Estimation of holm oak flowering intensity in dehesa farms using high-resolution aerial images

2021 ◽  
Author(s):  
Pedro Gómez-Giraldez ◽  
María Dolores Carbonero ◽  
Elisabet Carpintero ◽  
María Pat González-Dugo
Keyword(s):  
High Resolution ◽  
Holm Oak ◽  
Aerial Images ◽  
Flowering Intensity

Mapping of landscape-morphological structure of the Northern-Western part of Anapa bay bar by digital high resolution aerial images

2017 ◽  
Vol 927 (9) ◽  
pp. 22-29
Author(s):  
V.I. Kravtsovа ◽  
E.R. Chalova
Keyword(s):  
High Resolution ◽  
Morphological Structure ◽  
Middle Part ◽  
Aerial Images ◽  
Medical Resource ◽  
Sea Waves ◽  
Coast Line ◽  
Waves Interaction ◽  
Account Due ◽  
Digital Landscape

Anapa bay bar is a valuable recreational-medical resource. Digital landscape-morphological mapping of its the Northern-Western part was created by digital aero survey materials for monitoring of its statement. Compiled maps show that in the Western part of region dune belt is degradated, front dune hills destroyed due to spreading of settlement Veselovka buildings to beach, and due to mass enactments carrying out at bay bar of lake Solenoe. Here it is necessary to decide the problem of defense from waves flooding by construction of artificial hills. The middle part of region, around Bugaz lagoon, is using for unregulated recreation of extreme sportsmen – windsurfing and kiting – with seasonal recreation in camping from tent-city and campers. Many short roads to sea beach, orthogonal to coast line, have been transformed to corridors of blowing and sea waves interaction to lagoon lowland with dune belt destroying. In the Eastern part of region, at Bugaz bay bar, dune belt is conserve, it changes under natural sea and wind processes action. At some places sea waves are erode windward front dune slope. Just everywhere sand accumulative trains are forming at leeward slope of front dune. Showed peculiarities of landscape morphological structure mast be taken in account due treatment of measures for bay bar defense and keeping.

scholarly journals Dynamics of Erosion and Deposition in a Partially Restored Valley-Bottom Gully

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 62
Author(s):  
Alberto Alfonso-Torreño ◽  
Álvaro Gómez-Gutiérrez ◽  
Susanne Schnabel
Keyword(s):  
High Resolution ◽  
Sediment Deposition ◽  
Aerial Images ◽  
Valley Bottom ◽  
Erosion And Deposition ◽  
Channel Dynamics ◽  
Check Dams ◽  
Before And After ◽  
Multi Temporal ◽  
Spatio Temporal

Gullies are sources and reservoirs of sediments and perform as efficient transfers of runoff and sediments. In recent years, several techniques and technologies emerged to facilitate monitoring of gully dynamics at unprecedented spatial and temporal resolutions. Here we present a detailed study of a valley-bottom gully in a Mediterranean rangeland with a savannah-like vegetation cover that was partially restored in 2017. Restoration activities included check dams (gabion weirs and fascines) and livestock exclosure by fencing. The specific objectives of this work were: (1) to analyze the effectiveness of the restoration activities, (2) to study erosion and deposition dynamics before and after the restoration activities using high-resolution digital elevation models (DEMs), (3) to examine the role of micro-morphology on the observed topographic changes, and (4) to compare the current and recent channel dynamics with previous studies conducted in the same study area through different methods and spatio-temporal scales, quantifying medium-term changes. Topographic changes were estimated using multi-temporal, high-resolution DEMs produced using structure-from-motion (SfM) photogrammetry and aerial images acquired by a fixed-wing unmanned aerial vehicle (UAV). The performance of the restoration activities was satisfactory to control gully erosion. Check dams were effective favoring sediment deposition and reducing lateral bank erosion. Livestock exclosure promoted the stabilization of bank headcuts. The implemented restoration measures increased notably sediment deposition.

scholarly journals Multiscale Semantic Feature Optimization and Fusion Network for Building Extraction Using High-Resolution Aerial Images and LiDAR Data

2021 ◽  
Vol 13 (13) ◽  
pp. 2473
Author(s):  
Qinglie Yuan ◽  
Helmi Zulhaidi Mohd Shafri ◽  
Aidi Hizami Alias ◽  
Shaiful Jahari Hashim
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Spatial Information ◽  
Feature Fusion ◽  
Aerial Images ◽  
Semantic Gap ◽  
Superior Performance ◽  
Lidar Data ◽  
Building Extraction ◽  
Hierarchical Features

Automatic building extraction has been applied in many domains. It is also a challenging problem because of the complex scenes and multiscale. Deep learning algorithms, especially fully convolutional neural networks (FCNs), have shown robust feature extraction ability than traditional remote sensing data processing methods. However, hierarchical features from encoders with a fixed receptive field perform weak ability to obtain global semantic information. Local features in multiscale subregions cannot construct contextual interdependence and correlation, especially for large-scale building areas, which probably causes fragmentary extraction results due to intra-class feature variability. In addition, low-level features have accurate and fine-grained spatial information for tiny building structures but lack refinement and selection, and the semantic gap of across-level features is not conducive to feature fusion. To address the above problems, this paper proposes an FCN framework based on the residual network and provides the training pattern for multi-modal data combining the advantage of high-resolution aerial images and LiDAR data for building extraction. Two novel modules have been proposed for the optimization and integration of multiscale and across-level features. In particular, a multiscale context optimization module is designed to adaptively generate the feature representations for different subregions and effectively aggregate global context. A semantic guided spatial attention mechanism is introduced to refine shallow features and alleviate the semantic gap. Finally, hierarchical features are fused via the feature pyramid network. Compared with other state-of-the-art methods, experimental results demonstrate superior performance with 93.19 IoU, 97.56 OA on WHU datasets and 94.72 IoU, 97.84 OA on the Boston dataset, which shows that the proposed network can improve accuracy and achieve better performance for building extraction.

Robust Vehicle Detection in High-Resolution Aerial Images with Imbalanced Data

2021 ◽  
pp. 1-1
Author(s):  
Xianghui Li ◽  
Xinde Li ◽  
Zhijun Li ◽  
Xinran Xiong ◽  
Mohammad Omar Khyam ◽  
...  
Keyword(s):  
High Resolution ◽  
Imbalanced Data ◽  
Vehicle Detection ◽  
Aerial Images

Detection of Damaged Rooftop Areas From High-Resolution Aerial Images Based on Visual Bag-of-Words Model

2016 ◽  
Vol 13 (12) ◽  
pp. 1817-1821 ◽  
Author(s):  
Jihui Tu ◽  
Haigang Sui ◽  
Wenqing Feng ◽  
Kaimin Sun ◽  
Li Hua
Keyword(s):  
High Resolution ◽  
Aerial Images ◽  
Bag Of Words

Analysis Of High Resolution Aerial Images For Object Detection

1989 ◽  
Author(s):  
Mohan M. Trivedi ◽  
Amol G. Bokil ◽  
Mourad B. Takla ◽  
George B. Maksymonko ◽  
J. Thomas Broach
Keyword(s):  
High Resolution ◽  
Object Detection ◽  
Aerial Images

Spatial changes of forests in a coastal and a remote mountainous area of Greece over a 65-year period

2020 ◽  
Vol 11 (4) ◽  
pp. 93-109
Author(s):  
Stavros KOLIOS ◽  
◽  
George NTOGAS ◽  
Efthimios ZERVAS ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Arable Land ◽  
Aerial Images ◽  
Mountainous Area ◽  
Land Use Land Cover ◽  
Spatial Homogeneity ◽  
Spatial Changes ◽  
Forested Areas ◽  
Of Greece

The scope of the study is to detect spatial changes in the forested areas over six decades (1945 - 2010) of two completely different landscapes in Greece (pilot areas). The first pilot area is Kastoria which is a relatively remote and mountainous area located northwestern on the Greek peninsula, while the second one is Propontida which is a coastal area in the Chalkidiki peninsula (central Macedonia, Greece). High resolution orthorectified aerial images are used to detect the general types (classes) of land use/land cover (LULC) in these pilot areas. The results reveal that during the examined period, a notable spatial growth and thickening of the forest areas was found (10,51%) in the pilot area of Kastoria. The spatial homogeneity of the forested areas in Kastoria decreased only by 2,11%. Regarding Propontida, the forested areas decreased in total about 13,02% while the agricultural and arable land has increased by 12,10%.

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