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A multispectral imaging system is presented, using components that will support its deployment within the world of small-holder agriculture. An active narrowband illumination setup was selected, which allowed a low-cost broadband image sensor to be used. The preliminary set-up has been demonstrated with droughted tomato plants as a proof of concept. The results demonstrated a 5, 28 and 90% deterioration...
Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as NDVI and NDWI, are defined based on the sensitivity and significance of specific bands. Nowadays, remote sensing capability with a good number of bands and high spatial resolution is available. Instead of classification based on indices, this paper explores direct classification...
In order to evaluate the recovery effect of the visible light band in the low-altitude remote sensing, the sensitivity and significance of the visual perception of the restored image are selected and optimized by the perceptual characteristics of the human visual system. Finally, the effective detail retention ability, Structure information, multi - scale similarity and visual fidelity. A kind of...
Soil moisture is an important indicator that defines the land surface-atmosphere interactions by contributing precisely to the surface energy and water balance. In this study, we examine the utility of the Neural Network (NN) model using Discrete Wavelet Transform (DWT) as preprocessing mechanism for soil moisture estimation. The decomposed wavelet sub-time series data was used as input to the 3-layered...
Temperature vegetation dryness index (TVDI) is widely used for its physical significance. In this study, using the historical MODIS data, we consider Henan Province, a large grain province in Central China, an example for constructing feature space and calculating TVDI. Multi- and single-group image approaches are then compared, and the applicability of the TVDI in Henan Province is analyzed through...
One important feature of geography phenomenon or spatial object is that there exists the spatial autocorrelation between them. As for a spatial sampling scheme for crop acreage estimation, the spatial autocorrelation of the sampling units has an important effect on the design of the sampling scheme and the improvement of the sampling efficiency. While the related researches on spatial autocorrelation...
Early information on crops spatial extent is useful from food security standpoint. Growing number of remote sensing satellites are making it easier to map the crop areas in a rapid and cost-effective way. Grape being an commercial fruit crop of India, it is useful to map the grape areas for acreage estimation and monitor its health continuously to get optimum yield. The main contribution of this paper...
Two GF-1 WFV images on August 3, 2015 and October 2, 2015 were selected to extract the cultivated area of paddy rice in Jianhu county of Jiangsu Province. Vegetation indexes were extracted from the original spectrum data in order to extract paddy rice area with Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Classification and Regression Trees (CART). The extraction accuracy...
Agricultural landscape is designated as important landscape components for partly controlling water quality, biodiversity, as well as for their aesthetic role in landscapes. Therefore, the change of agricultural landscape is at the top of the agenda for many policy makers and landscape planners. As a basis for conservation management, sufficient information about landscape structure should be providing...
Agricultural drought greatly impacts the crop yield. Monitoring agricultural drought can deliver critical information to farmers on when, where and how much to irrigate. However, precisely monitoring which requires many kinds of data sources and data fusion and mining is still a huge challenge for scientists. In recent years, many data sources like remote sensed hyperspectral images are released online...
Most previous studies applied land surface temperature and vegetation index retrieved by optical remote sensing data to drought monitoring. But the vegetation index indicates drought indirectly and lag behind, while the precipitation is directly affect the drought and flood disasters, and microwave remote sensing has its unique advantages to detect precipitation. So, in this paper, on the basis of...
The presence of outliers, noise, corrupt pieces of data and great quantity of samples in a multispectral image, makes the segmentation analysis work tedious. The fuzzy clustering approach, specially, is susceptible to inhomogeneity of characteristics. Furthermore, many algorithms such us FCM, PFCM, FCC, FWCM and modification aim to solve these problems by integrating spacial information. This process...
River interventions disturb the natural flow regime of channel. The impacts generated from river interventions is categorized based on the alteration of fluvial system including channel planform and ecology. The Brahmani River, one of the major peninsular river holds a significant importance for three major states of eastern India. This river has been subjected to periodic flooding events damaging...
We show an application of Moran's Index to process and analyze the waterbody-spread extracted from remotely sensed data. A method that is employed to quantify division-wise waterbody-spread, district-wise waterbody-spread and taluk-wise waterbody-spread spatial complexity is based on Moran's Index computation. The waterbody-spread data for each of the hierarchically partitioned geographical unit-wise...
Ships and ice monitoring is of key importance in numerous applications, such as maritime traffic control, prevention of illegal activities, climate change studies, and maritime security. In this work, the feasibility of near real-time ocean target detection from a constellation of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) images is demonstrated by addressing the two following...
In this work, we have explored a new method which based on Bayesian assimilation for monitoring methane (CH4) emissions at different rice phenological stages. Specifically, we investigate two algorithms, one based on the ground-based radar scatterometer (GBRS) with full polarization (HH, HV, VH, and VV) and the other based on the mechanistic process of agricultural model concluded the parameters of...
In this paper we investigate the use of discriminative model learning through Convolutional Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning strategy, hence it does not recover the filtered image, but the speckle component, which is then subtracted from the noisy one. Training is carried out by considering a large multitemporal SAR image and its multilook version,...
After over two decade of efforts, many land products are now being produced systematically from a variety of satellite data, and these products have been widely used. However, estimating a set of atmospheric and surface variables from one sensor data is often an ill-posed inversion problem, because the number of unknowns is often larger than the available bands[1]. Thus, one has to make assumptions...
This paper addressed the retrieval of land surface temperature (LST) from combined mid-infrared and thermal infrared data of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP). To efficiently remove the effect of the direct solar radiance, a relationship between direct solar radiance and water vapor content, view zenith angle and solar...
For the multi-frequency sensors such as AMSR-E and AMSR-2, the verification results of QP model with dual-channel algorithm (QDCA) soil moisture product are not good in Genhe area. In order to obtain the long time series of soil moisture datasets and improve the accuracy of QDCA in China, this paper improved the vegetation correction method on current QDCA soil moisture algorithm. This paper incorporated...
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