptic scale dynamic phenomena in the Oyashio current region observed in SAR imagery

ABSTRACT Satellite SAR images are an essential source of information on mesoscale and sub-mesoscale dynamic phenomena in the ocean with a resolution of 4–1000 m. They can be obtained irrespective of cloudiness and sun illumination. In this paper, the dynamic features in the large region in the Northwest Pacific associated with the cold Oyashio Current are considered. The combination of the Oyashio and Kuroshio currents, strong tides, and sharp changes in the topography of the Pacific Ocean shelf along the Kuril and Japan Islands together with storm winds accompanying the deep extratropical cyclones leads to a complicated water circulation. In the investigation, the attention is focused on dominant dynamic features including mesoscale and sub-mesoscale eddies, streamers and internal waves. They play a key role in physical and biological fluxes between waters of different origin. Under a clear sky, the mesoscale and sub-mesoscale features visualize themselves through prominent thermal and biological contrasts; however, under cloudy conditions, they can be detected in the sea surface roughness fields. The sea surface roughness contrasts caused by oceanic and atmospheric phenomena are observed on the Synthetic Aperture Radar (SAR) images acquired by Envisat ASAR and Sentinel-1A/-1B C-SAR at C-band and mainly by ALOS-1/-2 PALSAR at L-band at various polarizations. Spatial characteristics and seasonal features of the sub-mesoscale oceanic and atmospheric phenomena have been revealed on SAR images. The satellite visible and infrared images (NOAA AVHRR, Terra and Aqua MODIS, Landsat-8 OLI and TIRS, SNPP VIIRS) and various products (SST, chlorophyll-a concentration, surface analysis map, etc.) substantially complemented the SAR data.

Development of National Forest/Land Fire Monitoring System Using Remote Sensing Satellite Data (Terra/Aqua Modis and SNPP) by Automation and Nearly Real-time.

Hotspot monitoring system using remote sensing satellite data such as Terra/Aqua Modis and SNPP VIIRS. In order to manage national natural disaster (such as forest/land fire disaster), accurate-real time-accessible data and information are required. In this case the use of remote sensing satellites data is use for the monitoring of natural disasters, especially forest/land fires that occur very massive need monitoring in real time and up to date. Information systems for monitoring of forest/land fires, can be built using remote sensing data of Terra/Aqua Modis and SNPP satellites that continuously monitor the condition of the land/forest by photographing the Indonesian territory respectively four times a day. The hotspot data requirement is 30 minute after the reception in ground station. The built system consists of the reception, processing, cataloguing and dissemination data, in order to fit the requirement the system need to be automation. The data receiving process is done at Parepare and Rumpin ground stations, followed by sending data to Pekayon in real time. Data processing is done in Pekayon using automated software open source module. Furthermore, data cataloguing is built using spatial and numerical based databases. The appearance system is built interactively with web-based online and mobile, user can do searching hotspot information based on location, degree of trust and time of incident. The monitoring system of forest / land fires that have been built have been published and utilized nationally, especially the BNPB in the context of the prevention and mitigation of forest / land fire disasters in Indonesia. Users can access through the website http://modis-catalog.lapan.go.id or can download android-based mobile app “Hotspot LAPAN”. It is expected that with online and mobile web based online and mobile fire monitoring system, it can be used for the prevention and mitigation of forest/land fire disaster in Indonesia.

基于场地自动化观测技术的SNPP VIIRS高频次在轨辐射定标

基于场地自动化观测技术的SNPP VIIRS高频次在轨辐射定标

The progress of operational forest fire monitoring with infrared remote sensing

Forest wildfires pose significant and growing threats to human safety, wildlife habitat, regional economies and global climate change. It is crucial that forest fires be subject to timely and accurate monitoring by forest fire managers and other stake-holders. Measurement by spaceborne equipment has become a practical and appealing method to monitor the occurrence and development of forest wildfires. Here we present an overview of the principles and case studies of forest fire monitoring (FFM) with satellite- and drone-mounted infrared remote sensing (IRRS). This review includes four types of FFM-relevant IRRS algorithms: bi-spectral methods, fixed threshold methods, spatial contextual methods, and multi-temporal methods. The spatial contextual methods are presented in detail since they can be applied easily with commonly available satellite IRRS data, including MODIS, VIIRS, and Landsat 8 OLI. This review also evaluates typical cases of FFM using NOAA-AVHRR, EOS-MODIS, S-NPP VIIRS, Landsat 8 OLI, MSG-SEVIRI, and drone infrared data. To better implement IRRS applications in FFM, it is important to develop accurate forest masks, carry out systematic comparative studies of various forest fire detection systems (known as forest fire products), and improve methods for assessing the accuracy of forest fire detection. Medium-resolution IRRS data are effective for landscape-scale FFM, and the VIIRS 375 m contextual algorithm and RST-FIRES algorithm are helpful for closely tracking forest fires (including small and short-lived fires) and forest-fire early warning.

Using Ground Targets to Validate S-NPP VIIRS Day-Night Band Calibration

In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.

A New Method for Suomi-NPP VIIRS Day–Night Band On-Orbit Radiometric Calibration

The Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) instrument contains a visible imaging band designed to produce imagery during both daytime and nighttime, which is called the day-night band (DNB). The DNB is a three-gain-stage backside-illuminated charge-coupled device (CCD) with four detector arrays that aggregate the individual CCD pixels into 32 different aggregation modes across scan, yielding imagery with a roughly constant horizontal sampling interval. The highest gain stage is over 100 000 times more sensitive than the lowest gain stage; the combination of the three gain stages allows for imagery with radiances ranging from 10 -10 to 10 -2 W · cm -2 · sr -1 . The initial DNB on-orbit calibration relies on monthly sensor special operations. This offline calibration approach results in discrete calibration and the loss of some science data. In this paper, we will present a new calibration method based solely on VIIRS onboard calibrators (OBCs). The calibrator data collected on the nighttime side of an orbit are used to determine the dark offset and the data collected over the daytime side of the orbit, and the day-night terminators are used to compute the cross-stage gain ratios. The results showed that the dark offset and the gain ratio derived from the initial method could be biased up to ten digital numbers (DN) and 12%, respectively, due to nighttime airglow and Earth scene stray light. The calibration is also continuous as calibrator data are recorded for each scan. Because no special operation and offline analysis are required, this method was approved for VIIRS operational implementation to improve the DNB radiometric calibration and sensor on-orbit operations.