An integrated approach to surveying an Early Agricultural period landscape: Magnetic gradiometry and satellite imagery at La Playa, Sonora, Mexico

2017 ◽  
Vol 15 ◽  
pp. 381-392 ◽  
Author(s):  
Rachel Cajigas
Author(s):  
M. Kumar ◽  
R. K. Singh ◽  
P. L. N. Raju ◽  
Y. V. N. Krishnamurthy

High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resolution space imagery. The proposed approach begins with segmentation of the scene with Multi-resolution Object Oriented segmentation. This step focuses on exploiting both spatial and spectral information for the target feature extraction. The road regions are automatically identified using a soft fuzzy classifier based on a set of predefined membership functions. A number of shape descriptors are computed to reduce the misclassifications between road and other spectrally similar objects. The detected road segments are further refined using morphological operations to form final road network, which is then evaluated for its completeness, correctness and quality. The experiments were carried out of fused IKONOS 2 , Quick bird ,Worldview 2 Products with fused resolution’s ranging from 0.5m to 1 m. Results indicate that the proposed methodology is effective in extracting accurate road networks from high resolution imagery.


2020 ◽  
Author(s):  
Cristian Moise ◽  
Cristina Elena Mihalache ◽  
Luminita Andreea Dedulescu ◽  
Andi-Mihai Lazăr ◽  
Alexandru Badea ◽  
...  

<p>Remote sensing has already proven to represent an invaluable resource for monitoring the cultural heritage objectives by using non-invasive methods, thus enhancing the capabilities of safeguarding cultural heritage sites. Multiple types of data provide a better insight for the cultural heritage monitoring. Increasing human industrial activities in the vicinity of the Corvin Castle puts a question mark on the long-term conservation of the historic monument. Satellite imagery provides a large amount of data regarding the castle itself and its surrounding areas, enabling authorities and decision makers to assess the natural or anthropic hazards and mitigate potential damages. Freely available high-resolution satellite imagery that spans from mid 1970s until the present day enables an unprecedented opportunity for the creation of multi-sensor, multi-temporal and cross analysis.</p><p>In the field of cultural heritage and archaeological research, Light Detection and Ranging (LiDAR) is a significant technology that provides comprehensive data. LiDAR sensors acquire high-precision 3D information (point cloud) of the land surfaces and buildings.</p><p>Knowledge of structures stability is essential in early recognition of potential risks and enables preventive diagnosis of heritage sites. Vertical displacements in wide or remote areas can be identified using Persistent Scatterer Interferometry (PS-InSAR) technique. Measuring millimetric displacements using multi-temporal series of data acquired by spaceborne active sensors is less time consuming compared with in-situ measurements. The two-satellite constellation Sentinel-1 mission offers a 6-day exact repeat cycle at the equator, thus providing fast and high accuracy results for emergency situations and hazards monitoring, suitable for PS-InSAR processing. Monitoring the structure stability of this historical monument is of great importance.</p><p>The Corvin Castle, also known as Hunyadi Castle or Hunedoara Castle, is the most spectacular Gothic-style construction in Transylvania, Romania. Today, the castle is a rare historical and architectural example. Built in the mid-15th century, the Corvin Castle is split into three large areas: The Knight’s Hall, the Diet Hall, and the circular stairways. Each of these three parts is surrounded by both circular and rectangular towers that were used for both defense and as a prison.</p><p>This paper presents the ongoing activities of bringing together various geospatial technologies and data sources in order to set-up an integrated approach for site monitoring and risk assessment related to the Corvin Castle and other similar cultural heritage objectives. The outcomes will provide significant contributions for implementing suitable protection and preservation measures.</p>


2006 ◽  
Vol 43 ◽  
pp. 385-389 ◽  
Author(s):  
Qinghua Ye ◽  
Tandong Yao ◽  
Shichang Kang ◽  
Feng Chen ◽  
Jinghua Wang

AbstractThis work quantifies glacier variations in the Naimona’nyi area of the western Himalaya by integrating glacier spatial data from ASTER and the Landsat series of satellite imagery at four different times: 1976, 1990, 1999 and 2003. Comparison of the results from individual images with those from the integrated method indicates that the integrated approach provides a better result. Glacier variations were mapped and analyzed; discrepancies between images could be detected and removed from the integrated data using remap tables in Arc/Info grid both graphically and numerically. Our results show that glaciers in the region both retreated and advanced during the last 28 years; however, retreat dominates. The variation of glaciers in the western Himalayan region is dramatic compared with other regions in high Asia. From 1976 to 2003, glacier area decreased from 84.41 km2 to 77.29 km2. Sequential images show that glacier areas shrank by 0.17, 0.19 and 0.77 km2 a−1, on average, during the periods 1976–90, 1990–99 and 1999–2003, respectively, suggesting that glacier retreat has accelerated.


Author(s):  
Q. A. Adejare ◽  
S. A. Azeez ◽  
Q. J. Aderibigbe ◽  
M .B. Adewara

Dams are reservoirs established for different reasons. Oyan dam, Ogun State, Nigeria was established and commissioned on the 29th March 1983 to supply water to Lagos State and Abeokuta for municipal uses, with power generation potentials to support Lower Ogun Irrigation Project. However, flooding has become an annual experience of downstream communities along Ogun river especially when the Oyan dam is opened; it has really becomes remarkable since the flood events of 2012. This project investigates the level of siltation and floods menace adjoining Oyan dam and its environ. An integrated methodology of bathymetric survey, total station traversing and satellite imagery were used to acquire geospatial locations of the dam features and other details within the dam through the process of traversing, heightening and detailing. The field investigation was conducted between January 2018 and January 2020 to determine dam bed topography with the deployment of integrated approach. The collected data were processed using Hydrologic Engineering Center’s River Analysis System (HEC-RAS), HYPACK software and ArcGIS 10.6 software. The maximum and minimum depth within the dam are -4.072m and -21.588m respectively. The cross sections are represented for each 200m length of the dam. Furthermore, volumetric analysis of sediment budget was computed to be 251.7x106m3 and compared with designed reservoir capacity of 270x106m3. From the study, a loss of about 18.2x106m3 approximately 6.7% was recorded. Satellite imagery shows the rate of change within Oyan dam and its catchment area downstream based on Triangulated Irregular Network (TIN) generated from Shuttle Radar Topography Mission (SRTM) the maximum and minimum elevation in the catchment are 29m and 182m respectively. The study recommends that deepen and training of Ogun river and all adjoining drainages system within the study corridor to retain more water when peak rainfall is recorded.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luciana Nieto ◽  
Raí Schwalbert ◽  
P. V. Vara Prasad ◽  
Bradley J. S. C. Olson ◽  
Ignacio A. Ciampitti

AbstractEfficient, more accurate reporting of maize (Zea mays L.) phenology, crop condition, and progress is crucial for agronomists and policy makers. Integration of satellite imagery with machine learning models has shown great potential to improve crop classification and facilitate in-season phenological reports. However, crop phenology classification precision must be substantially improved to transform data into actionable management decisions for farmers and agronomists. An integrated approach utilizing ground truth field data for maize crop phenology (2013–2018 seasons), satellite imagery (Landsat 8), and weather data was explored with the following objectives: (i) model training and validation—identify the best combination of spectral bands, vegetation indices (VIs), weather parameters, geolocation, and ground truth data, resulting in a model with the highest accuracy across years at each season segment (step one) and (ii) model testing—post-selection model performance evaluation for each phenology class with unseen data (hold-out cross-validation) (step two). The best model performance for classifying maize phenology was documented when VIs (NDVI, EVI, GCVI, NDWI, GVMI) and vapor pressure deficit (VPD) were used as input variables. This study supports the integration of field ground truth, satellite imagery, and weather data to classify maize crop phenology, thereby facilitating foundational decision making and agricultural interventions for the different members of the agricultural chain.


2007 ◽  
Vol 6 (1) ◽  
pp. 185-186
Author(s):  
E COSENTINO ◽  
E RINALDI ◽  
D DEGLIESPOSTI ◽  
S BACCHELLI ◽  
D DESANCTIS ◽  
...  

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