No abstract

Existing drought-impacted data are generally rooted from individual reports, which under-represent spatial information. To improve the report, some meteorological satellites have been employed. Nonetheless, due to lacking of spatial resolution, the scale of the data is often excessively coarse. With the availability of long-term Landsat data, estimated extent of drought has been studied. One of the latest methods for this purpose is Vegetation Supply Water Index (VSWI). VSWI is defined as a ratio between vegetation index (in this case NDVI) and land surface temperature (LST, presented in Kelvin). Both data can be derived from remote sensing data containing multispectral reflectance and thermal data, which are available in Landsat data after calibration procedure. In this research, Landsat 7 sensor was applied considering its temporal span. Landsat data were atmospherically corrected to avoid misinterpretation of the results. We found that VSWI can accommodate various state of drought in agricultural fields. Severely affected fields are represented in dark tone, illustrating the absence of vegetation cover when surface temperature rises. Nonetheless, shortcomings of the technique are visually observable. Based on two kinds of rice field (irrigated and rainfed) coupled with two states of field condition (wet and dry), we conclude that dried and waterlogged irrigated rice fields are inseparable due similar value of NDVI. In contrast, vegetated rice field has fairly high VSWI value. The results indicate that further analysis incorporating water index can improve discrimination process.

The study analysis of the land surface temperature (LST) is crucial to maintain the environmental quality of climatic conditions, particularly in Jember as the forest buffer region in the eastern part of Java, Indonesia. In this paper, the land surface temperature (LST) distributions were investigated using Landsat 8 OLI/TIRS images in about 24,008.67 ha of the southern part of Jember. The land surface emissivity (LSE) is also provided in deriving the land surface temperature (LST) from satellite images. The LSE value in the Earth’s surface is retrieved from NDVI (Normalized Difference Vegetation Index) and fractional vegetation cover (Pv). In this case, the reflectance of NIR (Near Infrared) and red bands of Landsat 8 OLI sensor have been acquired to derive NDVI and Pv distribution. Therefore, the LST can be obtained from the LSE coefficient result and brightness temperature (BT) of Landsat 8 TIRS. The results showed that the LST average in the study area increased significantly from 20°C in 2013 to 26°C in 2018. This condition was triggered by the decreasing area with a high vegetation density about 5% of the study area from 2013 to 2018, which was figured out from the spatial distribution of NDVI and LSE.

Urban Heat Island (UHI) phenomenon is a particular climate change impact in urban areas that can trigger adverse effects on environmental conditions. This effect is usually worsened by increasing anthropogenic activities. While the impact of UHI has mostly been studied in metropolitans around the world, few studies are presented investigating the outcome in mid-sized cities. This study aims to assess spatial distribution of Urban Heat Island (UHI) in Bogor city, Indonesia, by utilizing thermal data (Band-10) from Landsat-8 OLI/TIRS. The Landsat imagery was acquired in May 2021, in the beginning of the dry season. The result of study shows Land Surface Temperature (LST) values ranged from 26.23 to 33.76°C, with an average temperature of 31.29°C, while the range of NDVI was between 0.08 to 0.55. Further, the correlation between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) was calculated to investigate the relationship between vegetation density and surface temperature condition for examining the outlook and possibilities to minimize the impact of UHI through improving vegetal conditions. A negative correlation suggests that expanding vegetation coverage can reduce urban heat island impacts by 35%, and other factors influence the rest. The land surface temperature threshold to determine UHI is 32.01°C, so the UHI area was identified at ca. 13.12 km2 around the city centre.