GIS and Remote Sensing

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.

Volume XIX |

Assessment of Soil Erosion by RUSLE Model using Remote Sensing and GIS – A case study of Ziz Upper Basin Southeast Morocco

Abstract: cause many environmental and socio-economic problems on -and off-site: loss of biodiversity, reduced productivity of agricultural land, siltation of dams, increased risk of flooding. The quantification of soil erosion is essential in the management and conservation of the soil and water resources. Modeling soil erosion can provide a lot of information to estimate soil loss and sediment yields at large-scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) integrated into a GIS was used to quantify soil losses in the large upper watershed of Ziz (4435 km2) in southeastern of Morocco. The RUSLE parameters were estimated based on data from satellite imagery, DEM-SRTM and national watershed management plan studies. The results show that annual average of the potential soil erosion is 489.5 t. ha-1. yr-1 and the specific sediment yield is 36.4 t. ha-1. yr-1. The main sources of sediment are in the watershed upstream parts and some deposition zones are located before the catchment outlet. These soil losses contribute to the annual siltation of the Hassan Eddakhil dam by a rate of 3.5%. The application of principal components analysis to soil erosion factors shows an important influence of the soil erodibility factor (K) followed by the topographic factor (LS) then crop management factor (C). These modeling results will provide data within the Moroccan southeastern High Atlas that can constitute a road map for future soil erosion projects and it can be a useful tool for proposing soil conservation strategies.

Volume XIX |

GRASS GIS for topographic and geophysical mapping of the Peru-Chile Trench

Abstract: The study area is located along the western continental margins of South America, Peru-Chile Trench south-east Pacific Ocean, geographically encompasses 90° to 60°W longitude and 55°S to 0° latitude. The study aims to perform a spatial analysis using GRASS GIS approach applied for processing and visualizing topographic and geophysical data on the study area. Data include following raster grids: topographic SRTM_15PLUS raster grid with 15 arc-second resolution, geoid model (EGM96), geophysical fields and gravity maps (marine free-air gravity and vertically corrected free-air gravity). The thematic grids were mapped by GRASS GIS modules and visualized for comparative analysis. Spatial analysis included plotting slope aspect, profile curvature, terrain elevation and modeled topographic classes based on the neighborhood analysis. The results include visualized geophysical and topographic maps of the study area showing correlation between the geophysical fields and topographic elevation. The variety of forms of the submarine relief of the Pacific Ocean seafloor was formed as a result of complex factors: tectonic movements, dislocations, active volcanism, geologic variations in rock density, which is reflected in visualized gravity and geoid maps. The actuality of the study is explained by high potential commercial interests in deep-water mineral resource deposits, oil and gas, which make ocean seafloor studies one of the most promising topics in geoscience. At the same time, the need for programming applications for big data analysis in geosciences requires testing advanced scripting approaches in cartography. Therefore, the current paper presents a multi-disciplinary approach combining geological analysis with technical cartographic aspects of data analysis and visualization.

Volume XIX |

Agriculture drought assessment based on remote sensing, cloud computing, multi-temporal analysis. A case study: the Mostiștea Plain (Romania)

Abstract: Agricultural drought is one of the most important natural hazards worldwide, affecting a significant proportion of the global population. Earth Observation multi-spectral imagery satellites can provide a comprehensive picture of all land and sea areas of the Earth. Free of charge and open access imagery from missions such as Sentinel-2 provides high quality imagery with rapid high revisit period. Earth Engine© developed by Google Inc. provides the possibility to view and analyse petabytes of remote sensing data in archives that include more than thirty years of satellite imagery and scientific datasets. This paper proposes a cloud- based computation approach and analysis of multi-temporal, high resolution Sentinel-2 imagery on the Mostiștea Plain (Romania) in order to evaluate the agriculture drought. Custom javascript code was created in the Code Editor for calculating and analyzing remote sensing-based indices between 2017 and 2019. The results were classified into six classes: Water, No drought, Light drought, Moderate drought, Heavy drought, Severe drought. According to the classification, the southern half of Mostiștea Plain was the most affected area by a heavy agricultural drought during 2017-2019 period.