Satellite monitoring of the environment on a regional scale: Western Pomerania in the years 2000–2015

Satellite monitoring of the environment on a regional scale: Western Pomerania in the years 2000–2015

Alfred Stach

 

Summary

Satellite remote sensing for many years has been the most important source of knowledge about the state and trends of environmental changes on Earth. However,
the use of recording made from satellites to monitor the environment on a local or regional scale was limited. The situation has changed signifcantly by entering
into service in 2000 and 2002 of two satellites Terra and Aqua equipped with MODIS spectroradiometer. It allows to record the characteristics of the surface of the planet twice a day in 36 spectral channels with a resolution of 0.25–1 km. The aim was the assessment of trends in the environment of Western Pomerania in the years 2000–2015 on the basis of data from the MODIS sensor. This area is highly diverse both in natural and economic conditions, including large urban areas, areas
intensively used for agriculture, forest plantations as well as valuable, legally protected natural objects: national parks, lakes, protected landscape areas, etc.
In this work we used land surface temperature (LST), and the state of vegetation indexes NDVI (Normalized Difference Vegetation) and EVI (Enhanced Vegetation
Index). We analyzed trends in both long-term average values, as well as the characteristics of seasonal cycle. The study was based on the 8 days average values of LST
for the day and the night, and the 16 days average value of NDVI and EVI from March 2000 to February 2016. The analysis covered an area of approximately 35.500
km
2. The novelty was the use of so-called contextual Mann-Kendall test. It is based on the assumption that the trends between adjacent pixels should exhibit autocorrelation and reduces false detection of trends and increase the confdence of the results when trends are spatially coherent. Analysis of seasonal trends consist of two stages. In the frst the annual and shorter components of the seasonal cycle was ftted using harmonic regression. In the second stage by means of non-parametric technique of median slope were determined parameters trends of cycles (amplitude and phase). This methodology effectively eliminates high frequency noise that occurs in the scale of a single year and it is resistant to short-term variability between years. Also in this procedure the contextual Mann-Kendall test was used. The calculations showed the presence in the analyzed period and analyzed area of signifcant trends in both LST, and NDVI / EVI indicators of biomass. That concern both the averages and seasonal cycle parameters. Spatial distribution of trends shows variability in two spatial scales: local and regional. Multi-annual LST trends were recorded surprisingly only for the night measurements. They are only increase. They include over 56% of the study area and their spatial distribution is not random. On a regional scale they primarily include higher-lying moraine areas. Much less frequently they are listed in the Noteć and Odra valleys and the lowlands along the shore of the Baltic Sea. It has been found both increments (approx. 28% of the area) and decreases (approx. 10%) of the average values of plant biomass (NDVI and EVI). About 70% of the high increases of the two indicators is shared, indicating both an increase in the amount of chlorophyll (NDVI), leaf area, and changes in the type and physiognomy of plant community (EVI). The spatial distribution trends of biomass indicators also showed regional variation, but it is more complicated than in the case of LST. Analysis of the seasonal cycles characteristics showed that on the areas of statistically signifcant changes, they relates to both the decrease in the annual amplitude and phase shift – a faster onset of the growing season in the spring. Identifcation of the relationship between the characteristics of the surface, LST changes and indicators of biomass enables the identifcation of areas that should be subjected to a more elaborate test – hotspots of environmental imbalance.

 



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