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 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 Geomorphometric analysis of cave ceiling channels mapped with 3D terrestrial laser scanning

2016 ◽  
Author(s):  
Michal Gallay ◽  
Zdenko Hochmuth ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka
Keyword(s):  
Laser Scanning ◽  
Methodological Approach ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Scalar Fields ◽  
Complex Environments ◽  
Digital Elevation ◽  
Unique Manner ◽  
Elevation Model ◽  
Different Levels

Abstract. The change of hydrological conditions during the evolution of caves in carbonate rocks often results in a complex subterranean geomorphology which comprises specific landforms such as ceiling channels, anastomosing half tubes, or speleothems organised vertically in different levels. Studying such complex environments traditionally requires tedious mapping, however, this is being replaced with terrestrial laser scanning technology. Laser scanning overcomes the problem of reaching high ceilings providing new options to map underground landscapes with unprecedented level of detail and accuracy. The acquired point cloud can be handled conveniently with dedicated software, but applying traditional geomorphometry to analyse the cave surface is limited. This is because geomorphometry has been focused on parameterisation and analysis of surficial terrain. The theoretical and methodological concept has been based on two-dimensional scalar fields which is sufficient for most cases of the surficial terrain. The terrain surface is modelled with a bivariate function of altitude (elevation) and represented by a raster digital elevation model. However, the cave is a three-dimensional entity therefore a different approach is required for geomorphometric analysis. In this paper, we demonstrate the benefits of high resolution cave mapping and 3-D modelling to better understand the palaeohydrography of the Domica cave in Slovakia. This methodological approach adopted traditional geomorphometric methods in a unique manner and also new methods used in 3D computer graphics which can be applied to study other 3-D geomorphological forms

scholarly journals Geomorphometric analysis of cave ceiling channels mapped with 3-D terrestrial laser scanning

2016 ◽  
Vol 20 (5) ◽  
pp. 1827-1849 ◽  
Author(s):  
Michal Gallay ◽  
Zdenko Hochmuth ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka
Keyword(s):  
Laser Scanning ◽  
Methodological Approach ◽  
Terrestrial Laser Scanning ◽  
Scalar Fields ◽  
Complex Environments ◽  
New Methods ◽  
Digital Elevation ◽  
Unique Manner ◽  
Elevation Model ◽  
Different Levels

Abstract. The change of hydrological conditions during the evolution of caves in carbonate rocks often results in a complex subterranean geomorphology, which comprises specific landforms such as ceiling channels, anastomosing half tubes, or speleothems organized vertically in different levels. Studying such complex environments traditionally requires tedious mapping; however, this is being replaced with terrestrial laser scanning technology. Laser scanning overcomes the problem of reaching high ceilings, providing new options to map underground landscapes with unprecedented level of detail and accuracy. The acquired point cloud can be handled conveniently with dedicated software, but applying traditional geomorphometry to analyse the cave surface is limited. This is because geomorphometry has been focused on parameterization and analysis of surficial terrain. The theoretical and methodological concept has been based on two-dimensional (2-D) scalar fields, which are sufficient for most cases of the surficial terrain. The terrain surface is modelled with a bivariate function of altitude (elevation) and represented by a raster digital elevation model. However, the cave is a 3-D entity; therefore, a different approach is required for geomorphometric analysis. In this paper, we demonstrate the benefits of high-resolution cave mapping and 3-D modelling to better understand the palaeohydrography of the Domica cave in Slovakia. This methodological approach adopted traditional geomorphometric methods in a unique manner and also new methods used in 3-D computer graphics, which can be applied to study other 3-D geomorphological forms.

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 Prediction of soil classes in a complex landscape in Southern Brazil

2019 ◽  
Vol 54 ◽  
Author(s):  
Jean Michel Moura-Bueno ◽  
Ricardo Simão Diniz Dalmolin ◽  
Taciara Zborowski Horst-Heinen ◽  
Luciano Campos Cancian ◽  
Ricardo Bergamo Schenato ◽  
...  
Keyword(s):  
Random Forest ◽  
Prediction Models ◽  
Expert Knowledge ◽  
Model Performance ◽  
Spatial Prediction ◽  
Support Vector ◽  
Kappa Index ◽  
Digital Elevation ◽  
Complex Landscape ◽  
Elevation Model

Abstract: The objective of this work was to evaluate the use of covariate selection by expert knowledge on the performance of soil class predictive models in a complex landscape, in order to identify the best predictive model for digital soil mapping in the Southern region of Brazil. A total of 164 points were sampled in the field using the conditioned Latin hypercube, considering the covariates elevation, slope, and aspect. From the digital elevation model, environmental covariates were extracted, composing three sets, made up of: 21 covariates, covariates after the exclusion of the multicollinear ones, and covariates chosen by expert knowledge. Prediction was performed with the following models: decision tree, random forest, multiple logistic regression, and support vector machine. The accuracy of the models was evaluated by the kappa index (K), general accuracy (GA), and class accuracy. The prediction models were sensitive to the disproportionate sampling of soil classes. The best predicted map achieved a GA of 71% and K of 0.59. The use of the covariate set chosen by expert knowledge improves model performance in predicting soil classes in a complex landscape, and random forest is the best model for the spatial prediction of soil classes.

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.

Impacts of coarse-resolution soil maps and high-resolution digital-elevation-model-generated attributes on modelling forest soil zinc and copper

2021 ◽  
pp. 1-16
Author(s):  
Zhengyong Zhao ◽  
Qi Yang ◽  
Xiaogang Ding ◽  
Zisheng Xing
Keyword(s):  
High Resolution ◽  
Forest Soil ◽  
Digital Elevation Model ◽  
Cross Validation ◽  
Large Area ◽  
Coarse Resolution ◽  
Digital Elevation ◽  
Ann Models ◽  
Elevation Model ◽  
Fold Cross Validation

The depth-specific zinc (Zn) and copper (Cu) maps with high resolution (i.e., ≤10 m) are important for soil and forest management and conservation. The objective of this study was to assess the effects of easily accessible model inputs, i.e., existing coarse-resolution parent material, pH, and soil texture maps with 1:1 800 000–2 800 000 scale and nine digital elevation model (DEM)-generated terrain attributes with 10 m resolution, on modelling Zn and Cu distributions of forest soil over a large area (e.g., thousands of km2). A total of 511 artificial neural network (ANN) models for each depth (20 cm increments to 100 cm) were built and evaluated by a 10-fold cross-validation with 385 soil profiles from the Yunfu forest, South China, about 4915 km2 areas. The results indicated that the optimal models for five depths engaged five to seven DEM-generated attributes together with three coarse-resolution soil attributes as inputs, respectively, and accuracies for estimating Zn and Cu varied with R2 of 0.76–0.85 and relative overall accuracy ±10% of 74%–86%. The produced maps showed that DEM-generated sediment delivery ratio, topographic position index (TPI), and aspect were the most important attributes for predicting Cu, but flow length, TPI, and slope were for Zn, which heavily affected Zn and Cu distributions in detail. Boundaries of three coarse-resolution maps were still visible in the generated maps indicated that the maps affected the distributions of Zn and Cu in large scales. Thus, the modelling method, i.e., developing ANN models with k-fold cross-validation, can be used to map high-resolution Zn and Cu over a large area.

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