Detecting Invasive Plants Using Hyperspectral and High Resolution Satellite Images
نویسندگان
چکیده
The rapid spread of nonnative plant species have caused considerable negative impact to the biodiversity and ecosystems in Taiwan. To better unders tand the status and to suppor t researchers and decision makers to develop strategies and remedies for this problem, it is necessary to obtain accurate spatial information and the progression about the invasions of foreign species into native ecocommu nity. The availability of hyperspectral and high resolution satellite data provides researchers an opportuni ty to pursue more complex analysis and have a great potential to achieve better performance and results in an invasive plants investigation. High resolution images provide detail spatial information about the target areas but are often limited to single or few spectral bands. On the other hand, hyperspect ral data consist of tens to hundreds of contiguous bands but lack of spatial details. Therefore, a combination of both types of data is likely to be an optimal approach to the mapping of alien plants. However, with the large data volume and high data dimensionality, the major challenge of using hyperspectral and high resolution data together is to extract useful information effectively and efficiently. This paper presents a work in progress of developing a systematic method to use hyperspectral and high resolution satellite images to identify an invasive plant (horse tamarind, Leucaena Leucocephala ) that is spreading in an alarming rate in southern Taiwan. The developed method first locates "areas of interest" where target species is likely to populate most densely. Then a twolevel analysis procedure is implemented using hyperspectral and high resolution satellite images to identify and map the distribution of target species. The first phase of the procedure is to analyze hyperspectral images with selected (helpful) features to obtain a preliminary result. The second phase is to isolate the areas where discrimination of target plant species is not satisfactory and to improve the accuracy of discrimination with the analysis of canopy structures in high resolution satellite images. Verification with ground truth samples indicates that the developed method of combining high resolution and hyperspectral images analysis is an effective and efficient approach to detect invasive plants in a large area.
منابع مشابه
Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images
As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...
متن کاملLand Cover Subpixel Change Detection using Hyperspectral Images Based on Spectral Unmixing and Post-processing
The earth is continually being influenced by some actions such as flood, tornado and human artificial activities. This process causes the changes in land cover type. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Today’s remote sensing plays key role in geology and environmental monitoring by its high resolution, wide covering and low cost...
متن کاملObject Detection from Hs/ms and Multi-platform Remote- Sensing Imagery by the Integration of Biologically and Geometrically Inspired Approaches
This paper presents a system that integrates biologically and geometrically inspired approaches to detecting objects from hyperspectral and/or multispectral (HS/MS), multiscale, multiplatform imagery. First, dimensionality reduction methods are studied and used for hyperspectral dimensionality reduction. Then, a biologically inspired method, SLEGION (Spatial Locally Excitatory Globally Inhibito...
متن کاملComparative Evaluation of Image Fusion Methods for Hyperspectral and Panchromatic Data Fusion in Agricultural and Urban Areas
Nowadays remote sensing plays a key role in the field of earth science studies due to some of the advantages, including data collection at a very low cost and time on a very large scale. Meanwhile, using hyperspectral data is of great importance due to the high spectral resolution. Because of some limitations, such as hyperspectral imaging technology, it suffers from a reduction in the spatial ...
متن کاملDigital surface model extraction with high details using single high resolution satellite image and SRTM global DEM based on deep learning
The digital surface model (DSM) is an important product in the field of photogrammetry and remote sensing and has variety of applications in this field. Existed techniques require more than one image for DSM extraction and in this paper it is tried to investigate and analyze the probability of DSM extraction from a single satellite image. In this regard, an algorithm based on deep convolutional...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004