scholarly journals Comparison of methods of Humidity Index processing in the Irrigated Perimeter Nilo Coelho, Northeast of Brazil

2018 ◽  
Vol 7 (6) ◽  
pp. 315
Author(s):  
Antonio Celso de Sousa Leite ◽  
Leidjane Maria Maciel De Oliveira ◽  
Ulisses Alencar Bezerra ◽  
Débora Natália O. de Almeida Oliveira De Almeida ◽  
Ana Lucia B. Candeias ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Image ◽  
Comparison Of Methods ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Humidity Index ◽  
Irrigated Perimeter ◽  
Remote Sensing Techniques ◽  
Object Of Study ◽  
Remote Sensing Image Processing

The use of remote sensing techniques in support of hydrological studies became common in recent years, through the application of orbital images that are used the reflectance values of the water, for mapping, delineation of water bodies and moisture monitoring in the internal structure of vegetable biomass. Among the methods and techniques of remote sensing image processing with the hydrological analysis, here the Normalized Difference Water Index (NDWI), object of study in the present work, in order to compare the application of the index through different methods. The present study was developed in the territorial part of the Nilo Coelho Irrigated Perimeter located in the Semiarid Northeastern region and covers the municipalities of Casa Nova-BA, Petrolina-PE and Juazeiro-BA, using TM-Landsat 5 sensor images from 30/07/2006. This comparison of the NDWI provided the best application for each index, as well as evaluate the potentiality of the index according to the applied method. 

scholarly journals COMPARISON OF VEGETATION INDICES FROM RPAS AND SENTINEL-2 IMAGERY FOR DETECTING PERMANENT PASTURES

2018 ◽  
Vol XLII-3 ◽  
pp. 1381-1387 ◽  
Author(s):  
M. Piragnolo ◽  
G. Lusiani ◽  
F. Pirotti
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Vegetation Indices ◽  
Monitoring And Control ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Remote Sensing Techniques ◽  
Sentinel 2

Permanent pastures (PP) are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016). Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA) takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI), the Soil-adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Built Index (NDBI). The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

scholarly journals MAPPING AND MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY

2017 ◽  
Vol IV-4/W4 ◽  
pp. 271-277 ◽  
Author(s):  
G. Kaplan ◽  
U. Avdan
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kappa Coefficient ◽  
Water Index ◽  
Object Based ◽  
The World ◽  
Normalized Difference Water Index ◽  
Remote Sensing Techniques ◽  
Sentinel 2

Mapping and monitoring of wetlands as one of the world`s most valuable natural resource has gained importance with the developed of the remote sensing techniques. This paper presents the capabilities of Sentinel-2 successfully launched in June 2015 for mapping and monitoring wetlands. For this purpose, three different approaches were used, pixel-based, object-based and index-based classification. Additional, for more successful extraction of wetlands, a combination of object-based and index-based method was proposed. It was proposed the use of object-based classification for extraction of the wetlands boundaries and the use of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for classifying the contents within the wetlands boundaries. As a study area in this paper Sakarbasi spring in Eskisehir, Turkey was chosen. The results showed successful mapping and monitoring of wetlands with kappa coefficient of 0.95.

scholarly journals Remote Sensing Image Dataset Expansion Based on Generative Adversarial Networks with Modified Shuffle Attention

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4867
Author(s):  
Lu Chen ◽  
Hongjun Wang ◽  
Xianghao Meng
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Image Processing ◽  
Remote Sensing Image ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Evaluation Indexes ◽  
Adversarial Network ◽  
Remote Sensing Image Processing ◽  
Data Expansion

With the development of science and technology, neural networks, as an effective tool in image processing, play an important role in gradual remote-sensing image-processing. However, the training of neural networks requires a large sample database. Therefore, expanding datasets with limited samples has gradually become a research hotspot. The emergence of the generative adversarial network (GAN) provides new ideas for data expansion. Traditional GANs either require a large number of input data, or lack detail in the pictures generated. In this paper, we modify a shuffle attention network and introduce it into GAN to generate higher quality pictures with limited inputs. In addition, we improved the existing resize method and proposed an equal stretch resize method to solve the problem of image distortion caused by different input sizes. In the experiment, we also embed the newly proposed coordinate attention (CA) module into the backbone network as a control test. Qualitative indexes and six quantitative evaluation indexes were used to evaluate the experimental results, which show that, compared with other GANs used for picture generation, the modified Shuffle Attention GAN proposed in this paper can generate more refined and high-quality diversified aircraft pictures with more detailed features of the object under limited datasets.

A dynamic acceleration method for remote sensing image processing based on CUDA

2021 ◽  
Author(s):  
Xianyu Zuo ◽  
Zhe Zhang ◽  
Baojun Qiao ◽  
Junfeng Tian ◽  
Liming Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Remote Sensing Image ◽  
Acceleration Method ◽  
Remote Sensing Image Processing
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