Abstract: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.

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.

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Remote sensing data with medium spatial resolution can provide useful information about Gross Primary Production (GPP), especially on the scale of urban areas. Most models of ecosystem carbon exchange that are based on remote sensing use some form of the light use efficiency (LUE) model. The aim of this work is to analyze the distribution of annual GPP in the urban area of Denpasar, Bali. Additional analysis using two types of satellite data (ALOS/AVNIR-2 and Aster) addresses the impact of spatial resolution on the detection of various ecosystem processes in Denpasar. Annual GPP estimated using ALOS/AVNIR-2 varied from 0.13 gC m . GPP as measured by ALOS/AVNIR-2 was lower than that from Aster because ALOS/AVNIR-2 has medium spatial resolution and a smaller spectral range than Aster. Variations in land use may influence the measured value of GPP via differences in vegetation type, distribution, and photosynthetic pathway type. The medium spatial resolution of the remote sensing data is crucial for discriminating different land cover types in heterogeneous urban areas. Given the heterogeneity of land cover over Denpasar, ALOS/AVNIR-2 detects a smaller maximum value of GPP than Aster, but the annual mean GPP from ALOS/AVNIR-2 is higher than that from Aster. Based on comparisons with previous work, we find that ALOS/AVNIR-2 and Aster satellite data provided more accurate estimates of maximum GPP in Denpasar and in the tropical Kalimantan-Indonesia and Amazon forest than estimates derived from the MODIS GPP product (MOD17).

There was change of expanding land use in Bedugul, It is necessary to monitor the change of highland of Bali, catchments area of Bcratan, Buyan and Tamblingan lakes. In order to control land use change and to anticipate degradation of hydrology function of this area. This study is to monitor the land use change by remote sensing and GIS technique. To evaluate land use and land cover, aerial photograph imagery and Ikonos imagery were used.Over 22 years of observation (1981 -2003), there \vas land use changes in the calchments area of Bcratan, Buyan and Tamblingan lakes at Bedugul area. The area of settlement increased by 62.6 ha, dry land vegetable crops increased by 7.5 ha, and shrub increased by 26.2 ha. On the other hand, areas of coffee crops and forest decreased by 116.5 ha and 32.5 ha, respectively. The surface area of Buyan Lake was also decreased, due to sedimentation caused by erosion in the vegetables dry land crops. Planning the land use study on erosion and soil-water conservation in this area are necessary, in order to control land use change, erosion, and sedimentation in the lakes