scholarly journals Combining Historical Remote Sensing, Digital Soil Mapping and Hydrological Modelling to Produce Solutions for Infrastructure Damage in Cosmo City, South Africa

2020 ◽  
Vol 12 (3) ◽  
pp. 433 ◽  
Author(s):  
George van Zijl ◽  
Johan van Tol ◽  
Darren Bouwer ◽  
Simon Lorentz ◽  
Pieter le Roux
Keyword(s):  
South Africa ◽  
Remote Sensing ◽  
Structural Damage ◽  
Kappa Statistic ◽  
Hydrological Modelling ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Soil Map ◽  
Structural Impacts ◽  
The Impact

Urbanization and hydrology have an interactive relationship, as urbanization changing the hydrology of a system and the hydrology commonly causing structural damage to the infrastructure. Hydrological modelling has been used to quantify the water causing structural impacts, and to provide solutions to the issues. However, in already-urbanized areas, creating a soil map to use as input in the modelling process is difficult, as observation positions are limited and visuals of the natural vegetation which indicate soil distribution are unnatural. This project used historical satellite images in combination with terrain parameters and digital soil mapping methods to produce an accurate (Kappa statistic = 0.81) hydropedology soil map for the Cosmo City suburb in Johannesburg, South Africa. The map was used as input into the HYDRUS 2D and SWAT hydrological models to quantify the water creating road damage at Kampala Crescent, a road within Cosmo City (using HYDRUS 2D), as well as the impact of urbanization on the hydrology of the area (using SWAT). HYDRUS 2D modelling showed that a subsurface drain installed at Kampala Crescent would need a carrying capacity of 0.3 m3·h−1·m−1 to alleviate the road damage, while SWAT modelling shows that surface runoff in Cosmo City will commence with as little rainfall as 2 mm·month−1. This project showcases the value of multidisciplinary work. The remote sensing was invaluable to the mapping, which informed the hydrological modelling and subsequently provided answers to the engineers, who could then mitigate the hydrology-related issues within Cosmo City.

Regional characterisation of soil properties by combining soil science and hyperspectral and thermal remote sensing: A technical overview of lab and field remote sensing methods

2021 ◽  
Author(s):  
Richard Mommertz ◽  
Lars Konen ◽  
Martin Schodlok
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Regional Scale ◽  
Arable Land ◽  
Soil Mapping ◽  
Soil Science ◽  
Near Surface ◽  
Soil Parameter ◽  
The Impact ◽  
Parameter Retrieval

<p>Soil is one of the world’s most important natural resources for human livelihood as it provides food and clean water. Therefore, its preservation is of huge importance. For this purpose, a proficient regional database on soil properties is needed. The project “ReCharBo” (Regional Characterisation of Soil Properties) has the objective to combine remote sensing, geophysical and pedological methods to determine soil characteristics on a regional scale. Its aim is to characterise soils non-invasive, time and cost efficient and with a minimal number of soil samples to calibrate the measurements. Konen et al. (2021) give detailed information on the research concept and first field results in a presentation in the session “SSS10.3 Digital Soil Mapping and Assessment”. Hyperspectral remote sensing is a powerful and well known technique to characterise near surface soil properties. Depending on the sensor technology and the data quality, a wide variety of soil properties can be derived with remotely sensed data (Chabrillat et al. 2019, Stenberg et al. 2010). The project aims to investigate the effects of up and downscaling, namely which detail of information is preserved on a regional scale and how a change in scales affects the analysis algorithms and the possibility to retrieve valid soil parameter information. Thus, e.g. laboratory and field spectroscopy are applied to gain information of samples and fieldspots, respectively. Various UAV-based sensors, e.g. thermal & hyperspectral sensors, are applied to study soil properties of arable land in different study areas at field scale. Finally, airborne (helicopter) hyperspectral data will cover the regional scale. Additionally forthcoming spaceborne hyperspectral satellite data (e.g. Prisma, EnMAP, Sentinel-CHIME) are a promising outlook to gain detailed regional soil information. In this context it will be discussed how the multisensor data acquisition is best managed to optimise soil parameter retrieval. Sensor specific properties regarding time and date of acquisition as well as weather/atmospheric conditions are outlined. The presentation addresses and discusses the impact of a multisensor and multiscale remote sensing data collection regarding the results on soil parameter retrieval.</p><p> </p><p>References</p><p>Chabrillat, S., Ben-Dor, E. Cierniewski, J., Gomez, C., Schmid, T. & van Wesemael, B. (2019): Imaging Spectroscopy for Soil Mapping and Monitoring. Surveys in Geophysics 40:361–399. https://doi.org/10.1007/s10712-019-09524-0</p><p>Stenberg, B., Viscarra Rossel, R. A., Mounem Mouazen, A. & Wetterlind, J. (2010): Visible and Near Infrared Spectroscopy in Soil Science. In: Donald L. Sparks (editor): Advances in Agronomy. Vol. 107. Academic Press:163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7</p>

scholarly journals An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

2013 ◽  
Vol 37 (2) ◽  
pp. 359-366 ◽  
Author(s):  
Alexandre ten Caten ◽  
Ricardo Simão Diniz Dalmolin ◽  
Fabrício de Araújo Pedron ◽  
Luis Fernando Chimelo Ruiz ◽  
Carlos Antônio da Silva
Keyword(s):  
Rio Grande ◽  
Northern Region ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Digital Information ◽  
Rio Grande Do Sul ◽  
Predictive Capacity ◽  
Data Set ◽  
Data Volume ◽  
The Impact

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

scholarly journals Análise da eficiência dos métodos indiretos para o mapeamento de solos frente às técnicas diretas, e suas possíveis associações: Uma revisão metodológica.

2020 ◽  
Vol 13 (2) ◽  
pp. 487
Author(s):  
José Gustavo Da Silva Nunes ◽  
Rogério Uagoda
Keyword(s):  
Remote Sensing ◽  
Low Cost ◽  
Microwave Frequency ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Indirect Methods ◽  
Gis And Remote Sensing ◽  
Radar Images ◽  
Cost Efficient ◽  
Landscape Information

Este artigo se trata de uma revisão metodológica de técnicas indiretas de mapeamento pedológico, envolvendo ensaios granulométricos, SIG e sensoriamento remoto dentro do mapeamento digital de solos, espectrorradiometria e Georadar (GPR), comparados e/ou associados às técnicas diretas como coleta, descrição de trincheiras ou perfis, análise da paisagem. O mapeamento digital de solos (MDS) vem se provando com uma ferramenta eficiente desde o início do ano 2000, associadas a outros métodos como o sensoriamento remoto e análises laboratoriais, o MDS forneceu ao mundo mapas que representam bem a realidade dos solos. Mas as técnicas diretas ainda são usuais e eficientes, e podem ser associadas aos métodos indiretos, para que o mapeamento de uma pequena área possa ser espalhado regionalmente. A busca por técnicas de baixo custo, eficiência e praticidade tem levado pesquisadores a buscarem técnicas como o Georradar para verificar a profundidade do solo, sem que seja necessário a destruição de perfis por meio da abertura de trincheiras, como também ao uso de imagens de radar capaz de oferecer um produto de alta resolução espacial, independentemente da altitude da plataforma, e que tem auxiliado na extração de diversas informações da paisagem diretamente ligadas à pedogênese. Esta pesquisa tem o intuito de buscar a evolução do mapeamento pedológico através das diversas técnicas citadas, e bem como a associação entre os diversos métodos para gerar um mapa de solos de alta precisão. Efficiency analysis of indirect methods for soil mapping against direct techniques, and their possible associations: A methodological reviewA B S T R A C TThis article is a methodological review of indirect techniques of pedological mapping, GIS and remote sensing within digital soil mapping, spectroradiometry and Georadar (GPR), compared to landscape analysis. Research has shown that digital soil mapping (MDS) has been an efficient tool since the beginning of the year 2000, combined with other methods such as remote sensing and laboratory analysis, MDS has provided the world with maps that represent the reality of soils well. But direct techniques are still common and efficient, and can be associated with indirect methods, so that local mapping information can be dispersed regionally. The search for low-cost, efficient and practical techniques has led researchers to look for techniques such as Georadar to check the depth of the soil, without the need to destroy profiles by opening trenches, as well as using radar images. which provide a high spatial resolution product, regardless of the platform's altitude, and which has helped in the extraction of various landscape information directly linked to pedogenesis. Spectroradiometry is a methodology that works with the measurement of radiant electromagnetic energy, and allows for quick associations between targets and spectral curves, allowing the creation of global libraries of these curves. Radiometry in turn has been widely used in systems that operate in the microwave frequency range, ranging from 1mm to 1m in length, and allow you to locate objects. This research aims to seek the evolution of pedological mapping through the various techniques mentioned, as well as the association between the various methods to generate a highly accurate soil map.Keywords: Soil Mapping; GPR; Spectroradiometry; Orbital Sensors

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