Detection of Peat Fire Risk Area Based on Impedance Model and DInSAR Approaches Using ALOS-2 PALSAR-2 Data
Detection of Peat Fire Risk Area Based on Impedance Model and DInSAR Approaches Using ALOS-2 PALSAR-2 Data
复制标题
使用 ALOS-2 PALSAR-2 数据基于阻抗模型和 DInSAR 方法检测泥炭火灾风险区域
DOI：
10.1109/access.2019.2899080
复制
发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
J. S. Sri Sumantyo
中科院分区：
文献类型：
--
作者：
J. Widodo;Y. Izumi;A. Takahashi;H. Kausarian;D. Perissin;J. S. Sri Sumantyo
印尼森林火灾多发生在泥炭地地区。地下水位（GWT）超过40厘米，从土壤表面的干旱泥炭地地区已成为具有高火灾潜力的退化地区。本文提出了一种新的检测泥炭火灾危险区结合两种方法：阻抗模型和差分干涉SAR（DInSAR）技术，这是基于知识的年沉降率与GWT。本文通过将表面粗糙度信息作为新奇的一部分整合到模型中，对以前的阻抗模型进行了修改。最后，利用GWT的地面真实数据对该方法进行了验证.利用阻抗模型，基于干泥炭地的后向散射系数模拟，成功地探测出泥炭火灾危险区。基于模拟模型，干泥炭的后向散射系数的平均值、最小值和最大值分别为−13.97、−11.5和−17.29 dB。模拟的后向散射系数与ALOS-2/PALSAR-2数据的后向散射系数之间的相关系数为0.8，均方根误差为1.4。利用DInSAR方法，成功地检测了干泥炭地面积。GWT测量值和模型之间确认的显著相关性对于A对为0.71，对于B对为0.85。这两种方法都成功地识别了泥炭火灾风险区。泥炭土的介电常数还表明，感兴趣的地区的土壤条件非常干燥，表明潜在的泥炭火灾风险。建议分别采用两种模型来获得检测分析的精密度。
Forest fire in Indonesia occurs mostly in peatland area. Dry peatland areas with groundwater table (GWT) more than 40 cm from the soil surface have become degradation areas with high potentials to fire. This paper presents a new novel to detect a peat fire risk area by incorporating two methods: the impedance model and the differential interferometric SAR (DInSAR) technique which is based on the knowledge of annual subsidence rate associated with the GWT. The previous impedance model is modified in this paper by integrating the surface roughness information in the model as a part of novelty. The proposed method was then validated with ground truth data of GWT. By using an impedance model, this paper successfully detected peat fire risk area based on the backscattering coefficient simulation of dry peatland. Based on the simulation model, the average, minimum, and maximum of backscattering coefficient of dry peat are −13.97, −11.5, and −17.29 dB, respectively. The correlation coefficient between the simulated backscattering coefficient and backscattering from ALOS-2/PALSAR-2 data is 0.8 with root mean square error of 1.4. By using the DInSAR method, detection of dry peatland area was successful. The significant relationships confirmed between GWT measurement and model are 0.71 for Pair A and 0.85 for Pair B. Both methods showed that peat fire risk areas were identified successfully. The dielectric constant of the peat soil also revealed that the soil condition of the area of interest is very dry indicating the potential to peat fire risk. Employing two models, respectively, were recommended to get precision of detection analysis.