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A PROBABILITY-BASED STATISTICAL METHOD TO EXTRACT WATER BODY OF TM IMAGES WITH MISSING INFORMATION
Probability statistics Water body extraction of TM images Missing information
2016/7/8
Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot b...
CONSISTENCY ANALYSIS ON PADDY RICE AREA SURVEY WITH SPOT AND TM IMAGES UNDER THE TOTAL RESTRAINT QUANTITY
Image Interpretation Percentage Vegetation Cover Space Photogrammetry ComparativeAnalysis Crop Satellite Remote Sensing Classification
2015/12/28
Many global problems can be estimated and forecasted by remote sensing with its advantage of periodicity, objectivity and large scale scope, besides plant area estimation. Conventional classification ...
Applying Sleuth for Simulating and Assessing Urban Growth Scenario Based on Time Series TM Images: Referencing to a Case Study of Chongqing, China
Mountain Cities Compact City Decentralized Concentration Ecological Integrity
2015/12/2
This research simulates the urban growth and therefore the landscape change of a mountain city of Chongqing, China through a Cellular Automata (CA) based model of SLEUTH. The fundamental data were fou...
Integration of radarsat-1 and landsat tm images for mineral exploration in east oweinat district, south western desert, egypte
East Oweinat Principal Component Landsat TM
2015/8/21
East Oweinat district is located in the south Western Desert of Egypt. It is mainly occupied by outcrops of Archean to Early
Proterozoic rocks of high to medium metamorphic grade and younger granitoi...
ABOVE-GROUND BIOMASS ESTIMATION OF SUCCESSIONAL AND MATURE FORESTS USING TM IMAGES IN THE AMAZON BASIN
ABOVE-GROUND BIOMASS SUCCESSIONAL MATURE FORESTS TM IMAGES AMAZON BASIN
2015/3/16
ABOVE-GROUND BIOMASS ESTIMATION OF SUCCESSIONAL AND MATURE FORESTS USING TM IMAGES IN THE AMAZON BASIN.
Comparison of a back propagation and a self organizing map neural networks in classification of TM images
Thematic Classification Neural Network Back Propagation Self Organizing Maps Landsat TM
2015/2/5
In this paper we report the results of an experimental analysis on the use of two neural models for the thematic
classification of multispectral remotely sensed data. A Back Propagation network with ...
SEGMENTATION AND CLASSIFICATION OF LANDSAT-TM IMAGES TO MONITOR THE SOIL USE
Classification Segmentation
2015/2/4
A hybrid unsupervised/supervised classification method is described and applied to
Landsat TM images. This method differs from the conventional classification in the sense that the
clustering algori...
MERGING LANDSAT TM IMAGES AND AIRBORNE PHOTOGRAPHS FOR MONITORING OPENCAST MINE AREA
Landsat images open-pit mine monitoring aerial photographs
2015/2/4
MERGING LANDSAT TM IMAGES AND AIRBORNE PHOTOGRAPHS FOR MONITORING OPENCAST MINE AREA.
Evaluation of Forest Fire Risk by the Analysis of Environmental Data and TM Images
Evaluation of Forest Fire Ris TM Images
2014/4/15
Evaluation of Forest Fire Risk by the Analysis of Environmental Data and TM Images。
Study of Forest Vegetation Regeneration Based upon Landsat TM Images Analysis: Preliminary Results
Study Forest Vegetation Regeneration Landsat TM Images Analysis Preliminary Results
2014/4/15
Study of Forest Vegetation Regeneration Based upon Landsat TM Images Analysis: Preliminary Results。