Smoldering peat fires in Indonesia are responsible for large quantities of trace gas and particulate emissions. However, to date no satellite remote sensing technique has been demonstrated for the identification of smoldering peat fires. Fires have two distinct combustion phases: a high temperature flaming and low temperature smoldering phases. The flaming phase temperature is approximately twice that of the smoldering phase. This temperature differential results in a spectral displacement of the primary radiant emissions of the two combustion phases. It it is possible to exploit this spectral displacement using widely separated wavelength ranges. This paper examines active fire features found in short-wave infrared (SWIR) and long-wave infrared (LWIR) nighttime Landsat data collected on peatlands in Sumatra and Kalimantan. Landsat 8's SWIR bands are on the leading edge of flaming phase radiant emissions, with only minor contribution from the smoldering phase. Conversely, Landsat 8's LWIR bands are on the trailing edge of smoldering phase radiant emissions. After examining the LWIR fire features, we conclude that they are the result of smoldering phase combustion. This has been confirmed with field validation. Detection limits for smoldering peat fires in Landsat 8 is in the 40-90 m 2 range. These results could lead to improved management of peatland fires and emission modeling.
This study presents the information on the dynamics of changes in land use/land cover (LULC) spatially and temporally related to the causes of flooding in the study area. The dynamics of LULC changes have been derived based on the classification of Landsat imagery for the period between 1990 and 2016. Terrain surface classification (TSC) was proposed as a micro-landform classification approach in this study to create flood hazard assessment and mapping that was produced based on the integration of TSC with a probability map for flood inundation, and flood depth information derived from field observation. TSC as the micro-landform classification approach was derived from SRTM30 DEM data. Multi-temporal Sentinel-1 data were used to construct a pattern of historical inundation or past flooding in the study area and also to produce the flood probability map. The results of the study indicate that the proposed flood hazard mapping (FHM) from the TSC as a micro-landform classification approach has the same pattern with the results of the integration of historical inundation or previous floods, as well as field investigations in the study area. This research will remain an important benchmark for planners, policymakers and researchers regarding spatial planning in the study area. In addition, the results can provide important input for sustainable land use plans and strategies for mitigating flood hazards.
Satellite-based burned area products are accurate for many regions. However, only limited assessments exist for Indonesia despite extensive burning and globally important carbon emissions. We evaluated the accuracy of four MODIS-derived (moderate resolution imaging spectroradiometer) burned area products (MCD45A1 collection 5.1, MCD64A1 (collection 5.1 and 6), FireCCI51), and their sensitivity to burned-area size and temporal window length used for detection. The products were compared to reference burned areas from SPOT 5 imagery using error matrices and linear regressions. The MCD45A1 product detected <1% of burned areas. The other products detected 38%–48% of burned area with accuracies increasing modestly (45%–57%) when smaller burns (<100 ha) were excluded, with MCD64A1 C6 performing best. Except for the MCD45 product, linear regressions showed generally good agreement in peatlands (R 2 ranging from 0.6 to 0.8) but detections were less accurate in non-peatlands (R 2 ranging from 0.2 to 0.5). Despite having higher spatial resolution, the FireCCI51 product (250 m) showed lower accuracy (OE = 0.55–0.88, CE = 0.33–0.50) than the 500 m MCD64A1 C6 product (OE = 0.43–0.79, CE = 0.36–0.51) but it was comparable to the C5.1 product (OE = 0.52–0.91, CE = 0.37–0.67). Dense clouds and smoke limited the accuracies of all burned area products, even when the temporal window for detection was lengthened. This study shows that emissions calculations based on burned area in peatlands remain highly uncertain. Given the globally significant amount of emissions from burning peatlands, specific attention is required to improve burned area mapping in these regions in order for global emissions models to accurately reflect when, where, and how much emissions are occurring.
Coastal landforms are located in the interface zone between atmosphere, ocean and land surface systems formed by the geomorphic process of erosion, depositional, and subsidence. Studying the dynamics of coastal landform change is important for tracing the relationship between coastal landform changes and tidal flooding in the coastal areas of Pekalongan, Indonesia. The method of integrating remote sensing data with geographic information system (GIS) techniques has been widely used to monitor and analyze the dynamics of morphology change in coastal landform areas. The purpose of this study is to map the dynamics of landform change in the study area from 1978 to 2017 and to analyze its implications for the impact of tidal flooding. The results of the mapping and change analysis associated with coastal landforms can be classified into four landform types: beach, beach ridge, backswamp and alluvial plain. Changes in coastal morphology and landform topography affected by land subsidence and changes in land use/ land cover have contributed to the occurrence of tidal flooding in the study area. Beach ridges perform an important role as natural levees which hold back and prevent the entry of seawater at high tide in coastal areas. A limitation of this study is that, as it focuses only on the physical aspects of coastal landform characteristics for one of the factors causing tidal flooding.
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