CREATION OF SOIL PERMEABILITY MAPS TROUGH OBIA CLASSIFICATION OF VERY HIGH-RESOLUTION SATELLITE IMAGES

Abstract. In the last few months, we have been working on images acquired by the WorldView3 satellite over the city of Pavia with the final intent to create a soil permeability map. These maps can be particularly useful in various fields, such as water management and public green, for evaluate the correlation between overbuilt areas and pollution, the influence of vegetation on the temperature in within the different areas of the city, for the planning and monitoring of a sustainable transition of cities. To create such maps, it is essential to be able to identify various objects lying in the images, in our case we have done a classification of the image using the software Trimble eCognition™, applying Object-based Image Analysis (OBIA) approach and various classification methods, by applying fuzzy logic and supervised classification. The objects generated through various segmentations have been classified into 7 classes, water, fields, cultivated fields / low vegetation, high vegetation, roads, red roofs, and white roofs. And from the comparison with the manually defined ground truth, an overall accuracy degree of 80% was achieved. Furthermore, by applying various aggregation strategies, by combining the cultivated fields / low vegetation and high vegetation classes, we achieved a better overall accuracy of 91%

Techniques for Improving Color Segmentation in the Task of Identifying Objects on Aerial Images

Automatic identification of objects on aerospace images allows to increase the efficiency of making the necessary management decisions in important areas of human activity. A promising approach is the object-oriented image analysis, in which image segmentation is performed and the resulting image regions are classified into target object categories. The main problem constraining the effectiveness of this approach is the lack of segmentation accuracy. To solve this problem, the paper proposes techniques aimed at obtaining more relevant color seg- ments of the image: partition of the image into frames with sub- sequent merging of color areas lying on the borders of adjacent frames, splitting color regions in relatively narrow places, as well as adaptive approximation of the edges of color areas. An exper- imental study of improving the quality of identification of objects as a result of the application of the developed techniques is car- ried out. The experiments were conducted on high resolution aerial images from a publicly available dataset. It is shown that the proposed techniques make a significant contribution to im- proving the efficiency of the logical approach to the identification of objects based on shape features

OBJECT BASED “DAYAS” CLASSIFICATION USING SENTINEL A-2 SATELLITE IMAGERY CASE STUDY CITY OF BENSLIMANE

The management of “DAYAS” is a major issue in the preservation and maintain of biodiversity and environmental balance, especially in a context where this fragile ecosystems face many degradation factors. The extraction of Dayas is a key component in the management process of this type of wetlands, and has been the subject of many researches related to remote sensing. The methods and instrumentation for optical remote sensing are used to improve the mapping of Dayas, based on the radiometric characteristics of local hydrosystems. The present paper studies the inputs of different methods for the delimitation and extraction of Dayas in the realm of Benslimane city, using Sentinel A-2 imagery for the mapping. The methodology for the application of the pixel-based and the object-oriented approaches requires many steps, starting from an image pre-processing with Sentinel-2 calibration, the calculation of NDWI index, to proceed to the extraction of Dayas from the very high resolution image segmentation, then the application of the object-oriented classification to validate the results. The cartographic results demonstrate the input of the applied methodology in the Dayas extraction in different situations and timing (winter/summer), and allow to measure the cartographic accuracy for each approach, finding 65% of accuracy for the pixel-based approach with Kappa index = 0.40 versus 75% of accuracy for the object-oriented approach with Kappa index = 0.72. The results achieved inform and orient about optimisation measures and regulations of the Kappa index to improve the Dayas extraction and mapping

Sustainable Agriculture and Advances of Remote Sensing (Volume 1)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words