Urban Recovery Process in Pisco After the 2007 Peru Earthquake

2013 ◽  
Vol 8 (2) ◽  
pp. 356-364 ◽  
Author(s):  
Osamu Murao ◽  
◽  
Tomoyo Hoshi ◽  
Miguel Estrada ◽  
Kazuya Sugiyasu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Quantitative Analysis ◽  
Physical Environment ◽  
Field Survey ◽  
Remote Sensing Data ◽  
Recovery Process ◽  
Satellite Imaging ◽  
Victim Satisfaction ◽  
Earthquake Research ◽  
Post Disaster

Post-disaster urban recovery is a significant matter in disaster management that represents government efforts after a disaster and victim satisfaction with these efforts in affected areas. Understanding the recovery process is a procedure necessary for evaluating government strategy. From this view, the authors dealt with the recovery process at Pisco, the area most devastated in the 2007 Peru Earthquake. Research was conducted through the following procedure: (1) a field survey including interviews was carried out in July 2012 to clarify post-earthquake conditions in urban Pisco, especially from the viewpoint of the physical environment, (2) recovery conditions were compared with damage conditions investigated by CISMID just after the event using satellite imaging and building recovery data obtained in the survey, and (3) post-earthquake recovery was quantitatively analyzed in terms of building recovery. Results indicated that 93.2% of seriously or severely damaged buildings had been reoccupied. In addition to quantitative analysis, recovery-related problems are discussed based on interviews. Results will be useful in the next stage of our research using remote sensing data for the chronological understanding of the post-earthquake urban recovery process in Pisco.

scholarly journals Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

2019 ◽  
Vol 4 (6) ◽  
pp. 84-89 ◽  
Author(s):  
Aniekan Effiong Eyoh ◽  
Akwaowo Ekpa
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Analysis ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Land Use Land Cover ◽  
Positive Growth ◽  
Bare Land ◽  
Erdas Imagine

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.

Relationships in Diversity, Vegetation Indexes and Water Area in Terminal Lake of the Tarim River, Northwest China

Ecologies ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 332-344
Author(s):  
Xinfeng Zhao ◽  
Tao Lin ◽  
Hailiang Xu ◽  
Ai Shajiang Aili ◽  
Wanyu Zhao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Plant Diversity ◽  
Groundwater Level ◽  
Field Survey ◽  
Remote Sensing Data ◽  
Northwest China ◽  
Vegetation Coverage ◽  
Tarim River ◽  
Lake Area ◽  
The Tarim River

To examine the variation in water and vegetation coverage areas, the groundwater level and plant diversity in the terminal lake of the Tarim River, northwest China, both the monitoring data of a field survey consisting of surface samples and remote sensing data for 20 years (2000–2019) were analyzed by using field survey and indoor remote sensing methods. The results showed that (1): from 2000 to 2019, water and vegetation areas increased significantly, especially the trend of vegetation areas becoming more significant, with an average annual increase of 13.9 km2/a; (2): the plant diversity increased first and then decreased; the species richness and Pielou index in the study area were 9.0 and 0.80 in 2005, but only 2.00 and 0.08 in 2000, respectively; species composition tends to be simplified; (3): with the increase in the lake area, the groundwater level showed an up-lifted trend; the correlation between the two was significant, but there was a lag in the response of the groundwater level.

scholarly journals Pemetaan Tingkat Kenyamanan Jalur Sepeda Daerah Malioboro Dengan Menggunakan Data Penginderaan Jauh

2017 ◽  
Author(s):  
Wenang Anurogo ◽  
Wikan Jaya Prihantarto ◽  
Isti Fadhatul K ◽  
Asih Dewi Nugraheni ◽  
Dana Krisna Prabawa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Spatial Data ◽  
Field Survey ◽  
Data Extraction ◽  
Remote Sensing Data ◽  
Comfort Level ◽  
Traffic Density ◽  
Sensing Data ◽  
Bicycle Lane

Bicycles are an environmentally friendly device of transportation. Today many big cities are facilitating bicycle users with a special bicycle lane. Yogyakarta is a place of cultural acculturation. One of the cultures presented is the culture of walking and cycling for the society. One of the famous location of cycling place in Yogyakarta is in Malioboro area. Aside from being the Central Bussines District (CBD) of Yogyakarta, Malioboro area is also an iconic area for travelers to enjoy the atmosphere in it. This research aims to determine Comfort Level Of Bicycle Lane in Malioboro and presents it into a spatial data that can be easily understood. The comfort level of cyclists can be extracted from remote sensing data and field survey data. The level of comfort is extracted into parameters that affect the comfort level of cyclists, especially in the area Malioboro Yogyakarta. The parameters used in this study resulted from high-resolution remote sensing data extraction are shade vegetation, side obstacles, bike lane mark, path position, traffic density, and relief. The results show that there are 8 bike paths with very comfortable class, 16 bicycle lanes with comfortable class, 7 lines with medium grade, 38 bike lines with uncomfortable class and 20 bike lanes with very uncomfortable class

scholarly journals Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China

2020 ◽  
Vol 12 (1) ◽  
pp. 164 ◽  
Author(s):  
Wutao Yao ◽  
Yong Ma ◽  
Fu Chen ◽  
Zhishu Xiao ◽  
Zufei Shu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Disaster Recovery ◽  
Vegetation Index ◽  
Coniferous Forest ◽  
Recovery Process ◽  
Forest Growth ◽  
Forest Recovery ◽  
Ice Storm ◽  
The Impact ◽  
Post Disaster

Ice storms greatly affect the structure, dynamics, and functioning of forest ecosystems. Studies on the impact of such disasters, as well as the post-disaster recovery of forests, are important contents in forest biology, ecology, and geography. Remote-sensing technology provides data and methods that can support the study of disasters at the large-to-medium scale and over long time periods. This study took Chebaling National Nature Reserve in Guangdong Province, China, as the study area. First, field-survey data and remote-sensing data were comprehensively analyzed to demonstrate the feasibility of replacing the forest stock volume with the mean annual value of the Enhanced Vegetation Index (EVI), to study forest growth and change. We then used the EVI from 2007 to 2017, together with a variety of other remote-sensing and forest sub-compartment data, to analyze the impact of the 2008 ice storm and the subsequent post-disaster recovery of the forest. Finally, we drew the following conclusions: (1) Topography had a considerable effect on disaster impact and forest recovery in Chebaling. The forest at high altitudes (700–1000 m) and on steep slopes (25–40°) was seriously affected by this disaster but had a stronger post-disaster recovery ability. Meanwhile, the hardest-hit area for coniferous forest was higher and steeper than that for broad-leaved forest. (2) In the same terrain conditions, coniferous forests were less affected by the disaster than broad-leaved forests and showed less variation during the post-disaster recovery process. Nevertheless, broad-leaved forests had faster recovery rates and higher recovery degrees; (3) Under the influence of human activities, the recovery and fluctuation degree for planted forest in the post-disaster recovery process was significantly higher than that for natural forest. The study suggests that forest has high disaster resistance and self-recovery ability after the ice storm, and this ability has a strong correlation with the type of forest and the topographic factors such as elevation and slope. At the same time, human intervention can speed up the recovery of forests after disasters.

scholarly journals SEMANTIC SEGMENTATION METHOD ACCELERATED QUANTITATIVE ANALYSIS OF THE SPATIAL CHARACTERISTICS OF TRADITIONAL VILLAGES

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 933-939
Author(s):  
M. Zhang ◽  
Z. Li ◽  
X. Wu
Keyword(s):  
Remote Sensing ◽  
Quantitative Analysis ◽  
Data Augmentation ◽  
Data Extraction ◽  
Remote Sensing Data ◽  
Semantic Segmentation ◽  
Mathematical Methods ◽  
Spatial Characteristics ◽  
Spatial Features ◽  
Short Period

Abstract. Rapid investigation and quantitative analysis are crucial for heritage conservation and renewal design. As an important category of architectural heritage - traditional settlements - with their large number and complex spatial characteristics, their spatial character patterns are an important support to assist settlement conservation and renewal design. However, the current means of analysis often requires manual data collection, secondary mapping of the collected data, extraction of individual elemental patterns and village boundaries. Then settlement boundary form, settlement density will be calculated by mathematical methods. The above methods are inefficient and prone to manual mapping errors, making it difficult to quantify and analyze a large number of traditional villages in a short period of time. Semantic segmentation is a computer vision technique for quickly segmenting different objects. Based on the collected remote sensing data of traditional villages, this paper established a dataset of semantic segmentation of spatial features of traditional settlements, segmenting village buildings, water systems, roads and plants. Using Transfer learning, data augmentation and other methods, a model was trained that can automatically segment elements of the villages. From the national traditional villages that have been announced so far, 60 traditional villages from different regions in the north and south were selected for analysis. The experiments show that the model established in this paper has an accuracy rate of above 86% in segmenting elements of villages, can effectively identify the location of different elements in remote sensing images, effectively improves the quantification rate of spatial features of settlements and saves the cost of mapping and data transcription. The results of the spatial characteristics of the 60 villages studied in this paper can also provide some theoretical basis and inspiration for the study, conservation, design and transformation of traditional villages.

scholarly journals Pemetaan Cepat Kawasan Terdampak Bencana Longsor dan Banjir di Kabupaten Bangli, Provinsi Bali

2017 ◽  
Vol 31 (2) ◽  
pp. 44 ◽  
Author(s):  
Theresia Retno Wulan ◽  
Wiwin Ambarwulan ◽  
Anggara S. Putra ◽  
Mega D Putra ◽  
Dwi Maryanto ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Field Survey ◽  
Rapid Mapping ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Landslide Event ◽  
Aerial Vehicle ◽  
Post Disaster

Abstrak Teknologi penginderaan jauh mengalami perkembangan yang sangat pesat. Salah satunya adalah teknologi akuisisi data dengan menggunakan UAV (Unmanned Aerial Vehicle).  Teknologi UAV dapat dipergunakan dalam berbagai bidang, salah satunya adalah bidang kebencanaan. Tujuan penelitian ini adalah untuk melakukan pemetaan secara cepat kawasan terdampak bencana banjir dan longsor di Kabupaten Bangli, Bali dengan menggunakan teknologi UAV. Metode yang digunakan adalah pemotretan udara dengan UAV, survei lapangan dan analisis laboratorium. Pemotretan udara dilakukan satu hari pasca kejadian longsor dengan ketinggian jelajah pesawat antara 100-120 meter di atas permukaan tanah. Resolusi spasial yang dihasilkan antara 4,5 - 6,5 cm. Wilayah yang berhasil dipetakan adalah wilayah yang terdampak banjir dan longsor di Desa Songan A serta Songan B, wilayah terdampak banjir bandang Yeh Mampeh di Desa Batur Selatan, serta wilayah terdampak longsor di Desa Sukawana dan Desa Awan. Berdasarkan hasil pemotretan udara, dapat diketahui luasan daerah terdampak longsor. Lebih lanjut, strategi rehabilitasi dan rekonstruksi dapat dilakukan dengan menggunakan hasil pemotretan udara.  Abstrak Remote sensing technology is experiencing rapid developments. One of which is in the field of data acquisition that has currently adopted the use of Unmanned Aerial Vehicle (UAV). UAV technology is, for instance, employed in various studies related to disasters. This research aimed to perform a rapid mapping of flood- and landslide-affected areas in Bangli Regency, Bali using UAV technology. The applied methods included UAV-assisted aerial photography, field survey, and laboratory analysis. The aerial photography was conducted one day after the landslide event and at a recording altitude of 100-120 m above the ground. The spatial resolution produced in the photography was 4.5-6.5 cm. The mapped areas were the ones affected by floods and landslides in Songa A and Songa B Villages, flash floods in Yeh Mampeh, Batur Selatan Village, and landslides in Sukawana and Awan Villages. The aerial photography also provided the extent of the landslide-affected areas. Therefore, the post-disaster rehabilitation and reconstruction strategies can be implemented using the results of the aerial photography.  

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