scholarly journals Gap-Filling of a MODIS Normalized Difference Snow Index Product Based on the Similar Pixel Selecting Algorithm: A Case Study on the Qinghai–Tibetan Plateau

2020 ◽  
Vol 12 (7) ◽  
pp. 1077
Author(s):  
Muyi Li ◽  
Xiufang Zhu ◽  
Nan Li ◽  
Yaozhong Pan
Keyword(s):  
Tibetan Plateau ◽  
Absolute Error ◽  
Significant Loss ◽  
Gap Filling ◽  
Filter Methods ◽  
Moderate Resolution ◽  
Filling Method ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

Cloud contamination has largely limited the application of the Moderate Resolution Imaging Spectroradiometer(MODIS) normalized difference snow index (NDSI). Here, a novel gap-filling method based on spatial-temporal similar pixel interpolation was proposed to remove cloud occlusions in MODIS NDSI products. First, the widely used Terra and Aqua combination and three-day temporal filter methods were applied. The remaining missing NDSI information was estimated by using similar eligible pixels in the remaining cloud-free portion of a target image through a spatial-temporal similar pixel selecting algorithm (SPSA). The MODIS daily NDSI product data from 2003 to 2018 in the Qinghai–Tibetan Plateau (China) was used as a case study. The results demonstrate that the three-step methodology can generate almost completely cloud-free, daily MODIS NDSI images, reducing the cloud-gap fraction from >45% to less than 1.5% on average. The validation results of the SPSA method exhibited a high accuracy, with a high R2 exceeding 0.78, a low mean absolute error of 2.77%, a root mean square error of 3.78%, and a 96.92% overall accuracy. The proposed method can fill cloud gaps without a significant loss of accuracy, especially during snow cover transition periods (autumn and spring), which may provide more accurate cloud-free NDSI data for climate change and energy balance studies.

scholarly journals Variations in Winter Surface Temperature of the Purog Kangri Ice Field, Qinghai–Tibetan Plateau, 2001–2018, Using MODIS Data

2020 ◽  
Vol 12 (7) ◽  
pp. 1133
Author(s):  
Yufan Qie ◽  
Ninglian Wang ◽  
Yuwei Wu ◽  
An’an Chen
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Warming Trend ◽  
Data Set ◽  
Moderate Resolution ◽  
Ice Field ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Meteorological Observations

In the context of global warming, the land surface temperature (LST) from remote sensing data is one of the most useful indicators to directly quantify the degree of climate warming in high-altitude mountainous areas where meteorological observations are sparse. Using the daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MOD11A1 V6) after eliminating pixels that might be contaminated by clouds, this paper analyzes temporal and spatial variations in the mean LST on the Purog Kangri ice field, Qinghai–Tibetan Plateau, in winter from 2001 to 2018. There was a large increasing trend in LST (0.116 ± 0.05 °C·a−1) on the Purog Kangri ice field during December, while there was no evident LST rising trend in January and February. In December, both the significantly decreased albedo (−0.002 a−1, based on the MOD10A1 V6 albedo product) on the ice field surface and the significantly increased number of clear days (0.322 d·a−1) may be the main reason for the significant warming trend in the ice field. In addition, although the two highest LST of December were observed in 2017 and 2018, a longer data set is needed to determine whether this is an anomaly or a hint of a warmer phase of the Purog Kangri ice field in December.

scholarly journals Cross-Comparison between MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

Climate ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 57 ◽  
Author(s):  
Shubhechchha Thapa ◽  
Parveen K. Chhetri ◽  
Andrew G. Klein
Keyword(s):  
Snow Cover ◽  
Infrared Imaging ◽  
Environmental Data ◽  
Data Series ◽  
Climate Data ◽  
Snow Cover Area ◽  
Transition Zones ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP (National Polar-Orbiting Partnership) satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS (Moderate Resolution Imaging Spectroradiometer). Although it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage, quantitative comparisons between their snow products are currently limited. Therefore, this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (Environmental Data Records) (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI (Normalized Difference Snow Index) Snow Cover product at a snow cover fraction of 30% generated binary snow maps are most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. The agreement was highest during the winter but lower during late fall and spring. MODIS and VIIRS often mapped snow/no-snow transition zones as a cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicate that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67% and cloud 65.02% and 59.91%, respectively. While VIIRS and MODIS have a similar capacity to map snow cover, VIIRS has the potential to map snow cover area more accurately, for the successful development of climate data records.

scholarly journals Comparison of MODIS 250 m products for early corn yield predictions: a case study in Vojvodina, Serbia

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Miro Govedarica ◽  
Dušan Jovanović ◽  
Filip Sabo ◽  
Mirko Borisov ◽  
Milan Vrtunski ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Corn Yield ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractThe aim of the paper is to compare Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (

scholarly journals The Spatial–Spectral–Environmental Extraction Endmember Algorithm and Application in the MODIS Fractional Snow Cover Retrieval

2020 ◽  
Vol 12 (22) ◽  
pp. 3693
Author(s):  
Hongyu Zhao ◽  
Xiaohua Hao ◽  
Jian Wang ◽  
Hongyi Li ◽  
Guanghui Huang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Absolute Error ◽  
Satellite Observation ◽  
Landsat 8 ◽  
Endmember Extraction ◽  
Analysis Model ◽  
Fractional Snow Cover ◽  
Extraction Algorithm ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Endmember extraction is a primary and indispensable component of the spectral mixing analysis model applicated to quantitatively retrieve fractional snow cover (FSC) from satellite observation. In this study, a new endmember extraction algorithm, the spatial–spectral–environmental (SSE) endmember extraction algorithm, is developed, in which spatial, spectral and environmental information are integrated together to automatically extract different types of endmembers from moderate resolution imaging spectroradiometer (MODIS) images. Then, combining the linear spectral mixture analysis model (LSMA), the SSE endmember extraction algorithm is practically applied to retrieve FSC from standard MODIS surface reflectance products in China. The new algorithm of MODIS FSC retrieval is named as SSEmod. The accuracy of SSEmod is quantitatively validated with 16 higher spatial-resolution FSC maps derived from Landsat 8 binary snow cover maps. Averaged over all regions, the average root-mean-square-error (RMSE) and mean absolute error (MAE) are 0.136 and 0.092, respectively. Simultaneously, we also compared the SSEmod with MODImLAB, MODSCAG and MOD10A1. In all regions, the average RMSE of SSEmod is improved by 2.3%, 2.6% and 5.3% compared to MODImLAB for 0.157, MODSCAG for 0.157 and MOD10A1 for 0.189. Therefore, our SSE endmember extraction algorithm is reliable for the MODIS FSC retrieval and may be also promising to apply other similar satellites in view of its accuracy and efficiency.

Snow cover mapping using IRS-P6 AWiFS data and the relationships between some climatic factors with snowpack in the northwest of Iran

2015 ◽  
Vol 7 (2) ◽  
pp. 415-429
Author(s):  
M. Seyedielmabad ◽  
H. R. Moradi
Keyword(s):  
Snow Cover ◽  
Climatic Factors ◽  
Unsupervised Classification ◽  
Wide Field ◽  
Snow Cover Area ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Field Sensor ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

In this study, we explored the potential of the multispectral and multi-temporal IRS Advanced Wide Field Sensor (AWiFS) data for mapping of the snow cover in the northwest regions of Iran. The AWiFS snow cover maps, based on the unsupervised classification method, were compared with the estimates of snow cover area derived from the moderate resolution imaging spectroradiometer (MODIS) images based on the normalized difference snow index. Good concurrence was observed with respect to the snow area between the AWiFS features and the MODIS features; however, the snow spatial distribution of the AWiFS features differed from those of the MODIS based on the nonentity of the temporal accordance between two types of features. Also, we explored the relationships between some climatic and topographic factors with the snowpack in the northwest part of Iran. Relationships between some climatic factors with snowpack specifications were obtained, which showed significant correlation only between the components of daily temperature and snow density. The other results showed that the amounts of snowpack depth have significant correlations with the height of the stations and the height classes in 1% surface and snowpack depths showed significant differences together within the different height classes.

scholarly journals MODIS-derived interannual variability of the equilibrium-line altitude across the Tibetan Plateau

2016 ◽  
Vol 57 (71) ◽  
pp. 140-154 ◽  
Author(s):  
Marinka Spiess ◽  
Christoph Schneider ◽  
Fabien Maussion
Keyword(s):  
Tibetan Plateau ◽  
Large Scale ◽  
Equilibrium Line ◽  
Climate Indices ◽  
The Tibetan Plateau ◽  
Equilibrium Line Altitude ◽  
Winter Temperatures ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Positive Correlations

Abstract.Using the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1 radiance Swath Data (MOD02QKM) with a spatial resolution of 250 m, we derive snowlines during July–September 2001–12 for several mountain ranges distributed across the Tibetan Plateau (TP). Radiance bands 1 and 2 are projected to the study area and processed automatically. The discrimination between snow and ice is done using a k-mean cluster analysis and the snowlines are delineated based on a fixed percentile of the snow-cover altitude. The highest transient snowline altitude is then taken as a proxy for the equilibrium-line altitude (ELA). In the absence of measured glaciological, meteorological or hydrological data, our ELA time series enable better understanding of atmosphere-cryosphere couplings on the TP. Interannual ELA variability is linked to local and remote climate indices using a correlation analysis. Southerly flow and higher temperatures are linked with a higher ELA in most regions. Eastern and Trans-Himalayan sites show positive correlations between winter temperatures and ELA. As winter temperatures are substantially below zero, this suggests an enhancement of winter sublimation as opposed to a reduction in accumulation. It appears that large-scale atmospheric forcing has varying and sometimes opposite influences on the annual ELA in different regions on the TP.

scholarly journals Adaption of the MODIS aerosol retrieval algorithm using airborne spectral surface reflectance measurements over urban areas: a case study

2015 ◽  
Vol 8 (12) ◽  
pp. 5237-5249 ◽  
Author(s):  
E. Jäkel ◽  
B. Mey ◽  
R. Levy ◽  
X. Gu ◽  
T. Yu ◽  
...  
Keyword(s):  
Urban Areas ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Airborne Measurements ◽  
Modis Aod ◽  
Urban Sample ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It was shown that the operational MODIS AOD retrieval over land reproduces the AOD reference input of 0.85 for dark surface types (retrieved AOD = 0.87 (C5)). An overestimation of AOD = 0.99 is found for urban surfaces, whereas the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86.

scholarly journals Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

2012 ◽  
Vol 51 (10) ◽  
pp. 1811-1822 ◽  
Author(s):  
Kristopher M. Bedka ◽  
Richard Dworak ◽  
Jason Brunner ◽  
Wayne Feltz
Keyword(s):  
Weather Prediction ◽  
Convective Cloud ◽  
Radar Data ◽  
Numerical Weather Prediction Model ◽  
Detection Methods ◽  
Spatial Gradients ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractTwo satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-μm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD > 0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

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.

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