Impact of the Variability of Vegetation, Soil Moisture, and Building Density between City Districts on Land Surface Temperature, Warsaw, Poland

The temperature of a city’s surface is influenced by many factors, including human-dependent ones that can be shaped, such as the urban density, the condition of urban vegetation, the presence of urban water bodies, and soil moisture. Knowledge on this subject allows for improving the urban climate through better planning and construction of urban infrastructure and adapting cities to climate change and avoiding deadly heat waves increasingly threatening European cities. So far, mainly the first three factors have been studied particularly well, while there is no in-depth research on the impact of soil moisture on a city’s climate in the literature. This article fills this gap by analyzing the impact of all the abovementioned factors on the temperature of the city’s surface in Warsaw, a large European urban agglomeration, located in a temperate climate zone. Due to the exceptionally large war damage to Warsaw during World War II, rapid postwar reconstruction, and significant expansion, the city is characterized by a very large diversity of urban development density and a much larger amount of green areas compared to most large cities, such as old Western European agglomerations. The scientific novelty of the work is also the fact that the soil moisture content was analyzed using the TVDI/qTVDI (Temperature Vegetation Dryness Index Estimation) indexes obtained by using the so-called triangle methods in NDVI-LST space, based on satellite observations. Such analyses have not been performed so far in urban areas, while in the article, many new results were obtained on this subject. For example, Pearson’s correlation coefficients between LST, NDBI, NDVI, and qTVDI calculated for the entire area of Warsaw on 8 August 2020 were 0.78, 0.45, and −0.35, respectively. Another important aspect of the work is that it includes comparative studies of the impact of the abovementioned factors on the temperature of the Earth’s surface at the level of different city districts. As a result, it was possible to more effectively study the impact of the abovementioned factors on the temperature of the Earth’s surface at the scale of local administrative units. Thanks to the obtained results, urban planners will be able to reduce urban hazard risks caused by climate change

Geostatistical Methods as a Tool Supporting Revitalization of Industrially Degraded and Post-Mining Areas

Post-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