GIS and Remote Sensing

Volume XXII |

Flood risk modelling using HEC-RAS and GIS in the semi-urban water-shed of Oued Ziad (Constantine, North-Eastern Algeria)

Abstract: The study of flood risk in Algerian cities has become essential given the multiple issues at stake (urbanization, urban sprawl, easements, infrastructure, soil structure, etc.), which constitute vulnerable elements, as well as their frequen-cy and repetition in time and space. This has become a problem for the city and the urban environment, particularly in large metropolises such as Constantine. The watershed of Oued Ziad located in the northwestern part of the city of Constantine has experienced exceptional flooding, causing loss of life and property in the Jebli Ahmed agglomeration in the Hamma Bouziane township. The main objective of this research is to identify the factors aggravating the risk of flooding in the Oued Ziad watershed, to analyze the frequency of maximum daily rainfall to determine peak flows for different return periods of 10, 20, 50, 100 and 1000 years, and to map the extent of the flood hazard in the Oued Ziad watershed for a centennial flow, using geographic information systems and HecRas software. The simulation results show the overflow of Oued Ziad on national road N°27, affecting a part of the agglomeration located downstream by a centennial peak flow equal to 50. 98 m3/s and a water height exceeding 3 m, which confirms the extent of the area exposed to risk during the flood that occurred on 19/9/2018. The field survey shows that several anthropic factors in-crease the risk of flooding while the capacity of the existing hydraulic structures is insufficient to evacuate water during floods, which requires the development of this watercourse and its banks to protect the population and its property from the risk of flooding and to reduce the impact on the city’s environment and socio-economic activities.

Volume XXII |

Determination for automated land-use / land cover change detection of Keti Bunder, Indus Delta, Pakistan, by using satellite remote sensing techniques

Abstract: The Land use/Land cover (LULC) has a substantial role in planning and monitoring natural resource utilization, in the framework of the ongoing surge in human demands in the current ecosystem. Satellite remote sensing provides modern methods for locating and mapping Land use/Land cover patterns and their spatial changes. This paper discusses the evaluation of the LULC classes characteristic of Keti Bunder during the years 2015 and 2020, by using satellite remote sensing; the paper also uses Geo-informatics to study and investigate the temporal LULC variations that occurred over time. According to the empirical findings, there have been significant spatial changes, with less dry mudflats and unoccupied land overall. In comparison, the findings of the research point to inter-conversion of the area between LULC classes, i.e. mangrove areas, turbid water, wet mudflat, dry mudflat and barren land/vacant land. Overall, these geographical alterations show that the environment has been significantly impacted due to recent extreme weather events in the region.

Volume XXII |

Change detection analysis using Landsat images on Balurghat Municipality, West Bengal, India

Abstract: The major focus of the current study is a spatio-temporal analysis of land use and land cover changes in Balurghat Municipality, West Bengal, using remote sensing and geographic information systems (G.I.S.) from 1990 to 2020. The primary goals are to identify changes in land use and land cover and to look at the key influences and how they affect the dynamics of the landscape. The Landsat images of the study area are classified into five categories with the help of GIS software and Google verified and validated by the process of accuracy assessment. An image has been classified digitally with the help of the Supervised Image Classification method under Maximum Likelihood Classification techniques which also helps to identify the transformation of land from vegetation cover to built up area.

Volume XX |

Green open space detection and mapping using planetscope-3A image with vegetation index approach and supervised classification in Banda Aceh, Indonesia

Abstract: Role of Green Open Space (GOS) is essential in creating a comfortable environment in cities. It is detected using a high-resolution satellite image, Planetscope-3A. This study aimed to classify landcover in Banda Aceh using a multispectral classification of Planetscope-3A image and to assess the applicability of Planetscope-3A image to identify GOS in Banda Aceh. The multispectral classification was used with a supervised classification-maximum likelihood algorithm that refers to normalized difference vegetation index (NDVI) transformation to obtain eight landcover classes. Additionally, field observation was used to retrieve sample points determined by Stratified Random Sampling. The classification detected eight landcover classes comprising non-GOS objects (water, developed, barren) and GOS objects (trees, shrubland, herbaceous, wetland, and cultivated). The result was combined with 128 samples data of field, producing an accuracy of 76.036 % and a kappa value of 0.726. Landcover was dominated by developed class with 29.739 km2 or 53.6 % of study area total with an accuracy of 94.094 %. Furthermore, GOS in Banda Aceh included 19.589 km2 or 35.291 % of the study area, consisting of trees (6.863 km2, accuracy 79.396 %), Shrubland (8.216 km2, accuracy 59.413 %), Herbaceous (4.132 km2, accuracy 73.564 %), Cultivated (0.291 km2, accuracy 73.475 %), and Wetlands (0.088 km2, accuracy 70.185 %). This concludes that Banda Aceh has a sufficient area of GOS. The result of GOS detection using Planetscope-3A image with supervised classification-maximum likelihood algorithm could be reference data and recommendation in managing sustainable development in Banda Aceh.

Volume XIX |

Landslide-susceptibility Analysis, Mapping and Validation in the Bălăcița Piedmont (South-West Romania)

Abstract: This work presents the results of applying the GIS matrix method (GMM) to the mapping and validation of landslide-susceptibility analysis in different sectors of the Bălăciţa Piedmont. The main objective of the paper concerns the achievement of landslide-susceptibility maps based on the inventory, classification and description of the landslides within the study area. The starting point was represented by the DEM and, subsequently, based on the lithological data, other determinant factors were analyzed and reclassified in a vectorial format: slope angle, slope elevation and slope aspect. After the factors that determine instability were identified for each type of mechanism, susceptibility maps were drawn. In the resulting landslide-susceptibility map a model for the validation is presented (based on the determination and calculation of a set of landslides not included in the susceptibility analysis). The landslide-susceptibility maps of the Bălăciţa Piedmont are preventive tools intended to minimize risks in the threatened areas, especially near the settlements that are located on the left slope of the Jiu river and witness the reactivation of old landslides.