The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia

Abstract

The result of the accuracy by using cross-correlation matrix between the LULC model in 2015 with the LULC reference in 2015 is 75.88 %. The dynamics of LULC changes showed that area-class forest, dry land, paddy fields and shrubbery would be expected to experience an area decreases in the extent from the year 2015 to 2050, with the rate of change in average: 10.52, 13.22, 14.49 and 1.15 ha/year, respectively. Meanwhile, the area-class bare soil, plantation, settlement and water body would be expected to experience an area increases, with the rate of change in average: 6.79, 11.14, 11.49 and 9.7 ha/year, respectively. Furthermore, flood damage assessment can be calculated by estimating LULC area affected by the flood, which is determined based on the overlay between LULC maps from the result of Markov-CA with flood maps from the result of Monte Carlo algorithm. Under current conditions, estimated flood damage exposure to extreme flood events with return periods of 100 years for the water level scenario Hc = 3 m and Hc = 5 m is more than €520 and €958 million, respectively.

The dynamics of shoreline change analysis based on the integration of remote sensing and geographic information system (GIS) techniques in Pekalongan coastal area, Central Java, Indonesia

“…The second stage converts radian values to reflectance values, as in Equation 2. This second stage of the process refers to Chavez (1988), NASA (2011), USGS (2013a, 2013b), and Yulianto et al (2016)…”

基于情景模拟的上海土地利用变化预测及其水文效应

“…美国克拉克大学研发的 Terrset 软件中的 CA-Markov 模型在国内外应用较为广泛 [11][12][13][14] ， 主要应用于不同地区的土地利用变化和预测研究，并且预测结果精度较高 [13] 。 表 1 修正 SCS 模型的误差统计 [9] [19][20] ，以降低城市暴露性和脆弱性。同时，上 海应改造现有排水系统，适当提高防涝标准，做到市区及周边扩张区将区域防涝标准提 高至 50~100 a 一遇 (主干道 100 a 一遇) ，市郊城镇化集中区 (尤其是黄浦江上游地区) 将区域防涝标准提升至 30~50 a 一遇，其他区域防涝标准提升至 10~30 a 一遇 [19] 。 5) 另外，本文在进行土地利用模拟时仅考虑了城市土地利用总体规划与城市总体规 划等政府政策的影响，而土地利用变化模拟是一个异常复杂的过程，还会受城市化发展 水平、社会经济发展速度、政府政策变化等多因素的影响，而这些因素往往很难进行量 化 [13] ；为了更好地通过城市土地利用规划或城市总体规划等途径降低城市系统的暴雨灾 害暴露性与脆弱性，以高精度土地利用数据为基础，结合城市化水平、社会经济发展速 度、政府政策等因素预测分析城市土地利用发展趋势是我们未来努力的重要方向。 参考文献(References):…”

Approach for Analysis of Land-Cover Changes and Their Impact on Flooding Regime

“…The impact of climate change on magnitude and frequency of floods has been widely investigated [4][5][6]. Similarly, numerous researches focused on study on the impacts of land cover changes on watershed hydrological response [3,[7][8][9], however, only a few of them focused on analyzing the impact of land-cover change in river floods using distributed hydrological modeling [7].…”

“…Since the changes in land use/land cover and their spatial distribution have significant impacts on river flow and flooding [7,9], land-cover change analysis and its impact on hydrological processes become the prominent research topics in recent years [8,10]. To analyze such impacts of land-cover changes, it is essential to analyze dynamics of land cover changes, and it is also necessary to investigate hydrological impacts of land use changes using hydrological modeling [7].…”

“…To analyze such impacts of land-cover changes, it is essential to analyze dynamics of land cover changes, and it is also necessary to investigate hydrological impacts of land use changes using hydrological modeling [7]. The dynamics of land-cover change can be monitored and observed by using remotely sensed satellite-based data [9], and land-cover maps can also be generated by using satellite data such as Landsat images [3,9,11,12] and Moderate Resolution Imaging Spectroradiometer (MODIS) images [13,14].…”