Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods

2007 ◽  
Vol 119 (2) ◽  
pp. 159-164 ◽  
Author(s):  
L. Martins ◽  
J. Castro ◽  
W. Macedo ◽  
C. Marques ◽  
C. Abreu
2005 ◽  
pp. 621-626 ◽  
Author(s):  
L.M. Martins ◽  
F.W. Macedo ◽  
C.P. Marques ◽  
C.G. Abreu

2020 ◽  
Vol 3 (1) ◽  
pp. 30-40
Author(s):  
Jarosław Zawadzki ◽  
Piotr Fabijańczyk ◽  
Karol Przeździecki

AbstractPost-industrial and post-mining areas have often been under strong anthropogenic pressure for a long time. As a result, such areas, after the ending of industrial activity require taking steps to revitalize them. It may cover many elements of the natural or urban environment, such as water, soil, vegetated areas, urban development etc. To carry out revitalization, it is necessary to determine the initial state of such areas, often using selected chemical, geophysical or ecological. After that it is also important to properly monitor the state of such areas to assess the progress of the revitalization process. For this purpose a variety of change detection technics were developed. Post-industrial areas are very often characterized by a large extent, are difficult to access, have complicated land cover. For this reason, it is particularly important to choose appropriate methods to assess the degree of pollution of such areas. Such methods should be as economical as possible and time-effective. A very desirable feature of such methods is that they should allow a quick assessment of the entire area. Geostatistics supplemented by modern remote sensing can be effective for this purpose. Nowadays, using remote sensing, it is possible to gather information simultaneously from the entire, even vast area, with high spatial, spectral and temporal resolution. Geostatistics in turn provides many tools that are able to enable rapid analysis and inference based on even very complicated often scarce spatial data sets obtained from ground measurement and satellite observations. The goal of the article was to present selected results obtained using geostatistical methods also related to remote sensing, which may be helpful for decision makers in revitalizing post-industrial and post-mining areas. The results described in this paper were based mostly on the previous studies, carried out by authors.


Author(s):  
Q. Wang ◽  
V. Rodriguez-Galiano ◽  
P. M. Atkinson

Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.


Author(s):  
Karl F. Warnick ◽  
Rob Maaskant ◽  
Marianna V. Ivashina ◽  
David B. Davidson ◽  
Brian D. Jeffs

Author(s):  
Dimitris Manolakis ◽  
Ronald Lockwood ◽  
Thomas Cooley

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