Object-based Change Detection Analysis for the Monitoring of Habitats in the Framework of the Natura 2000 Directive with Multi- Temporal Satellite Data
نویسندگان
چکیده
Multi-temporal and multi-sensor satellite information can supply valuable information about vegetation species, especially in the context of biodiversity. Main focus of the presented project CARE-X is the development of a remote sensing technology for the European monitoring of NATURA 2000 areas. For this type of monitoring, information about the structure and composition of the existing vegetation within a growth period are required. With temporal very high resolution (TVHR) satellite data, such as RapidEye and TerraSAR-X, the optimal dates for a highly effective utilization of acquired images for the monitoring of different vegetation types and habitats can be identified. The study area "Döberitzer Heide" is situated in the Federal State of Brandenburg (north-east Germany). The main habitats are heathland, dry grassland, and wetland, forming a heterogeneous small scale mosaic of vegetation types. In a first step the land-use and specific habitats within this site and the surrounding area were segmented and classified with five RapidEye images from the vegetation period of 2009. Simultaneously, intensive field spectral measurements took place. First results show that the main land-use classes related to the NATURA 2000 monitoring can be detected with an accuracy of above 0.85. The classification results improve when scenes of August and September are included. The terrestrial spectral measurements show a good accordance with the reflectance of the RapidEye images. Moreover, different vegetation types relevant to the NATURA 2000 monitoring can be separated temporally. In further research the field measurements will be transferred to the multi-temporal RapidEye images using the phenological profile of different vegetation types. * Corresponding author
منابع مشابه
Change detection from satellite images based on optimal asymmetric thresholding the difference image
As a process to detect changes in land cover by using multi-temporal satellite images, change detection is one of the practical subjects in field of remote sensing. Any progress on this issue increase the accuracy of results as well as facilitating and accelerating the analysis of multi-temporal data and reducing the cost of producing geospatial information. In this study, an unsupervised chang...
متن کاملCrop Land Change Monitoring Based on Deep Learning Algorithm Using Multi-temporal Hyperspectral Images
Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...
متن کاملپایش زمانی و مکانی خشکسالی کشاورزی با استفاده از دادههای سنجش از دور مورد مطالعه: استان مرکزی ایران
As a result of climate change and reduction in rainfall during the last decade, drought has become big problem in the world, especially in arid and semi-arid areas such as Iran. Therefore drought monitoring and management is great of important. In contrast with the traditional methods which are based on the ground stations measurements and meteorological drought monitoring, using the remote sen...
متن کاملTowards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter
Spatial monitoring tools are necessary to respond to the threat of global biodiversity loss. At the European scale, remote sensing tools for NATURA 2000 habitat monitoring have been requested by the European Commission to fulfill the obligations of the EU Habitats Directive. This paper introduces a method by which swath events in semi-natural grasslands can be detected from multi-temporal Terra...
متن کاملvegetation change detection using multi-temporal remotly sensed data during recent three decades by artificial intelligence technique (Case study: protected area of Bashgol)
Quantitative and qualitative information of vegetation and its changes in duration of time as a basic foundation of determination of habitat quality, priority of protected area and also determination of price of ecosystem services in order to optimum management of natural resources and sustainable development is a very important technical point. In other hand, researchers are interested in rem...
متن کامل