scholarly journals Digital mapping of a soil profile

2018 ◽  
Vol 70 (1) ◽  
pp. 27-41 ◽  
Author(s):  
Y. Zhang ◽  
A. E. Hartemink
Keyword(s):  
Soil Profile ◽  
Digital Mapping

KARAKTERISTIK TANAH DAN PERBANDINGAN PRODUKSI KELAPA SAWIT (Elaeis guineensis Jacq.) DENGAN METODE TANAM LUBANG BESAR DAN PARIT DRAINASE 2:1 PADA LAHAN SPODOSOL DI KABUPATEN BARITO TIMUR PROPINSI KALIMANTAN TENGAH - INDONESIA

2015 ◽  
Vol 2 (2) ◽  
pp. 148-158
Author(s):  
Surianto
Keyword(s):  
Soil Texture ◽  
Oil Palm ◽  
Soil Profile ◽  
Chemical Properties ◽  
Exchangeable Cations ◽  
Soil Horizon ◽  
Soil Profiles ◽  
Negative Effect ◽  
Hole Profile ◽  
And Chemical Properties

Spodosol soil of Typic Placorthod sub-group of East Barito District is one of the problem soils with the presence of hardpan layer, low fertility, low water holding capacity, acid reaction and it is not suitable for oil palm cultivation without any properly specific management of land preparation and implemented best agronomic practices. A study was carried out to evaluate the soil characteristic of a big hole (A profile) and no big hole (B profile) system and comparative oil palm productivity among two planting systems. This study was conducted in Spodosol soil at oil palm plantation (coordinate X = 0281843 and Y = 9764116), East Barito District, Central Kalimantan Province on February 2014, by surveying of placic and ortstein depth and observing soil texture and chemical properties of 2 (two) oil palm's soil profiles that have been planted in five years. Big hole system of commercial oil palm field planting on the Spodosol soil area was designed for the specific purpose of minimizing the potential of a negative effect of shallow effective planting depth for oil palms growing due to the hardpan layer (placic and ortstein) presence as deep as 0.25 - 0.50 m. The big hole system is a planting hole type which was vertical-sided with 2.00 m x 1.50 m on top and bottom side and 3.00 m depth meanwhile the 2:1 drain was vertical-sided also with 1.50 m depth and 300 m length. Oil palm production was recorded from the year 2012 up to 2014. Results indicated that the fractions both big hole profile (A profile) and no big hole profile (B profile) were dominated by sands ranged from 60% to 92% and the highest sands content of non-big hole soil profile were found in A and E horizons (92%). Better distribution of sand and clay fractions content in between layers of big hole soil profiles of A profile sample is more uniform compared to the B profile sample. The mechanical holing and material mixing of soil materials of A soil profile among the upper and lower horizons i.e. A, E, B and C horizons before planting that resulted a better distribution of both soil texture (sands and clay) and chemical properties such as acidity value (pH), C-organic, N, C/N ratio, CEC, P-available and Exchangeable Bases. Investigation showed that exchangeable cations (Ca, Mg, K), were very low in soil layers (A profile) and horizons (B profile) investigated. The low exchangeable cations due to highly leached of bases to the lower layers and horizons. Besides, the palm which was planted on the big hole system showed good adaptation and response positively by growing well of tertiary and quaternary roots that the roots were penetrable into deeper rooting zone as much as >1.00 m depth. The roots can grow well and penetrate much deeper in A profile compared to the undisturbed hardpan layer (B profile). The FFB (fresh fruit bunches) production of the non-big hole block was higher than the big hole block for the first three years of production. This might be due to the high variation of monthly rainfall in-between years of observation from 2009 to 2014. Therefore, the hardness of placic and ortstein as unpenetrable agents by roots and water to prevent water loss and retain the water in the rhizosphere especially in the drier weather. In the high rainfall condition, the 2:1 drain to prevent water saturation in the oil palm rhizosphere by moving some water into the drain. Meanwhile, the disturbed soil horizon (big hole area) was drier than un disturbance immediately due to water removal to deeper layers. We concluded that both big hole and 2:1 drain are a suitable technology for Spodosol soil land especially in preparing palms planting to minimize the negative effect of the hardpan layer for oil palm growth.

‘Imagined San Francisco’: Unpacking Urban Regime Theory through Interactive Cartography

2017 ◽  
Vol 11 (1) ◽  
pp. 126-143
Author(s):  
Ocean Howell
Keyword(s):  
San Francisco ◽  
Political Power ◽  
Regime Theory ◽  
Commercial Development ◽  
Urban Regime Theory ◽  
Digital Mapping ◽  
Urban Regime ◽  
Historical Processes ◽  
The City ◽  
Interactive Cartography

American urban historians have begun to understand that digital mapping provides a potentially powerful tool to describe political power. There are now important projects that map change in the American city along a number of dimensions, including zoning, suburbanization, commercial development, transportation infrastructure, and especially segregation. Most projects use their visual sources to illustrate the material consequences of the policies of powerful agencies and dominant planning ‘regimes.’ As useful as these projects are, they often inadvertently imbue their visualizations with an aura of inevitability, and thereby present political power as a kind of static substance–possess this and you can remake the city to serve your interests. A new project called ‘Imagined San Francisco’ is motivated by a desire to expand upon this approach, treating visual material not only to illustrate outcomes, but also to interrogate historical processes, and using maps, plans, drawings, and photographs not only to show what did happen, but also what might have happened. By enabling users to layer a series of historical urban plans–with a special emphasis on unrealized plans–‘Imagined San Francisco’ presents the city not only as a series of material changes, but also as a contingent process and a battleground for political power.

SOLUTION OF THE RICHARDS EQUATION IN A SOIL PROFILE WITH TWO LAYERS USING THE METHOD OF LINES

2020 ◽  
Author(s):  
Diego Sousa Lopes ◽  
Augusto Cezar Cordeiro Jardim ◽  
Diego Estumano ◽  
Emanuel Macêdo ◽  
João Quaresma
Keyword(s):  
Soil Profile ◽  
Method Of Lines ◽  
Richards Equation ◽  
The Method Of Lines

Digital Mapping, Charting, and Geodesy Analysis Program Technical Review of Raster Product Format (RPF) and Scanned Map (SMap)

1994 ◽  
Author(s):  
H. V. Miller ◽  
Tom Fetterer ◽  
Danette Coughlan ◽  
Kevin Shaw ◽  
Susan Carter
Keyword(s):  
Analysis Program ◽  
Digital Mapping ◽  
Technical Review

Caesium-137 and strontium-90 distribution in a soil profile

1993 ◽  
Vol 136 (3) ◽  
pp. 251-258 ◽  
Author(s):  
P CHAMARD ◽  
R VELASCO ◽  
M BELLI ◽  
G DISILVESTRO ◽  
G INGRAO ◽  
...  
Keyword(s):  
Soil Profile ◽  
Strontium 90

scholarly journals Implementation of Machine Learning Algorithms in Spectral Analysis of Surface Waves (SASW) Inversion

2021 ◽  
Vol 11 (6) ◽  
pp. 2557
Author(s):  
Sadia Mannan Mitu ◽  
Norinah Abd. Rahman ◽  
Khairul Anuar Mohd Nayan ◽  
Mohd Asyraf Zulkifley ◽  
Sri Atmaja P. Rosyidi
Keyword(s):  
Spectral Analysis ◽  
Surface Waves ◽  
Soil Profile ◽  
Field Tests ◽  
Iteration Process ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Complex Processes ◽  
Inversion Procedure ◽  
Inversion Analysis

One of the complex processes in spectral analysis of surface waves (SASW) data analysis is the inversion procedure. An initial soil profile needs to be assumed at the beginning of the inversion analysis, which involves calculating the theoretical dispersion curve. If the assumption of the starting soil profile model is not reasonably close, the iteration process might lead to nonconvergence or take too long to be converged. Automating the inversion procedure will allow us to evaluate the soil stiffness properties conveniently and rapidly by means of the SASW method. Multilayer perceptron (MLP), random forest (RF), support vector regression (SVR), and linear regression (LR) algorithms were implemented in order to automate the inversion. For this purpose, the dispersion curves obtained from 50 field tests were used as input data for all of the algorithms. The results illustrated that SVR algorithms could potentially be used to estimate the shear wave velocity of soil.

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