scholarly journals Digital soil mapping including additional point sampling in Posses ecosystem services pilot watershed, southeastern Brazil

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bárbara Pereira Christofaro Silva ◽  
Marx Leandro Naves Silva ◽  
Fabio Arnaldo Pomar Avalos ◽  
Michele Duarte de Menezes ◽  
Nilton Curi
Keyword(s):  
Multinomial Logistic Regression ◽  
Spatial Association ◽  
Soil Mapping ◽  
Soil Survey ◽  
Digital Soil Mapping ◽  
Southeastern Brazil ◽  
Kappa Index ◽  
Point Sampling ◽  
Terrain Attributes ◽  
Additional Point

Abstract This study aimed to evaluate the performance of three spatial association models used in digital soil mapping and the effects of additional point sampling in a steep-slope watershed (1,200 ha). A soil survey was carried out and 74 soil profiles were analyzed. The tested models were: Multinomial logistic regression (MLR), C5 decision tree (C5-DT) and Random forest (RF). In order to reduce the effects of an imbalanced dataset on the accuracy of the tested models, additional sampling retrieved by photointerpretation was necessary. Accuracy assessment was based on aggregated data from a proportional 5-fold cross-validation procedure. Extrapolation assessment was based on the multivariate environmental similarity surface (MESS). The RF model including additional sampling (RF*) showed the best performance among the tested models (overall accuracy = 49%, kappa index = 0.33). The RF* allowed to link soil mapping units (SMU) and, in the case of less-common soil classes in the watershed, to set specific conditions of occurrence on the space of terrain-attributes. MESS analysis showed reliable outputs for 82.5% of the watershed. SMU distribution across the watershed was: Typic Rhodudult (56%), Typic Hapludult* (13%), Typic Dystrudept (10%), Typic Endoaquent + Fluventic Dystrudept (10%), Typic Hapludult (9.5%) and Rhodic Hapludox + Typic Hapludox (2%).

scholarly journals Author Correction: Digital soil mapping including additional point sampling in Posses ecosystem services pilot watershed, southeastern Brazil

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bárbara Pereira Christofaro Silva ◽  
Marx Leandro Naves Silva ◽  
Fabio Arnaldo Pomar Avalos ◽  
Michele Duarte de Menezes ◽  
Nilton Curi
Keyword(s):  
Ecosystem Services ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Southeastern Brazil ◽  
Point Sampling ◽  
Additional Point

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Digital soil mapping and its implications in the extrapolation of soil-landscape relationships in detailed scale

2017 ◽  
Vol 52 (8) ◽  
pp. 633-642
Author(s):  
Mario Sergio Wolski ◽  
Ricardo Simão Diniz Dalmolin ◽  
Carlos Alberto Flores ◽  
Jean Michel Moura-Bueno ◽  
Alexandre ten Caten ◽  
...  
Keyword(s):  
Soil Mapping ◽  
Soil Survey ◽  
Digital Soil Mapping ◽  
Limiting Factor ◽  
Topographic Map ◽  
Kappa Index ◽  
Terrain Attributes ◽  
Soil Landscape ◽  
Mapping Techniques ◽  
Map Scale

Abstract: The objective of this work was to test the extrapolation of soil-landscape relationships in a reference area (RA) to a topographic map (scale 1:50,000), using digital soil mapping (DSM), and to compare these results to those obtained in similar studies previously conducted in Brazil. A soil survey in a 10 km2 RA, using conventional mapping techniques (scale 1:10,000), was made in order to map a 678 km2 physiographically similar area (scale 1:50,000) using DSM. The decision tree technique was employed to build a predictive extrapolation model based on soil classes and eight terrain attributes in the RA. The validation of DSM by application of field observation points resulted in a 66.1% global accuracy and in 0.36 kappa index. The most representative soils in the area were correctly predicted, whereas the less representative and less frequent soils in the landscape (and consequently with reduced sampling) had their prediction compromised. The RA proportion, which equals 1.5% of the total area, is a limiting factor in the formulation of soil-landscape relationships to precisely represent the mapped area by DSM.

Analysis of terrain attributes in different spatial resolutions for digital soil mapping application in southeastern Brazil

2020 ◽  
Vol 21 ◽  
pp. e00268
Author(s):  
Nathalie Cruz Sena ◽  
Gustavo Vieira Veloso ◽  
Elpídio Inácio Fernandes-Filho ◽  
Marcio Rocha Francelino ◽  
Carlos Ernesto G.R. Schaefer
Keyword(s):  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Southeastern Brazil ◽  
Terrain Attributes

scholarly journals Digital elevation model quality on digital soil mapping prediction accuracy

2018 ◽  
Vol 42 (6) ◽  
pp. 608-622 ◽  
Author(s):  
Elias Mendes Costa ◽  
Alessandro Samuel-Rosa ◽  
Lúcia Helena Cunha dos Anjos
Keyword(s):  
Multinomial Logistic Regression ◽  
External Validation ◽  
Quality Criteria ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Model Quality ◽  
Terrain Attributes ◽  
Digital Elevation ◽  
Lower Accuracy ◽  
Terrain Surface

ABSTRACT Digital elevation models (DEM) used in digital soil mapping (DSM) are commonly selected based on measures and indicators (quality criteria) that are thought to reflect how well a given DEM represents the terrain surface. The hypothesis is that the more accurate a DEM, the more accurate will be the DSM predictions. The objective of this study was to assess different criteria to identify the DEM that delivers the most accurate DSM predictions. A set of 10 criteria were used to evaluate the quality of nine DEMs constructed with different data sources, processing routines and three resolutions (5, 20, and 30 m). Multinomial logistic regression models were calibrated using 157 soil observations and terrain attributes derived from each DEM. Soil class predictions were validated using leave-one-out cross-validation. Results showed that, for each resolution, the quality criteria are useful to identify the DEM that more accurately represents the terrain surface. However, for all three resolutions, the most accurate DEM did not produce the most accurate DSM predictions. With the 20-m resolution DEMs, DSM predictions were five percentage points less accurate when using the more accurate DEM. The 5-m resolution was the most accurate DEM overall and resulted in DSM predictions with 44% accuracy; this value was equal to that obtained with two coarser resolution, lower accuracy DEMs. Thus, identifying the truly best DEM for DSM requires assessment of the accuracy of DSM predictions using some form of external validation, because not necessarily the most accurate DEM will produce the best DSM predictions.

scholarly journals DIGITAL SOIL MAPPING USING GEOMORPHOMETRIC ANALYSIS AND CASE-BASED FUZZY LOGIC APPROACH

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 863-866
Author(s):  
A. Rahmani ◽  
F. Sarmadian ◽  
S. R. Mousavi ◽  
S. E. Khamoshi
Keyword(s):  
Fuzzy Logic ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Kappa Index ◽  
Valley Bottom ◽  
Error Matrix ◽  
Soil Map ◽  
Expert’S Opinion ◽  
Fuzzy Logic Approach ◽  
Landscape Units

Abstract. In low relief region such as plains, applied digital soil mapping has a controvertible issue, therefore, this study was aimed to digital mapping of soil classes at family levels by appropriate Geomorphometric variables along with fuzzy logic with area of 16,600 hectares in Qazvin Plain. Based on the geomorphologic map, the plain and pen plain are dominant landscape units. In this regards, 61 soil profiles were dogged. According to the expert’s opinion, covariates including diffuse insolation, standardized height, catchment area, valley depth and multiresolution valley bottom flatness (MrVBF) had the most important in order to generating soil map. Also, 19 fuzzy soil class maps were generated through using sample-based in ArcSIE software. Validation were carried out using achieved overall accuracy (OA) and Kappa index through error matrix. Subsequently, both ignorance and exaggerating uncertainty of hardened soil map were also done. The results showed that 19 soil families class were found. Accordingly, OA and the Kappa index were 54% and 46% respectively. The uncertainty of ignorance and exaggeration were obtained from 0 to 0.64 and 0 to 1, respectively. Moreover, the results indicated that exaggerated uncertainty was the highest in the northern and the lowest in the southern regions. Generally, applied geomorphometric parameters had the specific importance in the low relief areas for mapping of soils that have not been assessed properly so far.

scholarly journals Decision trees for digital soil mapping on subtropical basaltic steeplands

2011 ◽  
Vol 68 (2) ◽  
pp. 167-174 ◽  
Author(s):  
Elvio Giasson ◽  
Eliana Casco Sarmento ◽  
Eliseu Weber ◽  
Carlos Alberto Flores ◽  
Heinrich Hasenack
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Land Use Planning ◽  
Spatial Information ◽  
Soil Mapping ◽  
Soil Survey ◽  
Digital Soil Mapping ◽  
Tree Algorithms ◽  
Mapping Techniques ◽  
Soil Surveys

When soil surveys are not available for land use planning activities, digital soil mapping techniques can be of assistance. Soil surveyors can process spatial information faster, to assist in the execution of traditional soil survey or predict the occurrence of soil classes across landscapes. Decision tree techniques were evaluated as tools for predicting the ocurrence of soil classes in basaltic steeplands in South Brazil. Several combinations of types of decicion tree algorithms and number of elements on terminal nodes of trees were compared using soil maps with both original and simplified legends. In general, decision tree analysis was useful for predicting occurrence of soil mapping units. Decision trees with fewer elements on terminal nodes yield higher accuracies, and legend simplification (aggregation) reduced the precision of predictions. Algorithm J48 had better performance than BF Tree, RepTree, Random Tree, and Simple Chart.

Soil survey design for management-scale digital soil mapping in a mountainous southern Philippine catchment

2012 ◽  
pp. 233-238 ◽  
Author(s):  
M Thomas ◽  
N Odgers ◽  
A Ringrose-Voase ◽  
G Grealish ◽  
M Glover ◽  
...  
Keyword(s):  
Survey Design ◽  
Soil Mapping ◽  
Soil Survey ◽  
Digital Soil Mapping

scholarly journals Comparison between detailed digital and conventional soil maps of an area with complex geology

2013 ◽  
Vol 37 (5) ◽  
pp. 1136-1148 ◽  
Author(s):  
Osmar Bazaglia Filho ◽  
Rodnei Rizzo ◽  
Igo Fernando Lepsch ◽  
Hélio do Prado ◽  
Felipe Haenel Gomes ◽  
...  
Keyword(s):  
Great Influence ◽  
Soil Formation ◽  
Principal Component ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Mapping Technique ◽  
Topographic Map ◽  
Soil Maps ◽  
Soil Map ◽  
Terrain Attributes

Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

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