Abstract
Abstract. Earth observations which are being useable by spatial analysis ability play an important role in detecting, management and solving environmental problems such as climate changes, deforestation, disasters, land use, water resource and carbon cycle. Remote sensing technology in combination with geospatial information system (GIS) can render reliable information on vegetation cover. Satellite Remote sensed data and GIS for land cover/use with its changes is a key to many diverse applications such as Forestry. Change detection can be defined as the process of identifying differences in the state of an object or phenomenon by observing it at different times. The analysis of the spatial extent and temporal change of vegetation cover (Forest) by using remotely sensed data is critically importance to natural resource management sciences. The main aim of this review paper is to go through the different change detection methods and algorithms based on very high resolution remote sensing imagery data, evaluate the quality of the spatial individual crown cover extraction in forests with high density, analyse, compare the results by optimized performance of control data for the same objects to provide the improvement in technique for detection and improve the mathematical sides of the change detection algorithms for high dense forests regions with different boundaries.
Highlights
INTRODUCTOINInformation on spatial distribution of forest cover classes is a primary and necessary requirement for sustainable forest management (Ghosh et al, 2014)
The main aim of this paper is to review the change detection techniques in two groups based on the unit of the image analysis
The paper is a review of commonly used object based techniques for detection of tree crown covers changes as spatial objects in forest vegetation, their applications and related issues
Summary
Information on spatial distribution of forest cover classes is a primary and necessary requirement for sustainable forest management (Ghosh et al, 2014). The new paradigm of individual tree-based analysis is expected to lead to powerful remote sensing-based forest survey and management tools for individual tree crowns (Brandtberg et al, 2003) This paradigm commends a more object-oriented image analysis, one that shift from traditional pixel-based techniques and towards the detection of individual tree crowns (Gougeon & Leckie, 2006). Satellite Imaging Corporation provides a large amount of remote sensing data at different spatial, spectral and temporal resolutions by using the appropriate combination of bands to bring out the geographical and manmade features for detecting changes. The paper is a review of commonly used object based techniques for detection of tree crown covers changes as spatial objects in forest vegetation, their applications and related issues
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