Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods
نویسندگان
چکیده
منابع مشابه
Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods
Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC) information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence....
متن کاملLand Cover Classification Using IRS-1D Data and a Decision Tree Classifier
Land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. Digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. In the present study the multispectral image from IRS LISS-III image along with ancillary datasuch as vegetation indices, principal componen...
متن کاملIntegrating Contextual Information with per-Pixel Classification for Improved Land Cover Classification
A hybrid segmentation procedure to integrate contexcompared to traditional per-pixel maximum likelihood classification results. Elsevier Science Inc., 2000 tual information with per-pixel classification in a metropolitan area land cover classification project is described and evaluated. It is presented as a flexible tool within a INTRODUCTION commercially available image processing environment...
متن کاملComparing the Capability of Sentinel 2 and Landsat 8 Satellite Imagery in Land Use and Land Cover Mapping Using Pixel-based and Object-based Classification Methods
Introduction: Having accurate and up-to-date information on the status of land use and land cover change is a key point to protecting natural resources, sustainable agriculture management and urban development. Preparing the land cover and land use maps with traditional methods is usually time and cost consuming. Nowadays satellite imagery provides the possibility to prepare these maps in less ...
متن کاملland cover classification using irs-1d data and a decision tree classifier
land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. in the present study the multispectral image from irs liss-iii image along with ancillary datasuch as vegetation indices, principal componen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2017
ISSN: 2072-4292
DOI: 10.3390/rs9121222