Soil type classification and estimation of soil properties using support vector machines

Geoderma ◽  
2010 ◽  
Vol 154 (3-4) ◽  
pp. 340-347 ◽  
Author(s):  
Miloš Kovačević ◽  
Branislav Bajat ◽  
Boško Gajić
Keyword(s):  
Support Vector Machines ◽  
Soil Properties ◽  
Soil Type ◽  
Support Vector ◽  
Vector Machines ◽  
Type Classification

scholarly journals Estimation of soil types by non linear analysis of remote sensing data

2008 ◽  
Vol 15 (1) ◽  
pp. 115-126 ◽  
Author(s):  
C. Hahn ◽  
R. Gloaguen
Keyword(s):  
Remote Sensing ◽  
Soil Type ◽  
Remote Sensing Data ◽  
Soil Types ◽  
Support Vector ◽  
Sensing Data ◽  
Vector Machines ◽  
Non Linear ◽  
Input Variables ◽  
Type Classification

Abstract. The knowledge of soil type and soil texture is crucial for environmental monitoring purpose and risk assessment. Unfortunately, their mapping using classical techniques is time consuming and costly. We present here a way to estimate soil types based on limited field observations and remote sensing data. Due to the fact that the relation between the soil types and the considered attributes that were extracted from remote sensing data is expected to be non-linear, we apply Support Vector Machines (SVM) for soil type classification. Special attention is drawn to different training site distributions and the kind of input variables. We show that SVM based on carefully selected input variables proved to be an appropriate method for soil type estimation.

Development of S-NPP VIIRS global surface type classification map using support vector machines

2017 ◽  
Vol 11 (2) ◽  
pp. 212-232 ◽  
Author(s):  
Rui Zhang ◽  
Chengquan Huang ◽  
Xiwu Zhan ◽  
Huiran Jin ◽  
Xiao-Peng Song
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Surface Type ◽  
Vector Machines ◽  
Global Surface ◽  
Type Classification
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