scholarly journals Mapping Large-Scale Plateau Forest in Sanjiangyuan Using High-Resolution Satellite Imagery and Few-Shot Learning

2022 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Zhihao Wei ◽  
Kebin Jia ◽  
Xiaowei Jia ◽  
Pengyu Liu ◽  
Ying Ma ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Ground Truth ◽  
Fine Tuning ◽  
Forest Monitoring ◽  
Learning Method ◽  
Ground Truth Data ◽  
Sensing Applications ◽  
High Resolution Satellite Imagery

Monitoring the extent of plateau forests has drawn much attention from governments given the fact that the plateau forests play a key role in global carbon circulation. Despite the recent advances in the remote-sensing applications of satellite imagery over large regions, accurate mapping of plateau forest remains challenging due to limited ground truth information and high uncertainties in their spatial distribution. In this paper, we aim to generate a better segmentation map for plateau forests using high-resolution satellite imagery with limited ground-truth data. We present the first 2 m spatial resolution large-scale plateau forest dataset of Sanjiangyuan National Nature Reserve, including 38,708 plateau forest imagery samples and 1187 handmade accurate plateau forest ground truth masks. We then propose an few-shot learning method for mapping plateau forests. The proposed method is conducted in two stages, including unsupervised feature extraction by leveraging domain knowledge, and model fine-tuning using limited ground truth data. The proposed few-shot learning method reached an F1-score of 84.23%, and outperformed the state-of-the-art object segmentation methods. The result proves the proposed few-shot learning model could help large-scale plateau forest monitoring. The dataset proposed in this paper will soon be available online for the public.

scholarly journals Penataan Batas Wilayah Administrasi Desa, Hambatan dan Alternatif Solusi dengan Pendekatan Geospasial

1969 ◽  
Vol 12 (2) ◽  
pp. 131-147
Author(s):  
Asadi Asadi
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
High Resolution Satellite Imagery ◽  
Main Instrument ◽  
Topographical Maps ◽  
Imagery Data

Law No. 6 of 2014 concerning Villages provides additional evidence that Indonesia has paid more attention and respect to the existence of villages. The significant amount of village expansion lately is not matched with the clarity of village boundaries that may rise in to potential conflicts. Ideally, the entire instruments to structure village boundaries must first be prepared. One of the instruments needed is the availability of large scale of basic maps (topographical maps) as the main instrument of making a village map. Unfortunately, the large-scale topographical maps are not available yet. This paper provides an alternative acceleration of village boundaries arrangement using High Resolution Satellite Imagery Data that has passed orthorectified process. By involving the community and village leaders in the process of structuring boundaries, and supported by the spirit of fraternity, all problems occured during the activity of village boundaries can be solved with the very best solution.Keywords: village boundary, High Resolution Satellite Imagery Data, spirit of fraternityUndang-Undang Nomor 6 Tahun 2014 tentang Desa memberikan tambahan bukti bahwa negara semakin memperhatikan dan menghormati keberadaan desa. Adanya pemekaran wilayah desa yang signifikan akhir-akhir ini, tidak diimbangi dengan kejelasan batas wilayah desa,berpotensi menimbulkan konflik. Idealnya, seluruh instrumen untuk melakukan penataan batas wilayah desa harus terlebih dahulu disiapkan. Salah satu instrumen tersebut adalah tersedianya peta dasar (peta rupabumi) skala besar sebagai bahan utama pembuatan peta desa. Sayangnya ketersediaan peta rupabumi skala besar belum tersedia. Tulisan ini memberikan alternatif percepatan penataan batas wilayah desa yang dapat menggunakan Citra Satelit Resolusi Tinggi (CSRT) yang sudah melalui proses ortorektifikasi. Dengan melibatkan masyarakat dan tokoh masyarakat desa dalam melakukan proses penataan batas wilayah, dan dengan didukung semangat persaudaraan, diharapkan permasalahan batas wilayah desa dapat diselesaikan dengan sebaik-baiknya.Kata kunci: batas desa, metode kartometrik, CSRT, semangat persaudaraan

scholarly journals Exploring the Potential of High-Resolution Satellite Imagery for the Detection of Soybean Sudden Death Syndrome

2020 ◽  
Vol 12 (7) ◽  
pp. 1213 ◽  
Author(s):  
Muhammad M. Raza ◽  
Chris Harding ◽  
Matt Liebman ◽  
Leonor F. Leandro
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Sudden Death ◽  
Satellite Imagery ◽  
Large Scale ◽  
Vegetation Index ◽  
Sudden Death Syndrome ◽  
Alternative Methods ◽  
High Resolution Satellite Imagery ◽  
Soybean Diseases

Sudden death syndrome (SDS) is one of the major yield-limiting soybean diseases in the Midwestern United States. Effective management for SDS requires accurate detection in soybean fields. Since traditional scouting methods are time-consuming, labor-intensive, and often destructive, alternative methods to monitor SDS in large soybean fields are needed. This study explores the potential of using high-resolution (3 m) PlanetScope satellite imagery for detection of SDS using the random forest classification algorithm. Image data from blue, green, red, and near-infrared (NIR) spectral bands, the calculated normalized difference vegetation index (NDVI), and crop rotation information were used to detect healthy and SDS-infected quadrats in a soybean field experiment with different rotation treatments, located in Boone County, Iowa. Datasets collected during the 2016, 2017, and 2018 soybean growing seasons were analyzed. The results indicate that spectral features, when combined with ground-based information, can detect areas in soybean plots that are at risk for disease, even before foliar symptoms develop. The classification of healthy and diseased soybean quadrats was >75% accurate and the area under the receiver operating characteristic curve (AUROC) was >70%. Our results indicate that high-resolution satellite imagery and random forest analyses have the potential to detect SDS in soybean fields, and that this approach may facilitate large-scale monitoring of SDS (and possibly other economically important soybean diseases). It may also be useful for guiding recommendations for site-specific management in current and future seasons.

scholarly journals Large-scale monitoring of coppice forest clearcuts by multitemporal very high resolution satellite imagery. A case study from central Italy

2011 ◽  
Vol 115 (4) ◽  
pp. 1025-1033 ◽  
Author(s):  
Gherardo Chirici ◽  
Diego Giuliarelli ◽  
Daniele Biscontini ◽  
Daniela Tonti ◽  
Walter Mattioli ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Central Italy ◽  
High Resolution Satellite Imagery ◽  
Coppice Forest ◽  
Very High

Automatic extraction of man-made objects from high-resolution satellite imagery by information fusion

2005 ◽  
Author(s):  
◽  
Xiaoying Jin
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Contextual Information ◽  
Automatic Extraction ◽  
Building Extraction ◽  
Geospatial Information ◽  
University Of Missouri ◽  
Sensing Applications ◽  
High Resolution Satellite Imagery ◽  
The University

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Recently available high-resolution commercial satellite imagery provides an important new data source for remote sensing applications. Automated feature extraction (AFE) techniques can assist human analysts by rapidly locating geospatial information and have the potential to significantly reduce the amount of time to process and analyze geospatial data. In this research, we have designed and developed systems for automatic extraction of man-made objects (roads, buildings and vehicles) from high-resolution satellite imagery. We conclude that AFE can be greatly enriched and improved by multiinformation fusion and/or multi-cue integration. For road extraction and building extraction respectively, multiple detectors were developed and the extraction performance was greatly improved using multi-detector fusion from different information sources. For vehicle detection, a GIS road vector layer was used to incorporate contextual information and an implicit vehicle model including spectral and spatial characteristics was learned by a morphological shared-weight neural network. An important characteristic of our research on road and building extraction is that our extraction strategies are fully automated with only a few preset parameters. Compared with related research in these areas, the performance evaluations of our extraction systems are among the highest statistical values reported in literature thus far.

scholarly journals COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

2015 ◽  
Vol XL-3/W2 ◽  
pp. 1-7 ◽  
Author(s):  
P. Agrafiotis ◽  
A. Georgopoulos
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Best Practice ◽  
Single Point ◽  
Critical Approach ◽  
Qualitative Properties ◽  
Check Points ◽  
High Resolution Satellite Imagery

This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO) provided by NCMA S.A (Hellenic Cadastre) from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD) from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO) were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

VERY HIGH RESOLUTION SATELLITE IMAGERY UTILIZATION STANDARD FOR LARGE SCALE TOPOGRAPHIC MAPPING

2021 ◽  
pp. 939
Author(s):  
Winhard Tampubolon ◽  
Wolfgang Reinhardt ◽  
Franz Josef Behr
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Local Coordinate System ◽  
Control Point ◽  
Least Square ◽  
Topographic Mapping ◽  
Geometric Correction ◽  
High Resolution Satellite Imagery ◽  
Very High

Due to its large area Large Scale Topographic Mapping (LSTM) for Indonesia requires acceleration strategies that must be innovative enough to take into account the production efficiency. Satellite-based technologies are still a preferable choice especially in conjunction with the security clearance and weather. Standards for the Very High-Resolution Satellite Imagery (VHRS) utilization are essential, especially in a situation where there are so many available sensors and processing methods implemented. Hence, the selection of a proper geometric correction method is fundamental in order to utilize the VHRS imagery as one source of geospatial data especially for LSTM production and updating purposes. For CSRT geometric correction, an orthorectification process is required, where this process requires input data from the Ground Control Point (TKT) and the Digital Elevation Model (DEM). Therefore, the Least Square Adjustment (LSA) method is implemented to be able to include 8-9 GCPs per-scene (orbital and sensor parameters) and the DEM with a maximum resolution 4 times of the VHRS imagery’s Ground Sampling Distance (GSD) in the process of producing VHRS orthoimages. In addition, the role of orbital and sensor parameters is also essential for the geometric correction because its relation to the Direct Georeferencing (DG) of each pixel by Rigorous Sensor Model (RSM) approach. However, in the situation where the reliable orbital and sensor parameters are not available, the Rational Function Model (RFM) can be used as an alternative solution for the geometric correction of VHRS imagery. This paper discusses the VHRS utilization with a comprehensive approach that can be implemented in a local coordinate system i.e. the Indonesian Geospatial Reference System for the production of the reliable VHRS imageries.

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