scholarly journals Improving the usability of the Multi-angle Imaging SpectroRadiometer (MISR) L1B2 Georectified Radiance Product (2000–present) in land surface applications

2020 ◽  
Vol 12 (2) ◽  
pp. 1321-1346
Author(s):  
Michel M. Verstraete ◽  
Linda A. Hunt ◽  
Veljko M. Jovanovic
Keyword(s):  
Missing Data ◽  
Land Surface ◽  
Data Repository ◽  
Local Mode ◽  
Science Data ◽  
Data Services ◽  
Spectral Bands ◽  
Digital Elevation ◽  
Virtual Machine Technology ◽  
Elevation Model

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra platform has been acquiring global measurements of the spectrodirectional reflectance of the Earth since 24 February 2000 and is still operational as of this writing. The primary radiometric data product generated by this instrument is known as the Level 1B2 (L1B2) Georectified Radiance Product (GRP): it contains the 36 radiometric measurements acquired by the instrument's nine cameras, each observing the planet in four spectral bands. The product version described here is projected on a digital elevation model and is available from the NASA Langley Atmospheric Science Data Center (ASDC; http://doi.org/10.5067/Terra/MISR/MI1B2T_L1.003; Jovanovic et al., 1999). The MISR instrument is highly reliable. Nevertheless, its onboard computer occasionally becomes overwhelmed by the number of raw observations coming from the cameras' focal planes, especially when switching into or out of Local Mode acquisitions that are often requested in conjunction with field campaigns. Whenever this occurs, one or more lines of data are dropped while the computer resets and readies itself for accepting new data. Although this type of data loss is minuscule compared to the total number of measurements acquired and is marginal for atmospheric studies dealing with large areas and long periods of time, this outcome can be crippling for land surface studies that focus on the detailed analysis of particular scenes at specific times. This paper describes the problem, reports on the prevalence of missing data, proposes a practical solution to optimally estimate the values of the missing data and provides evidence of the performance of the algorithm through specific examples in southern Africa. The software to process MISR L1B2 GRP data products as described here is openly available to the community from the GitHub website (https://github.com/mmverstraete or https://doi.org/10.5281/zenodo.3519988). Two additional sets of resources are also made available on the research data repository of GFZ Data Services in conjunction with this paper. The first set (A; Verstraete et al., 2020, https://doi.org/10.5880/fidgeo.2020.012) includes five items: (A1) a compressed archive (L1B2_Out.zip) containing all intermediary, final and ancillary outputs created while generating the figures of this paper; (A2) a user manual (L1B2_Out.pdf) describing how to install, uncompress and explore those files; (A3) an additional compressed archive (L1B2_Suppl.zip) containing a similar set of results, only for eight other sites, spanning a much wider range of geographical, climatic and ecological conditions; (A4) a companion user manual (L1B2_Suppl.pdf) describing how to install, uncompress and explore those additional files; and (A5) a separate input MISR data archive (L1B2_input_68050.zip) for Path 168, Orbit 68050. This latter archive is usable with the second set (B; Verstraete and Vogt, 2020; https://doi.org/10.5880/fidgeo.2020.011), which includes (B1) a stand-alone, self-contained, executable version of the L1B2 correction codes (L1B2_Soft_Win.zip) that uses the IDL Virtual Machine technology and does not require a paid IDL license as well as (B2) a user manual (L1B2_Soft_Win.pdf) that explains how to install, uncompress and use this software.

scholarly journals Improving the usability of the MISR L1B2 Georectified Radiance Product (2000–present) in land surface applications

2019 ◽  
Author(s):  
Michel M. Verstraete ◽  
Linda A. Hunt ◽  
Veljko M. Jovanovic
Keyword(s):  
Missing Data ◽  
Land Surface ◽  
Local Mode ◽  
Science Data ◽  
Spectral Bands ◽  
Digital Elevation ◽  
Field Campaigns ◽  
Elevation Model ◽  
Raw Observations ◽  
Radiometric Data

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra platform has been acquiring global measurements of the spectro-directional reflectance of the Earth since 24 February 2000 and is still operational as of this writing. The primary radiometric data product generated by this instrument is known as the Level 1B2 Georectified Radiance Product (GRP): it contains the 36 radiometric measurements acquired by the instrument's 9 cameras, each observing the planet in 4 spectral bands. The product version described here is projected on a digital elevation model and is available from the NASA Langley Atmospheric Science Data Center (ASDC) (https://doi.org/10.5067/Terra/MISR/MI1B2T_L1.003 (Jovanovic et al., 1999). The MISR instrument is highly reliable. Nevertheless, its on-board computer occasionally becomes overwhelmed by the amount of raw observations coming from the cameras' focal planes, especially when switching into or out of Local Mode acquisitions that are often requested in conjunction with field campaigns. Whenever this occurs, one or more lines of data are dropped while the computer resets and readies itself for accepting new data. Although this type of data loss is minuscule compared to the total amount of measurements acquired, and is marginal for atmospheric studies dealing with large areas and long periods of time, this outcome can be crippling for land surface studies that focus on the detailed analysis of particular scenes at specific times. This paper describes the problem, reports on the prevalence of missing data, proposes a practical solution to optimally estimate the values of the missing data and provides evidence of the performance of the algorithm through specific examples in South Africa. The software to process MISR L1B2 GRP data products as described here is openly available to the community from the GitHub web site https://github.com/mmverstraete or https://doi.org/10.5281/zenodo.3519989.

scholarly journals Replacing missing values in the standard Multi-angle Imaging SpectroRadiometer (MISR) radiometric camera-by-camera cloud mask (RCCM) data product

2020 ◽  
Vol 12 (1) ◽  
pp. 611-628 ◽  
Author(s):  
Michel M. Verstraete ◽  
Linda A. Hunt ◽  
Hugo De Lemos ◽  
Larry Di Girolamo
Keyword(s):  
Missing Values ◽  
Near Infrared ◽  
Data Repository ◽  
Observation Data ◽  
Science Data ◽  
Data Services ◽  
Data Product ◽  
Spectral Bands ◽  
Earth Observation Data ◽  
Cloud Mask

Abstract. The Multi-angle Imaging SpectroRadiometer (MISR) is one of the five instruments hosted on board the NASA Terra platform, launched on 18 December 1999. This instrument has been operational since 24 February 2000 and is still acquiring Earth observation data as of this writing. The primary mission of the MISR is to document the state and properties of the atmosphere, in particular the clouds and aerosols it contains, as well as the planetary surface, on the basis of 36 data channels collectively gathered by its nine cameras (pointing in different directions along the orbital track) in four spectral bands (blue, green, red and near-infrared). The radiometric camera-by-camera cloud mask (RCCM) is derived from the calibrated measurements at the nominal top of the atmosphere and is provided separately for each of the nine cameras. This RCCM data product is permanently archived at the NASA Atmospheric Science Data Center (ASDC) in Hampton, VA, USA, and is openly accessible (Diner et al., 1999b, and https://doi.org/10.5067/Terra/MISR/MIRCCM_L2.004). For various technical reasons described in this paper, this RCCM product exhibits missing data, even though an estimate of the clear or cloudy status of the environment at each individual observed location can be deduced from the available measurements. The aims of this paper are (1) to describe how to replace over 99 % of the missing values by estimates and (2) to briefly describe the software to replace missing RCCM values, which is openly available to the community from the GitHub website, https://github.com/mmverstraete/MISR\\ RCCM/ (last access: 12 March 2020), or https://doi.org/10.5281/ZENODO.3240017 (Verstraete, 2019e). Two additional sets of resources are also made available on the research data repository of GFZ Data Services in conjunction with this paper. The first set (A; Verstraete et al., 2020; https://doi.org/10.5880/fidgeo.2020.004) includes three items: (A1) a compressed archive, RCCM_Out.zip, containing all intermediary, final and ancillary outputs created while generating the figures of this paper; (A2) a user manual, RCCM_Out.pdf, describing how to install, uncompress and explore those files; and (A3) a separate input MISR data archive, RCCM_input_68050.zip, for Path 168, Orbit 68050. This latter archive is usable with (B), the second set (Verstraete and Vogt, 2020; https://doi.org/10.5880/fidgeo.2020.008), which includes (B1), a stand-alone, self-contained, executable version of the RCCM correction codes, RCCM_Soft_Win.zip, using the IDL Virtual Machine technology that does not require a paid IDL license, as well as (B2), a user manual, RCCM_Soft_Win.pdf, to explain how to install, uncompress and use this software.

scholarly journals Terrain-Based Shadow Correction Method for Assessing Supraglacial Features on the Greenland Ice Sheet

2021 ◽  
Vol 2 ◽  
Author(s):  
Sasha. Z. Leidman ◽  
Åsa K. Rennermalm ◽  
Richard G. Lathrop ◽  
Matthew. G. Cooper
Keyword(s):  
Land Surface ◽  
Greenland Ice Sheet ◽  
Correction Method ◽  
Correction Coefficient ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Sediment Cover ◽  
Elevation Model ◽  
Uav Images ◽  
Gis Software

The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.

scholarly journals The Retrieval of Land Surface Pressure from MERIS Measurements in the Oxygen A Band

2009 ◽  
Vol 26 (7) ◽  
pp. 1367-1377 ◽  
Author(s):  
Rasmus Lindstrot ◽  
Rene Preusker ◽  
Jürgen Fischer
Keyword(s):  
Surface Pressure ◽  
Land Surface ◽  
Sea Level Pressure ◽  
Imaging Spectrometer ◽  
Medium Resolution ◽  
Digital Elevation ◽  
Sensitivity Studies ◽  
Ice Surfaces ◽  
Elevation Model ◽  
Digital Elevation Model Data

Abstract Measurements of the Medium-Resolution Imaging Spectrometer (MERIS) on the Environmental Satellite (Envisat) are used for the retrieval of surface pressure above land and ice surfaces. The algorithm is based on the exploitation of gaseous absorption in the oxygen A band at 762 nm. The strength of absorption is directly related to the average photon pathlength, which in clear-sky cases above bright surfaces is mainly determined by the surface pressure, with minor influences from scattering at aerosols. Sensitivity studies regarding the influences of aerosol optical thickness and scale height and the temperature profile on the measured radiances are presented. Additionally, the sensitivity of the retrieval to the accuracy of the spectral characterization of MERIS is quantified. The algorithm for the retrieval of surface pressure (SPFUB) is presented and validated against surface pressure maps constructed from ECMWF sea level pressure forecasts in combination with digital elevation model data. The accuracy of SPFUB was found to be within 10 hPa above ice surfaces at Greenland and 15 hPa above desert and mountain scenes in northern Africa and southwest Asia. In a case study above Greenland the accuracy of SPFUB could be enhanced to be better than 3 hPa by spatial averaging over areas of 40 km × 40 km.

scholarly journals Watershed Management for Ingrul village in Sangli District, Maharashtra by using GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 1593-1599
Keyword(s):  
Watershed Management ◽  
Cost Estimation ◽  
Land Surface ◽  
Watershed Modeling ◽  
Project Work ◽  
Bottom Surface ◽  
Monsoon Period ◽  
Digital Elevation ◽  
Using Data ◽  
Elevation Model

Watershed is land surface bounded by a divide which contributes runoff to a common point. Watershed management basically involves management of land surface and vegetation so as to conserve and utilize maximum water that falls on the area of watershed and also conserve the soil for long term benefits to the farmer and his society. Watershed management implies the wise use of soil and water resources so as to provide clean, uniform water supply for beneficial use and to control damaging overflow. Study area for this project work is Ingrul village, which is comes in Shirala tehsil, Sangli district of Maharashtra state. This area lies between Latitude 16.9550N, Longitude 74.1585E and Elevation 587 m. In ingrul village in pre-monsoon period lack of water availability for drinking, agricultural purpose. Due to the water scarcity the agricultural production is reduced. To reduce the problem of water, watershed management is necessary in the Ingrul village. Watershed studies conducted employing a GIS platform have incontestable that the special analysis capabilities of GIS hold the key to improved watershed modeling techniques. The GIS-based watershed modeling method begins with a digital illustration of the bottom surface topography, or a digital elevation model. Availability of natural resources like land and water is studied using data from bhuvan, Survey of India toposheets and remote sensed data. Watershed structures proposed on the basis of contour map, drainage map, land use land pattern map and water requirement and runoff calculations. Design and cost estimation of structures recommended for Ingrul village

scholarly journals Identifying and Predicting the Geographical Distribution Patterns of Oncomelania hupensis

2019 ◽  
Vol 16 (12) ◽  
pp. 2206 ◽  
Author(s):  
Niu ◽  
Li ◽  
Qiu ◽  
Xu ◽  
Huang ◽  
...  
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Distribution Patterns ◽  
Oncomelania Hupensis ◽  
Spatial And Temporal Patterns ◽  
Jianghan Plain ◽  
Coverage Area ◽  
Digital Elevation ◽  
Elevation Model

Schistosomiasis is a snail-borne parasitic disease endemic to the tropics and subtropics, whose distribution depends on snail prevalence as determined by climatic and environmental factors. Here, dynamic spatial and temporal patterns of Oncomelania hupensis distributions were quantified using general statistics, global Moran’s I, and standard deviation ellipses, with Maxent modeling used to predict the distribution of habitat areas suitable for this snail in Gong’an County, a severely affected region of Jianghan Plain, China, based on annual average temperature, humidity of the climate, soil type, normalized difference vegetation index, land use, ditch density, land surface temperature, and digital elevation model variables; each variable’s contribution was tested using the jackknife method. Several key results emerged. First, coverage area of O. hupensis had changed little from 2007 to 2012, with some cities, counties, and districts alternately increasing and decreasing, with ditch and bottomland being the main habitat types. Second, although it showed a weak spatial autocorrelation, changing negligibly, there was a significant east–west gradient in the O. hupensis habitat area. Third, 21.9% of Gong’an County’s area was at high risk of snail presence; and ditch density, temperature, elevation, and wetting index contributed most to their occurrence. Our findings and methods provide valuable and timely insight for the control, monitoring, and management of schistosomiasis in China.

scholarly journals An Improved Approach for Downscaling Coarse-Resolution Thermal Data by Minimizing the Spatial Averaging Biases in Random Forest

2020 ◽  
Vol 12 (21) ◽  
pp. 3507
Author(s):  
Sammy M. Njuki ◽  
Chris M. Mannaerts ◽  
Zhongbo Su
Keyword(s):  
Random Forest ◽  
Land Surface ◽  
Spatial Averaging ◽  
Complex Environments ◽  
Spatial And Temporal Scales ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Thermal Data ◽  
Geophysical Processes ◽  
Elevation Model

Land surface temperature (LST) plays a fundamental role in various geophysical processes at varying spatial and temporal scales. Satellite-based observations of LST provide a viable option for monitoring the spatial-temporal evolution of these processes. Downscaling is a widely adopted approach for solving the spatial-temporal trade-off associated with satellite-based observations of LST. However, despite the advances made in the field of LST downscaling, issues related to spatial averaging in the downscaling methodologies greatly hamper the utility of coarse-resolution thermal data for downscaling applications in complex environments. In this study, an improved LST downscaling approach based on random forest (RF) regression is presented. The proposed approach addresses issues related to spatial averaging biases associated with the downscaling model developed at the coarse resolution. The approach was applied to downscale the coarse-resolution Satellite Application Facility on Land Surface Analysis (LSA-SAF) LST product derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor aboard the Meteosat Second Generation (MSG) weather satellite. The LSA-SAF product was downscaled to a spatial resolution of ~30 m, based on predictor variables derived from Sentinel 2, and the Advanced Land Observing Satellite (ALOS) digital elevation model (DEM). Quantitatively and qualitatively, better downscaling results were obtained using the proposed approach in comparison to the conventional approach of downscaling LST using RF widely adopted in LST downscaling studies. The enhanced performance indicates that the proposed approach has the ability to reduce the spatial averaging biases inherent in the LST downscaling methodology and thus is more suitable for downscaling applications in complex environments.

scholarly journals EFFECT OF DIGITAL ELEVATION MODEL MESH SIZE ON GEOMORPHIC INDICES: A CASE STUDY OF THE IVAÍ RIVER WATERSHED - STATE OF PARANÁ, BRAZIL

2017 ◽  
Vol 23 (4) ◽  
pp. 684-699 ◽  
Author(s):  
Vanessa Cristina Dos Santos ◽  
Mhamad El Hage ◽  
Laurent Polidori ◽  
José Cândido Stevaux
Keyword(s):  
Land Surface ◽  
Quantitative Description ◽  
Mesh Size ◽  
Order Stream ◽  
Common Procedure ◽  
Geomorphic Indices ◽  
Full Resolution ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact

Abstract: Geomorphometry is the science of quantitative description of land surface morphology by the mean of geomorphic indices extracted from Digital Elevation Models (DEMs). The analysis of these indices is the first and most common procedure performed in several geoscience-related subjects. This study aims to assess the impact of mesh size degradation on different local and regional geomorphic indices extracted for GDEM and TOPODATA DEMs. Thus, these DEMs, having a mesh size of 30 m, were subsampled to 60, 120 and 240 m and then geomorphic indices were calculated using the full resolution DEM and the subsampled ones. Depending on their behavior, these indices are then classified into stable and unstable. The results show that the most affected indices are slope and hydrographic indices such as Strahler order, stream sinuosity and fractal dimension and watershed perimeter, whereas elevation remains stable. It also shows that the effect depends on the presence of the canopy and geological structures in the studied area.

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