Remotely sensed imagery is a type of data that is compatible with the monitoring and mapping of changes in built-up and bare land within urban areas as the impacts of population growth and urbanisation increase. The application of currently available remote sensing indices, however, has some limitations with respect to distinguishing built-up and bare land in urban areas. In this study, a new index for transforming remote sensing data for mapping built-up and bare land areas is proposed. The Enhanced Built-Up and Bareness Index (EBBI) is able to map built-up and bare land areas using a single calculation. The EBBI is the first built-up and bare land index that applies near infrared (NIR), short wave infrared (SWIR), and thermal infrared (TIR) channels simultaneously. This new index was applied to distinguish built-up and bare land areas in Denpasar (Bali, Indonesia) and had a high accuracy level when compared to existing indices. The EBBI was more effective at discriminating built-up and bare land areas and at increasing the accuracy of the built-up density percentage than five other indices.

It is important to understand the characteristics of Indonesian rainfall within the world’s climate system. The large rainfall in the Indonesian archipelago plays an essential role as a central atmospheric heat source of the Earth’s climate system throughout the year. Monthly rainfall satellite data, measured by the Tropical Rainfall Measuring Mission (TRMM) 3B43 over the course of 13 years, were employed to analyse monthly means, total means, maximum and minimum variability, standard deviation, and the trends analysis of Indonesian rainfall variability. The rainfall estimated from satellite data was then compared to the rain gauge data over the Indonesian region to determine the accuracy level. The results show that oceans, islands, monsoons, and topography clearly affect the spatial patterns of Indonesian rainfall. Most high-rainfall events in Indonesia peak during the December–January–February (DJF) season and the lowest rainfall events occur during the June–July–August (JJA) season. Those conditions are associated and generated with the northwest and southeast monsoon patterns. High fluctuations between maximum and minimum monthly rainfall data of over 400 mm month⁻¹ occur over Jawa (Java) Island, the Jawa Sea, and southern Sulawesi Island. A high annual and monthly rainfall typically occurs throughout Indonesia over island areas. The trend analysis shows an increasing trend in rainfall from 1998 to 2010 in Kalimantan, Jawa, Sumatra, and Papua. Decreasing rainfall trends occur along the west and south coast of Sumatra, eastern Jawa, southern Sulawesi, Maluku Islands, western Papua, and Bali Island.

Remote sensing data of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis for 13 years have been used to observe the spatial patterns relationship of rainfall with El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) over Indonesia. Linear correlation was measured to determine the relationship level by the restriction analysis of seasonal and monthly relationship, while the partial correlation technique was utilized to distinguish the impact of one phenomenon from that of the other. Application of remote sensing data can reveal an interaction of spatial‐temporal relationship of rainfall with ENSO and IOD between land and sea. In general, the temporal patterns relationship of rainfall with ENSO confirmed fairly similar temporal patterns between rainfall with IOD, which is high response during JJA (June–July–August) and SON (September–October–November) and unclear response during DJF (December–January–February) and MAM (March–April–May). Spatial patterns relationship of both phenomena with rainfall is high in the southeastern part of Sumatra Island and Java Island during JJA and SON. During the SON season, IOD has a higher relationship level than ENSO in this part. In the spatial‐temporal pattern seen, a dynamic movement of the relationship between IOD and ENSO with rainfall in Indonesia is indicated, where the influence of ENSO and IOD started during JJA especially in July in the southwest of Indonesia and ended in the DJF period especially in January in the northeast of Indonesia.