scholarly journals The Rapid Method of Soil Identification Based on Remote Sensing and Geographic Information Systems (Case Study of Moramo Watershed)

Land Science ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. p12
Author(s):  
Jufri Karim ◽  
Totok Gunawan ◽  
Tukidal Yunianto ◽  
Hasbullah Syaf ◽  
Syamsu Alam
Keyword(s):  
Land Use ◽  
Soil Analysis ◽  
Mineral Soil ◽  
Image Data ◽  
Soil Classification ◽  
Histogram Equalization ◽  
Geographic Information ◽  
Soil Taxonomy ◽  
Composite Image

The field-tested samples are done by stratified random sampling. Soil classification was obtained through observation of field profile morphology and soil analysis in the laboratory followed by supporting data such as temperature and rainfall. The Moramo River Basin (DAS) was used as the location of the case study in this experiment by observing 13 soil profiles. Soil properties and characteristics were observed for soil texture, clay mineral, soil pH (H2O and KCl), soil cation, saturation bases, and C-organic.  The soil naming was done to subgroup category based on Soil Taxonomy System in 2010 and paired with the land classification system of Soil Research Center in 1983, and WRB-FAO in 2006. The result showed that the accuracy of landform interpretation 89.6%, rocks 92.19%, accuracy of land use interpretation 90.63%, and accuracy of soil mapping 90.00%, so that the image ALOS AVNIR-2 can be utilized well to obtain parameter of the land unit for land mapping. The result of image data processing through RGB 341 composite image showed a high unidirectional frequency filter, histogram equalization, and analyzed with Geographic Information System, 15 units of landform, five-rock units. nine land-use units and 11 sub-soil sub-groups were obtained. The results of the soil classification in the Moramo Watershed (DAS) region in the subgroup category obtained 11 subgroups of land consisting of Lithic Udorthents, Typic Udifluvents, Aeric Endoaquents, Typic Fluvaquents, Typic Dystrudepts, Typic Eutrudepts, Ruptic-Alfic Eutrudepts, Lithic Dystrudepts, Oxyaquic Eutrudepts, Fluvaquentic Epiaquepts, Typic Endoaquepts.

LAND USE TYPES AND SOIL CHARACTERISTICTS: A CASE STUDY IN HUONG VINH COMMUNE, HUONG TRA TOWN, THUA THIEN HUE PROVINCE

2017 ◽  
Vol 126 (4B) ◽  
Author(s):  
Trần Thanh Đức
Keyword(s):  
Land Use ◽  
Sweet Potato ◽  
Soil Analysis ◽  
Soil Characteristics ◽  
Low Ph ◽  
Clay Loam ◽  
Total N ◽  
Land Use Types ◽  
Total P

This research carried out in Huong Vinh commune, Huong Tra town, Thua Thien Hue province aimed to identify types of land use and soil characteristics. Results showed that five crops are found in Huong Vinh commune including rice, peanut, sweet potato, cassava and vegetable. There are two major soil orders with four soil suborders classified by FAO in Huong Vinh commune including Fluvisols (Dystric Fluvisols<em>, </em>Gleyic Fluvisols and Cambic Fluvisols) and Arenosols (Haplic Arenosols). The results from soil analysis showed that three soil suborders including Dystric Fluvisols<em>, </em>Gleyic Fluvisols and Cambic Fluvisols belonging to Fluvisols were clay loam in texture, low pH, low in OC, total N, total P<sub>2</sub>O<sub>5</sub> and total K<sub>2</sub>O. Meanwhile, the Haplic Arenosols was loamy sand in texture, poor capacity to hold OC, total N, total P<sub>2</sub>O<sub>5</sub> and total K<sub>2</sub>O

scholarly journals High-quality observation of surface imperviousness for urban runoff modelling using UAV imagery

2015 ◽  
Vol 19 (10) ◽  
pp. 4215-4228 ◽  
Author(s):  
P. Tokarczyk ◽  
J. P. Leitao ◽  
J. Rieckermann ◽  
K. Schindler ◽  
F. Blumensaat
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Surface Runoff ◽  
Urban Areas ◽  
Image Data ◽  
Aerial Images ◽  
Urban Drainage ◽  
High Quality ◽  
Modern Classification

Abstract. Modelling rainfall–runoff in urban areas is increasingly applied to support flood risk assessment, particularly against the background of a changing climate and an increasing urbanization. These models typically rely on high-quality data for rainfall and surface characteristics of the catchment area as model input. While recent research in urban drainage has been focusing on providing spatially detailed rainfall data, the technological advances in remote sensing that ease the acquisition of detailed land-use information are less prominently discussed within the community. The relevance of such methods increases as in many parts of the globe, accurate land-use information is generally lacking, because detailed image data are often unavailable. Modern unmanned aerial vehicles (UAVs) allow one to acquire high-resolution images on a local level at comparably lower cost, performing on-demand repetitive measurements and obtaining a degree of detail tailored for the purpose of the study. In this study, we investigate for the first time the possibility of deriving high-resolution imperviousness maps for urban areas from UAV imagery and of using this information as input for urban drainage models. To do so, an automatic processing pipeline with a modern classification method is proposed and evaluated in a state-of-the-art urban drainage modelling exercise. In a real-life case study (Lucerne, Switzerland), we compare imperviousness maps generated using a fixed-wing consumer micro-UAV and standard large-format aerial images acquired by the Swiss national mapping agency (swisstopo). After assessing their overall accuracy, we perform an end-to-end comparison, in which they are used as an input for an urban drainage model. Then, we evaluate the influence which different image data sources and their processing methods have on hydrological and hydraulic model performance. We analyse the surface runoff of the 307 individual subcatchments regarding relevant attributes, such as peak runoff and runoff volume. Finally, we evaluate the model's channel flow prediction performance through a cross-comparison with reference flow measured at the catchment outlet. We show that imperviousness maps generated from UAV images processed with modern classification methods achieve an accuracy comparable to standard, off-the-shelf aerial imagery. In the examined case study, we find that the different imperviousness maps only have a limited influence on predicted surface runoff and pipe flows, when traditional workflows are used. We expect that they will have a substantial influence when more detailed modelling approaches are employed to characterize land use and to predict surface runoff. We conclude that UAV imagery represents a valuable alternative data source for urban drainage model applications due to the possibility of flexibly acquiring up-to-date aerial images at a quality compared with off-the-shelf image products and a competitive price at the same time. We believe that in the future, urban drainage models representing a higher degree of spatial detail will fully benefit from the strengths of UAV imagery.

scholarly journals High-quality observation of surface imperviousness for urban runoff modelling using UAV imagery

2015 ◽  
Vol 12 (1) ◽  
pp. 1205-1245 ◽  
Author(s):  
P. Tokarczyk ◽  
J. P. Leitao ◽  
J. Rieckermann ◽  
K. Schindler ◽  
F. Blumensaat
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Surface Runoff ◽  
Urban Areas ◽  
Image Data ◽  
Aerial Images ◽  
Urban Drainage ◽  
High Quality ◽  
Modern Classification

Abstract. Modelling rainfall–runoff in urban areas is increasingly applied to support flood risk assessment particularly against the background of a changing climate and an increasing urbanization. These models typically rely on high-quality data for rainfall and surface characteristics of the area. While recent research in urban drainage has been focusing on providing spatially detailed rainfall data, the technological advances in remote sensing that ease the acquisition of detailed land-use information are less prominently discussed within the community. The relevance of such methods increase as in many parts of the globe, accurate land-use information is generally lacking, because detailed image data is unavailable. Modern unmanned air vehicles (UAVs) allow acquiring high-resolution images on a local level at comparably lower cost, performing on-demand repetitive measurements, and obtaining a degree of detail tailored for the purpose of the study. In this study, we investigate for the first time the possibility to derive high-resolution imperviousness maps for urban areas from UAV imagery and to use this information as input for urban drainage models. To do so, an automatic processing pipeline with a modern classification method is tested and applied in a state-of-the-art urban drainage modelling exercise. In a real-life case study in the area of Lucerne, Switzerland, we compare imperviousness maps generated from a consumer micro-UAV and standard large-format aerial images acquired by the Swiss national mapping agency (swisstopo). After assessing their correctness, we perform an end-to-end comparison, in which they are used as an input for an urban drainage model. Then, we evaluate the influence which different image data sources and their processing methods have on hydrological and hydraulic model performance. We analyze the surface runoff of the 307 individual subcatchments regarding relevant attributes, such as peak runoff and volume. Finally, we evaluate the model's channel flow prediction performance through a cross-comparison with reference flow measured at the catchment outlet. We show that imperviousness maps generated using UAV imagery processed with modern classification methods achieve accuracy comparable with standard, off-the-shelf aerial imagery. In the examined case study, we find that the different imperviousness maps only have a limited influence on modelled surface runoff and pipe flows. We conclude that UAV imagery represents a valuable alternative data source for urban drainage model applications due to the possibility to flexibly acquire up-to-date aerial images at a superior quality and a competitive price. Our analyses furthermore suggest that spatially more detailed urban drainage models can even better benefit from the full detail of UAV imagery.

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