Browsing by Author "Shao, Zhenfeng"

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Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery
(2017-03-26) Shao, Zhenfeng; Deng, Juan; Wang, Lei; Fan, Yewen; Sumari, Neema S.; Cheng, Qimin
Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM) to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate) on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM) is 21.8 and Random Forest (RF) is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.
A Fuzzy Logic-Based Approach for Modelling Uncertainty in Open Geospatial Data on Landfill Suitability Analysis
(International Journal of Geo-Information, 2020-12-09) Lyimo, Neema Nicodemus; Shao, Zhenfeng; Ally, Ally Mgelwa; Twumasi, Nana Yaw Danquah; Altan, Orhan; Sanga, Camilius A
Besides OpenStreetMap (OSM), there are other local sources, such as open government data (OGD), that have the potential to enrich the modeling process with decision criteria that uniquely reflect some local patterns. However, both data are affected by uncertainty issues, which limits their usability. This work addresses the imprecisions on suitability layers generated from such data. The proposed method is founded on fuzzy logic theories. The model integrates OGD, OSM data and remote sensing products and generate reliable landfill suitability results. A comparison analysis demonstrates that the proposed method generates more accurate, representative and reliable suitability results than traditional methods. Furthermore, the method has facilitated the introduction of open government data for suitability studies, whose fusion improved estimations of population distribution and land-use mapping than solely relying on free remotely sensed images. The proposed method is applicable for preparing decision maps from open datasets that have undergone similar generalization procedures as the source of their uncertainty. The study provides evidence for the applicability of OGD and other related open data initiatives (ODIs) for land-use suitability studies, especially in developing countries.
Geospatial Distribution and Accessibility of Primary and Secondary Schools: A case of Abbottabad City, Pakistan
(Proceedings of the International Cartographic Association, 2019-07-27) Sumari, Neema S.; Tanveer, Hashir; Shao, Zhenfeng; Kira, Ernest Simon
Quality education in isolated areas is a major issue in developing countries like Pakistan, as access to formal education is linked to improved life prospects for rural students. Among the factors for education, accessibility is school availability within a minimum spatial distance. The spatial distribution of schools is generally uneven in most of the cities of Northern Pakistan, thus limiting access to formal education at the primary and secondary level. This paper analyzes the spatial distribution of the primary and secondary schools found in the hilly terrain of Abbottabad city. Results show an uneven scattered pattern of schools and decreasing accessibility with longer travel times, at higher costs. Cost-weighted distance showed that this spatial distribution extends the travel distance by more than 5km for secondary school students living in the city. However, spatial restructuring and reorganization of schools in the study area would enhance student access to school facilities.
Status of geoinformatics education and training in Sub-Saharan Africa: initiatives taken and challenges
(2019-03-11) Sumari, Neema S.; Shao, Zhenfeng; Van Genderen, John L.; Musakwa, Walter; Ujoh, Fanan; Washaya, Prosper; Gumbo, Trynos
This paper presents an update on some of the activities that have taken place since aWorld Bank report; “Guidelines for Education and Training in Environmental Information Systems in Sub-Saharan Africa: Some Key Issues” was published and provides details on the current situation. It shows how organizations such as the African Association on Remote Sensing of Environment, International Society of Photogrammetry and Remote Sensing, European Association of Remote Sensing Companies, Group on Earth Observation, and several others have helped to increase manpower resources in the region and strengthened institutional capacity in the field of geoinformatics, through capacity building, technology transfer, international cooperation and the provision of internal African resources. After reviewing what has happened in the field of geoinformatics education and training, we focused on current initiatives taken and challenges in five Sub-Saharan countries: Ethiopia, Nigeria, South Africa, Tanzania, and Zimbabwe. We reviewed GIS education and training in the private sector, government, information communications technology in higher education institutions, GIS application areas and challenges facing GIS education and training. Findings show that; change should involve education stakeholders in all levels of education and curriculum quality, regional and international cooperation through exchange programs, should be a priority for Sub-Saharan Africa countries.
Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data
(Geo-spatial Information Science, 2020-07-28) Shao, Zhenfeng; Sumari, Neema S.; Portnov, Aleksei; Ujoh, Fanan; Musakwa, Walter; Mandela, Paulo J.
Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals (SDGs). Urban sprawl has resulted in unsustainable urban development patterns from social, environmental, and economic perspectives. This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality, Tanzania. Random Forest (RF) method was applied to accomplish imagery classification and location-based social media (Twitter usage) data were obtained through a Twitter Application Programming Interface (API). Morogoro urban municipality was classified into built-up, vegetation, agriculture, and water land cover classes while the classification results were validated by the generation of 480 random points. Using the Kernel function, the study measured the location of Twitter users within a 1 km buffer from the center of the city. The results indicate that, expansion of the city (built-up land use), which is primarily driven by population expansion, has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover. In addition, social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area. The outcome of the study suggests that the combination of remote sensing, social sensing, and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro, and Africa city where data for urban planning is often unavailable, inaccurate, or stale.