Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"Land cover mapping"”.
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Learning with Weak Supervision for Land Cover Mapping Problems
Land cover mapping is the task of generating maps of land use globally across time. The recent decades have seen an increasing availability of public satellite data sets with observations of the Earth at regular intervals of space and time. This coupled with the advances in machine learning and …
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Deep learning convolutional neural networks for Landsat-derived land cover mapping
… into categorical classes as required to produce land cover maps from satellite imagery. A major advance in the accuracy of convolutional neural networks (CNNs) for computer vision image classification occurred in 2012, supported by advances in processing such as GPUs. This was subsequently …
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Deep learning convolutional neural networks for Landsat-derived land cover mapping
… into categorical classes as required to produce land cover maps from satellite imagery. A major advance in the accuracy of convolutional neural networks (CNNs) for computer vision image classification occurred in 2012, supported by advances in processing such as GPUs. This was subsequently …
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Land cover mapping through optimizing remote sensing data for SVM classification
Support Vector Machines (SVMs) are a new supervised classification technique that has its roots in statistical learning theory. It has gained popularity in fields such as machine vision, artificial intelligence, digital image processing and more recently remote sensing. The three commonly used SVMs …
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Urban land cover mapping using medium spatial resolution satellite imageries: effectiveness of Decision Tree Classifier
… from satellite imageries for supporting rapid mapping activities, where information need to be extracted quickly and the elimination, also if partially, of manual digitalization procedures, can be considered a great breakthrough. The main aim of this study was therefore to develop algorithms …
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Satellite image classification and spatial analysis of agricultural areas for land cover mapping of grizzly bear habitat
… multiple classes of agricultural and herbaceous land cover for the purpose of grizzly bear habitat mapping, and to determine what, if any, spatial and compositional components of the landscape affected the bears in these agricultural areas. Spectral and environmental data for five different …
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Representing complex multisector, human systems into land use and land cover mapping to inform sustainability and future societal development.
… the human population, it directly impacts the land with large-scale deforestation and habitat fragmentation. Human-earth interactions such as these are studied in the field of Multi-Sector Dynamics (MSD). MSD divides the earth’s natural systems into sectors and records their connection …
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A contextual classification approach for forest land cover mapping using high spatial resolution multispectral satellite imagery – a case study in Lake Tahoe, California
Maps of classified surface features are a key output from remote sensing. Conventional methods of pixel-based classification label each pixel independently by considering only a pixel’s spectral properties. While these purely spectral-based techniques may be applicable to many medium and …
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Spatial Analysis of La Nana Bayou Watershed to Assess Stream Health
… study was to evaluate the feasibility of using land cover mapping to identify water quality indicators within a river basin, assessing whether this method provides greater efficiency compared to traditional field-based water quality testing. Land cover mapping has efficiently monitored …
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Analisis orientado a objetos de imágenes de teledetección para cartografia forestal : bases conceptuales y un metodo de segmentacion para obtener una particion inicial para la clasificacion = Object-oriented analysis of remote sensing images for land cover mapping : Conceptual foundations and a segmentation method to derive a baseline partition for classification
El enfoque comúnmente usado para analizar las imágenes de satélite con fines cartográficos da lugar a resultados insatisfactorios debido principalmente a que únicamente utiliza los patrones espectrales de los píxeles, ignorando casi por completo la estructura espacial de la imagen. Además, la …
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Robust Deep Learning Methodologies for Weakly Supervised Remote Sensing Image Classification
… RS with a focus on classification tasks such as land-cover mapping and scene classification. WSL strategies are commonly subdivided into three different categories: i) inaccurate supervision, which deals with label noise; ii) inexact supervision, which deals with coarse-grained supervision (e.g., …
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Remote sensing applications in vegetation mapping with special reference to the Langebaan area, South Africa
… procedure used during the process of vegetation mapping has developed from a purely visual process of image identification to one which can utilize computerised methods to aid consistent identification of vast quantities of digitally stored/recorded spectral information. A description of the …
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A Medium Resolution Land Cover Map of Africa
<p>Land cover datasets are important for environmental monitoring and research purposes, and can influence policy regarding natural resource allocation and exploitation. For continental scale mapping, datasets with continuous spatial coverage, a spatial resolution good enough to represent the land …
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Cybergis-enabled remote sensing data analytics for deep learning of landscape patterns and dynamics
Mapping landscape patterns and dynamics is essential to various scientific domains and many practical applications. The availability of large-scale and high-resolution light detection and ranging (LiDAR) remote sensing data provides tremendous opportunities to unveil complex landscape patterns and …
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Impacts of Land Cover Changes on Ecosystem Services Delivery in the Black Hills Ecoregion from 1950 to 2010
<p>Environmental degradation generated by land use choices and human activities is the first driver of change in the provision of ecosystem goods and services. One of the challenges in ecosystem services research is to evaluate the contribution of each land cover unit to ecosystem services delivery …
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Remote Sensing Applications to Support Sustainable Natural Resource Management
… produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems …
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Remote Sensing Applications to Support Sustainable Natural Resource Management
… produce one single, dynamic, classification and mapping system for existing vegetation that could rely on commonly available inventory and remote sensing data. This classification and mapping system was intended to provide the analytical basis for resource planning and management. The problems …
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Automated Building Extraction from Remote Sensing Imagery Using Deep Learning
… aerial images is crucial for supporting various land use and land cover mapping applications. The conventional building polygon extraction process requires hand-crafted features and high human intervention, which is time-consuming and often has limited generalization capability. In recent years, …
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