| Título: | A Neural Network Model for Mapping and Predicting Unconventional Soils at A Regional Level |
| Autores: | El-Sayed Ewis Omran; Soil and Water Department, Suez Canal University, Ismailia, Egypt |
| Fecha: | 2012-08-17 |
| Publicador: | Applied Remote Sensing |
| Fuente: |
 |
| Tipo: |
|
| Tema: |
Accuracy Assessment, GIS, Gypsum Mapping, Ismailia, Landsat ETM+, Neural Model, Remote Sensing |
| Descripción: | For the formulation of sound decisions about unconventional soils, mapping waterlogged and gypsiferous soils in arid areas are challenging. A neural networks model for mapping unconventional soils is presented in the current study. With this aim, the main objective of this study was to propose a proper model for mapping and prediction the gypsiferous soils by remote sensing (RS). In doing so, ETM+ satellite images of the year 2011 of the Ismailia Province were obtained. The image was processed by spectral ratios and principle component analysis. Moreover, optimum index factor and band combinations were used to explore the scene. Finally the best band was decided. A number of 40 soil samples and 30 observations were collected using global position system. Soil gypsum was analyzed in the soil laboratory. The ETM+ bands 7, 5, 3 and 6 were the most useful for gypsiferous soils discrimination. Supervised classification for the studied area was carried out by using statistical procedures. The overall accuracy for gypsiferous soil maps was 96.80% which revealed by Neural Networks. Models were developed between dependent variables of gypsum content and independent variables of digital value of soil reflectance. It was found that band 6 strongly correlated to gypsiferous soils of the Province. 74% of the locations predicted to be gypsiferous soils were determined to be gypsiferous by field assessment. It was shown by using the thermal band that mapping of the soils containing gypsum can be done in a relatively fast and accurate way. The utility of the model is in its potential ability to use RS image to predict the gypsum content at a county level. The proposed model may be transferred to other areas, particularly in the arid region. The geographical information system has been used to integrate all the spatial information generated and to produce maps of the gypsum soils. |
| Idioma: | Inglés |
1 Correlation of Multispectral Satellite Data with Plant Species Diversity vis-à-vis Soil Characteristics in a Landscape of Western Himalayan Region, India por Amit Chawla; Institute of Himalayan Bioresource Technology (CSIR),Amit Kumar,S Rajkumar,Rakesh Deosharan Singh,Ashwani Kumar Thukral,Paramvir Singh Ahuja | 6 Urban Growth and Land Use/Land Cover Change of Biratnagar Sub-Metropolitan City, Nepal por Bhagawat Rimal; University of Wroclaw, Poland |
2 Improved Agricultural Management Using Remote Sensing to Estimate Water Stress Indices por Cagatay Tanriverdi | 7 Evaluation of Forest Extent Changes: Multi-temporal Satellite Images por Podduwa Kankanamge Subash Chaninda Jayasinghe; Tokyo University of Agriculture and Technology,Masao Yoshida; Ibaraki University |
3 Analysis of SPOT- 5 Data for Mapping Turbidity Level of River Klang, Peninsular Malaysia por Ismail Mohd Hasmadi; Senior Lecturer,Usali Norsaliza | 8 Landsat Satellite Multi-Spectral Image Classification of Land Cover and Land Use Changes for GIS-Based Urbanization Analysis in Irrigation Districts of Lower Rio Grande Valley of Texas por Yanbo Huang; USDA ARS,Guy Fipps; Texas A&M University,Ronald E Lacey; Texas A&M University,Steven J Thomson; USDA ARS |
4 Analysis of Spectral Vegetation Indices Related to Soil-Line for Mapping Mangrove Forests Using Satellite Imagery por Ibrahim Kasawani; Universiti Malaysia Terengganu, Malaysia,Usali Norsaliza; Universiti Putra Malaysia,Ismail Mohd Hasmadi; Universiti Putra Malaysia | 9 A case-study of in-stream juvenile salmon habitat classification using decision-based fusion of multispectral aerial images por Christine Louise Woll; University of Alaska Fairbanks, School of Fisheries and Ocean Sciences,Anupma PRAKASH,Trent SUTTON |
5 Retrieving Tiger Habitats: Conserving Wildlife Geospatially por Suman Sinha; Research Fellow,Laxmikant Sharma; Assistant Professor,Mahendra Singh Nathawat; Professor & Head | 10 Mapping Spatial and Temporal Distributions of Kuwait SST Using MODIS Remotely Sensed Data por Mohammad M M M Alsahli; Geography Department, Kuwait University,Mohammad M M M Alsahli; Geography Deprtment, Kuwait University,Kevin P Price; Geography Department, University of Kansas,Robert Buddemeier; Kansas Geological Survey, University of Kansas,Daphne G. Fautin; Ecology & Evolutionary Biology, University of Kansas,Stephen Egbert; 2Geography Department, University of Kansas |