scholarly journals Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery

2018 ◽  
Vol 10 (2) ◽  
pp. 77 ◽  
Author(s):  
Yuehong Chen ◽  
Ya’nan Zhou ◽  
Yong Ge ◽  
Ru An ◽  
Yu Chen
Keyword(s):  
Land Cover ◽  
Remotely Sensed ◽  
Land Cover Mapping ◽  
Remotely Sensed Imagery ◽  
Object Based

scholarly journals Object-Based Superresolution Land-Cover Mapping From Remotely Sensed Imagery

2018 ◽  
Vol 56 (1) ◽  
pp. 328-340 ◽  
Author(s):  
Yuehong Chen ◽  
Yong Ge ◽  
Gerard B. M. Heuvelink ◽  
Ru An ◽  
Yu Chen
Keyword(s):  
Land Cover ◽  
Remotely Sensed ◽  
Land Cover Mapping ◽  
Remotely Sensed Imagery ◽  
Object Based

Measuring and monitoring land cover, land use, and vegetation characteristics

2010 ◽  
Author(s):  
Ned Horning ◽  
Julie A. Robinson ◽  
Eleanor J. Sterling ◽  
Woody Turner ◽  
Sacha Spector
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Deciduous Forest ◽  
Land Cover Classification ◽  
Remotely Sensed ◽  
Land Cover Mapping ◽  
Remotely Sensed Data ◽  
Soil P ◽  
Vegetation Characteristics ◽  
Classification Project

In terrestrial biomes, ecologists and conservation biologists commonly need to understand vegetation characteristics such as structure, primary productivity, and spatial distribution and extent. Fortunately, there are a number of airborne and satellite sensors capable of providing data from which you can derive this information. We will begin this chapter with a discussion on mapping land cover and land use. This is followed by text on monitoring changes in land cover and concludes with a section on vegetation characteristics and how we can measure these using remotely sensed data. We provide a detailed example to illustrate the process of creating a land cover map from remotely sensed data to make management decisions for a protected area. This section provides an overview of land cover classification using remotely sensed data. We will describe different options for conducting land cover classification, including types of imagery, methods and algorithms, and classification schemes. Land cover mapping is not as difficult as it may appear, but you will need to make several decisions, choices, and compromises regarding image selection and analysis methods. Although it is beyond the scope of this chapter to provide details for all situations, after reading it you will be able to better assess your own needs and requirements. You will also learn the steps to carry out a land cover classification project while gaining an appreciation for the image classification process. That said, if you lack experience with land cover mapping, it always wise to seek appropriate training and, if possible, collaborate with someone who has land cover mapping experience (Section 2.3). Although the terms “land cover” and “land use” are sometimes used interchangeably they are different in important ways. Simply put, land cover is what covers the surface of the Earth and land use describes how people use the land (or water). Examples of land cover classes are: water, snow, grassland, deciduous forest, or bare soil.

Hybrid object-based approach for land use/land cover mapping using high spatial resolution imagery

2011 ◽  
Vol 25 (6) ◽  
pp. 1025-1043 ◽  
Author(s):  
Eva Savina Malinverni ◽  
Anna Nora Tassetti ◽  
Adriano Mancini ◽  
Primo Zingaretti ◽  
Emanuele Frontoni ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Land Cover Mapping ◽  
Land Use Land Cover ◽  
Object Based ◽  
High Spatial Resolution Imagery
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