scholarly journals Application of Remote-sensing Data and Decision-Tree Analysis to Mapping Salt-Affected Soils over Large Areas

2009 ◽  
Vol 2 (1) ◽  
pp. 151-165 ◽  
Author(s):  
Abdelhamid Elnaggar ◽  
Jay Noller
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Remote Sensing Data ◽  
Decision Tree Analysis ◽  
Tree Analysis ◽  
Sensing Data ◽  
Salt Affected Soils

Land degradation mapping in the MATOPIBA region (Brazil) using remote sensing data and decision-tree analysis

2021 ◽  
pp. 146900
Author(s):  
Rita Marcia da Silva Pinto Vieira ◽  
Javier Tomasella ◽  
Alexandre Augusto Barbosa ◽  
Silvia Palotti Polizel ◽  
Jean Pierre Henry Balbaud Ometto ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Land Degradation ◽  
Remote Sensing Data ◽  
Decision Tree Analysis ◽  
Tree Analysis ◽  
Sensing Data

scholarly journals The Design of a Land Suitability Model on Rice Production Estimation using Remote Sensing Method in Merauke District Papua

2020 ◽  
Vol 10 (1) ◽  
pp. 291-295
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Rice Field ◽  
Rice Production ◽  
Land Suitability ◽  
Decision Tree Analysis ◽  
Milled Rice ◽  
Tree Analysis ◽  
Local Residents ◽  
Remote Sensing Methods

The area of agricultural land in Merauke Regency according to data from Bappeda (Agency for Regional Development) of Merauke Regency is for about 4.6 million hectares in 2015 and within the next 5 years will be cultivated as much as 1.2 hectares, especially for rice field and secondary crops plants [1].This study has purpose to estimate the value of rice production by using dry-milled rice with a land suitability approach using decision tree analysis and remote sensing methods in Merauke Regency. Remote sensing that has been corrected geometrically and radio-metrically is analyzed by using decision tree analysis to derive information on paddy/rice and non-rice field land use and which is reclassified by using field unit information based on field observations which will result in accuracy of use and producer. The rice field data is then processed to derive information on the rotation pattern of rice by using a decision tree analysis that is using input data on land characteristics which will produce total accuracy. Information on rice field area and rotation patterns are complemented by land productivity (tons / ha) sourced from BPS (Central Statistics Agency) data and interviews with land cultivators and local residents (farmers) were used to calculate the total rice production value on dry-milled rice The results of calculations by using this method are expected to have a fairly large surplus of calculations, both data from BPS (Central Bureau of Statistics) and data from interviews with land cultivators and local residents (farmers). Thus, these results are expected to show that the land suitability approach by using remote sensing methods for estimating rice production can be used to produce information on rice field area and rotation patterns with moderate to high accuracy.

scholarly journals Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

2010 ◽  
Vol 105 (4) ◽  
pp. 541-548 ◽  
Author(s):  
Flávia T Martins-Bedê ◽  
Luciano V Dutra ◽  
Corina C Freitas ◽  
Ricardo JPS Guimarães ◽  
Ronaldo S Amaral ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Remote Sensing Data ◽  
Minas Gerais ◽  
The State ◽  
Risk Mapping ◽  
Sensing Data ◽  
Tree Approach

Decision tree regression for soft classification of remote sensing data

2005 ◽  
Vol 97 (3) ◽  
pp. 322-336 ◽  
Author(s):  
M XU ◽  
P WATANACHATURAPORN ◽  
P VARSHNEY ◽  
M ARORA
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Soft Classification

scholarly journals AUTOMATIC BUILDING EXTRACTION USING A DECISION TREE OBJECT-BASED CLASSIFICATION ON JOINT USE OF AERIAL AND LIDAR DATA

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 429-434
Author(s):  
R. Ghasemi Nejad ◽  
P. Pahlavani ◽  
B. Bigdeli
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Spatial Databases ◽  
Remote Sensing Data ◽  
Predictive Performance ◽  
Single Step ◽  
Building Extraction ◽  
Digital Maps ◽  
Sensing Data ◽  
Object Based

Abstract. Updating digital maps is a challenging task that has been considered for many years and the requirement of up-to-date urban maps is universal. One of the main procedures used in updating digital maps and spatial databases is building extraction which is an active research topic in remote sensing and object-based image analysis (OBIA). Since in building extraction field a full automatic system is not yet operational and cannot be implemented in a single step, experts are used to define classification rules based on a complex and subjective “trial-and-error” process. In this paper, a decision tree classification method called, C4.5, was adopted to construct an automatic model for building extraction based on the remote sensing data. In this method, a set of rules was derived automatically then a rule-based classification is applied to the remote sensing data include aerial and lidar images. The results of experiments showed that the obtained rules have exceptional predictive performance.

Application of decision tree technology for image classification using remote sensing data

2003 ◽  
Vol 76 (3) ◽  
pp. 1101-1117 ◽  
Author(s):  
Chun-Chieh Yang ◽  
Shiv O Prasher ◽  
Peter Enright ◽  
Chandra Madramootoo ◽  
Magdalena Burgess ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Tree ◽  
Image Classification ◽  
Remote Sensing Data ◽  
Sensing Data
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