Improved Water Classification Using an Application-oriented Processing of Landsat ETM+ and ALOS PALSAR
نویسندگان
چکیده
منابع مشابه
Improved Water Classification Using an Application-oriented Processing of Landsat ETM+ and ALOS PALSAR
The aim of this study is to extract water body using the integrated features of Landsat ETM+ and ALOS PALSAR data. Water body extracted from Landsat ETM+ tends to lose smaller water bodies like small rivers and ponds. Besides, water area with plant (lotus) is difficult to recognize. ALOS PALSAR data have a much higher resolution, capable of extracting almost all the water bodies without confusi...
متن کاملMapping Canopy Height and Growing Stock Volume Using Airborne Lidar, ALOS PALSAR and Landsat ETM+
We have investigated for forest plantations in Chile the stand-level retrieval of canopy height (CH) and growing stock volume (GSV) using Airborne Laser Scanner (ALS), ALOS PALSAR and Landsat. In a two-stage up-scaling approach, ensemble regression tree models (randomForest) were used to relate a suite of ALS canopy structure indices to stand-level in situ measurements of CH and GSV for 319 sta...
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The joint processing of remote sensing data acquired from sensors operating at different wavelengths has the potential to significantly improve the operation of global forest mapping and monitoring systems. This paper presents an analysis of the forest discrimination properties of Landsat TM and ALOS-PALSAR data when considered as a combined source of information. This study is carried out over...
متن کاملForest Discrimination Analysis of Combined Landsat and ALOS-PALSAR Datasets
The joint processing of remote sensing data acquired from sensors operating at different wavelengths has the potential to significantly improve the operation of global forest mapping and monitoring systems. This paper presents an analysis of the forest discrimination properties of Landsat TM and ALOS-PALSAR data when considered as a combined source of information. This study is carried out over...
متن کاملExtreme Learning Machine-based Crop Classification using ALOS/PALSAR Images
Classification maps are required for agricultural management and the estimation of agricultural disaster compensation. The extreme learning machine (ELM), a newly developed single hidden layer neural network is used as a supervised classifier for remote sensing classifications. In this study, the ELM was evaluated to examine its potential for multi-temporal ALOS/PALSAR images for the classifica...
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ژورنال
عنوان ژورنال: International Journal of Control and Automation
سال: 2014
ISSN: 2005-4297,2005-4297
DOI: 10.14257/ijca.2014.7.11.35