Remotely sensed vegetation indices (VI) such as the Normalized Difference Vegetation Index (NDVI) are increasingly used as a proxy indicator of the state and condition of the land cover/vegetation, including forest. However, the Enhanced Vegetation Index (EVI) on the outcome of forest change detection has not been widely investigated. We compared the influence of using EVI and NDVI on the number and time of detected changes by applying Breaks for Additive Seasonal and Trend (BFAST), a change detection algorithm. We used MODIS 16-day NDVI and EVI composite images (April 2000-April 2012) of three pixels (pixels 352, 378, and 380) in the tropical peat swamp forest area around the flux tower of Palangka Raya, Central Kalimantan. The results of BFAST method were compared to the Normalized Difference Fraction Index (NDFI) maps and the maps were validated by the hotspot of the Infrastructure and Operational MODIS-Based Near Real-Time Fire(INDOFIRE). Overall, the number and time of changes detected in the three pixels differed with both time series data because of the data quality due to the cloud cover. Nonetheless, we found that EVI is more sensitive than NDVI for detecting abrupt changes such as the forest fires of August 2009-October 2009 that occurred in our study area and it was verified by the NDFI and the hotspot data. Our results demonstrated that the EVI for forest monitoring in the tropical peat swamp forest area which is covered by intense cloud cover is better than that NDVI. Nonetheless, further research with improving spatial resolution of satellite images for application of NDFI is highly recommended.
The hotspot of MODIS Aqua/Terra represents the high risk of land/forest fire due to an extreme temperature over the hotspot location. Spatial-temporal analysis of the hotspot can be used to map the regions with a high vulnerability of forest/land fires. This study has an objective to use hotspot data from MODIS Aqua/Terra to map the forest/land fires over the Humbang Hasudutan Regency from 2001 to 2019. In spatial, the hotspot mostly occurs in the eastern part of the study area (Doloksanggul and Pollung), which this area has assigned as the peatland area. Based on land cover, the hotspot often detected over the dryland agriculture, dryland with shrubs, and bare soil. In temporal, the hotspot mostly increases during the dry seasons such as February, June, and July. The hotspot decreases during the wet season, such as January, October, November, and December. Besides, there was an inversely proportional between the number of detected hotspots and rainfall over the study area.
This study aims to explore the contrasting characteristics of large-scale circulation that led to the precipitation anomalies over the northern parts of Sumatra Island. Further, the impact of varying the Asian–Australian Monsoon (AAM) was investigated for triggering the precipitation variability over the study area. The moisture budget analysis was applied to quantify the most dominant component that induces precipitation variability during the JJA (June, July, and August) period. Then, the composite analysis and statistical approach were applied to confirm the result of the moisture budget. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Anaysis Interim (ERA-Interim) from 1981 to 2016, we identified 9 (nine) dry and 6 (six) wet years based on precipitation anomalies, respectively. The dry years (wet years) anomalies over the study area were mostly supported by downward (upward) vertical velocity anomaly instead of other variables such as specific humidity, horizontal velocity, and evaporation. In the dry years (wet years), there is a strengthening (weakening) of the descent motion, which triggers a reduction (increase) of convection over the study area. The overall downward (upward) motion of westerly (easterly) winds appears to suppress (support) the convection and lead to negative (positive) precipitation anomaly in the whole region but with the largest anomaly over northern parts of Sumatra. The AAM variability proven has a significant role in the precipitation variability over the study area. A teleconnection between the AAM and other global circulations implies the precipitation variability over the northern part of Sumatra Island as a regional phenomenon. The large-scale tropical circulation is possibly related to the PWC modulation (Pacific Walker Circulation).
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