Adequate Spatial Information Research Articles

Mapping Smallholder Maize Farms Using Multi-Temporal Sentinel-1 Data in Support of the Sustainable Development Goals

Reducing food insecurity in developing countries is one of the crucial targets of the Sustainable Development Goals (SDGs). Smallholder farmers play a crucial role in combating food insecurity. However, local planning agencies and governments do not have adequate spatial information on smallholder farmers, and this affects the monitoring of the SDGs. This study utilized Sentinel-1 multi-temporal data to develop a framework for mapping smallholder maize farms and to estimate maize production area as a parameter for supporting the SDGs. We used Principal Component Analysis (PCA) to pixel fuse the multi-temporal data to only three components for each polarization (vertical transmit and vertical receive (VV), vertical transmit and horizontal receive (VH), and VV/VH), which explained more than 70% of the information. The Support Vector Machine (SVM) and Extreme Gradient Boosting (Xgboost) algorithms were used at model-level feature fusion to classify the data. The results show that the adopted strategy of two-stage image fusion was sufficient to map the distribution and estimate production areas for smallholder farms. An overall accuracy of more than 90% for both SVM and Xgboost algorithms was achieved. There was a 3% difference in production area estimation observed between the two algorithms. This framework can be used to generate spatial agricultural information in areas where agricultural survey data are limited and for areas that are affected by cloud coverage. We recommend the use of Sentinel-1 multi-temporal data in conjunction with machine learning algorithms to map smallholder maize farms to support the SDGs.

DEVELOPMENT OF A SPACE TECHNOLOGY CAPACITY BUILDING INITIATIVE AT THE FEDERAL UNIVERSITY OF TECHNOLOGY, AKURE, NIGERIA

Satellite communication is a wireless means of transmission of intelligible signals/information. When properly utilized it will bring about a great and positive development on the economic growth of any nation. The Federal Government of Nigeria made a giant step in the communication sector by launching five satellites into space: NigeriaSat-1, NigComSat- 1, NigeriaSat-2r, NigeriaSat-X and NigComSat-1R. With adequate spatial information, informed decisions can be made by stakeholders and adequate steps taken to ensure the growth of the nation. Demand for training capacity building in space technology is increasing. Unfortunately, space technology is a relatively expensive field with ongoing research for affordable training approaches. This paper presents methods of building capacity by developing Demo Satellites that receive telemetry data with radiofrequency and internet of things communication protocol. Web Dashboard was developed for remote monitoring of ground station and for exploring mobility in data communication, Localization was achieved to also track the Demo Satellites and the ground station in real-time. It is shown that the implementation of a low-cost capacity building programme is not only possible but a goal that should be aimed at. Multiple segments in the design of the schematics produced can be reused. It presents a pioneer satellite constellation prototype that displays the capabilities of a satellite in solving some of the country’s challenges and creating awareness on space research and its trends.

Ground-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetation.

Rangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the 'travelling salesperson problem' (TSP) to increase time and cost efficiency. While UAS images can be acquired 2-3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.

Evaluation of the suitability of six drought indices in naturally growing, transitional vegetation zones in Inner Mongolia (China).

Naturally growing vegetation often suffers from the effects of drought. There exists a vast number of drought indices (DI’s) to assess the impact of drought on the growth of crops and naturally occurring vegetation. However, assessing the fitness of these indices for large areas with variable vegetation cover is often problematic because of the absence of adequate spatial information. In this study, we compared six DI’s to NDVI (the normalized difference vegetation index), a common indicator of vegetation occurrence and health based on satellite-acquired reflectance data. The study area covers an aridity gradient from forests to deserts along a 2,400-km-long section across the Inner Mongolia Autonomous Region of China. On an annual timescale, standardized precipitation index (SPI) was the most appropriate in assessing drought in steppes and deserts. On a seasonal timescale, the self-calibrated Palmer drought severity index (scPDSI) displayed the greatest sensitivity during the summer, but not during the other seasons. On a monthly timescale, scPDSI demonstrated the greatest sensitivity to the various vegetation zones (i.e., forests, steppes, and deserts) in June and July. Further analysis indicated that summer drought had a lag-effect on vegetation growth, which varied from one to six months according to the specific vegetation cover. The mixed response of DI’s to NDVI and the lag-effect in transitional vegetation on annual, seasonal, and monthly timescales were ascribed to differences in DI definition and the dominant plant species within the transitional cover. The current study has the potential to inform the drafting of selection criteria of DI’s for the study of drought-related impact on naturally growing vegetation at timescales from month to year.

Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time.

A number of acoustic super-resolution techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit. A crucial aspect of all ultrasound (US) super-resolution (SR) methods using single microbubble localization is time-efficient detection of individual bubble signals. Due to the need for bubbles to circulate through the vasculature during acquisition, slow flows associated with the microcirculation limit the minimum acquisition time needed to obtain adequate spatial information. Here, a model is developed to investigate the combined effects of imaging parameters, bubble signal density, and vascular flow on SR image acquisition time. We find that the estimated minimum time needed for SR increases for slower blood velocities and greater resolution improvement. To improve SR from a resolution of λ /10 to λ /20 while imaging the microvasculature structure modeled here, the estimated minimum acquisition time increases by a factor of 14. The maximum useful imaging frame rate to provide new spatial information in each image is set by the bubble velocity at low blood flows (<150 mm/s for a depth of 5 cm) and by the acoustic wave velocity at higher bubble velocities. Furthermore, the image acquisition procedure, transmit frequency, localization precision, and desired super-resolved image contrast together determine the optimal acquisition time achievable for fixed flow velocity. Exploring the effects of both system parameters and details of the target vasculature can allow a better choice of acquisition settings and provide improved understanding of the completeness of SR information.

Optical Probes for Neurobiological Sensing and Imaging.

Fluorescent nanosensors and molecular probes are next-generation tools for imaging chemical signaling inside and between cells. Electrophysiology has long been considered the gold standard in elucidating neural dynamics with high temporal resolution and precision, particularly on the single-cell level. However, electrode-based techniques face challenges in illuminating the specific chemicals involved in neural cell activation with adequate spatial information. Measuring chemical dynamics is of fundamental importance to better understand synergistic interactions between neurons as well as interactions between neurons and non-neuronal cells. Over the past decade, significant technological advances in optical probes and imaging methods have enabled entirely new possibilities for studying neural cells and circuits at the chemical level. These optical imaging modalities have shown promise for combining chemical, temporal, and spatial information. This potential makes them ideal candidates to unravel the complex neural interactions at multiple scales in the brain, which could be complemented by traditional electrophysiological methods to obtain a full spatiotemporal picture of neurochemical dynamics. Despite the potential, only a handful of probe candidates have been utilized to provide detailed chemical information in the brain. To date, most live imaging and chemical mapping studies rely on fluorescent molecular indicators to report intracellular calcium (Ca2+) dynamics, which correlates with neuronal activity. Methodological advances for monitoring a full array of chemicals in the brain with improved spatial, temporal, and chemical resolution will thus enable mapping of neurochemical circuits with finer precision. On the basis of numerous studies in this exciting field, we review the current efforts to develop and apply a palette of optical probes and nanosensors for chemical sensing in the brain. There is a strong impetus to further develop technologies capable of probing entire neurobiological units with high spatiotemporal resolution. Thus, we introduce selected applications for ion and neurotransmitter detection to investigate both neurons and non-neuronal brain cells. We focus on families of optical probes because of their ability to sense a wide array of molecules and convey spatial information with minimal damage to tissue. We start with a discussion of currently available molecular probes, highlight recent advances in genetically modified fluorescent probes for ions and small molecules, and end with the latest research in nanosensors for biological imaging. Customizable, nanoscale optical sensors that accurately and dynamically monitor the local environment with high spatiotemporal resolution could lead to not only new insights into the function of all cell types but also a broader understanding of how diverse neural signaling systems act in conjunction with neighboring cells in a spatially relevant manner.

Opportunities for UAV mapping to support unplanned settlement upgrading

The effort to improve sub-standard living conditions in unplanned settlements is often hindered due to a lack of adequate spatial information describing the baseline situation and changes occurring during and after the upgrading process. Low-cost Unmanned Aerial Vehicles (UAVs) could provide very detailed, up-to-date spatial information for small unplanned areas as and when required. To investigate the utility of such platforms in settlement upgrading, UAV flights were conducted over approximately 150 ha of unplanned settlements in the City of Kigali in May and June 2015. Data obtained with UAV were supplemented by an analysis of the spatial information needs of various stakeholders involved in the upgrading project. In the context of the upgrading project, the results of this study identify four main benefits of using UAV imagery. First, it could replace the 2008 25 cm ortho-imagery by up-to-date 3 cm imagery in current workflows for map updating. Second, it enables the extraction of additional information which was previously unavailable, such as detailed elevation data to support surface water runoff analysis and drainage capacity calculations. Third, it speeds up field work and fourth, the imagery provides a foundation for communication between different stakeholders. When using UAVs it is also important to take many practical considerations into account, as well as the societal and ethical context. Results of the first experiences in Kigali indicate that while the use of UAV is not generally perceived as a problem by the local population, fear of forced displacement and expropriation may raise concerns amongst the residents. Communication between the UAV operator, the local government, local leaders and with the residents before and during flights, and sharing the benefits of the acquired information are important to mitigate these fears. Moreover, the resolution and quality of the images is such that privacy concerns and issues such as their potential to be used to the detriment of residents of such areas should not be ignored. Keywords : Unmanned Aerial Vehicles, unplanned settlements, housing upgrading projects, spatial information requirements.

Urban habitats and the injury landscape

Multi-dimensional data analysis has rarely been performed on injury data. However, the implementation of sound policies can only be considered over geographical space when typologies of health vectors are considered at a global scale, and may be integrated at local level for decision making. In this study, frequency data of six injury types in Extended Golden Horseshoe area are collected and self-organizing maps (SOM) are used to construct an injury cluster system for the region. The results indicate that the variables are positively correlated and several outliers are found in the study area. The implementation of SOM brings an efficient tool for planning and assessment of spatially-explicit clusters for decision making at local and regional level. Furthermore, the visualization of multi-dimensional data allows for an integrative system of understanding the connectivity of injuries to existing land use types. The results also suggest that the injury prevention strategies should be reinforced in smaller CMAs like St. Catherine's – Niagara and Oshawa. But also, that land use typologies exist within metropolitan areas that create more probable injury outcomes. Overall our paper suggests the existence of clear clusters over geographical space that transcend traditional analysis techniques that may be adapted to ubiquitous concerns in epidemiology linked to land use planning and safer environments. Self-organizing maps may have a profound and significant role in merging decision-makers with adequate spatial information for health determinants and assessments suggesting a new integrative method of multi-dimension analysis of land use and injury data.

Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca &amp; G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)

It is estimated that most of the problems in forestry associated with the spatial attributes. From the perspective of forest function that includes production, ecological, and social functions, the spatial aspects has always been a very important part. In Indonesia, the forestry areas is always dealing with very large areas which is mostly inaccessible due to limitation of roads, mountainous with steep slopes, cliffs, hills or wetland such as peat, swamp or marsh. This condition makes it difficult to collect the data in quick manner comprehensively with low cost. Veronique et al. (2012) recognized that remote technology may provide objective, practical and cost-effective solution. Currently, one of the most reliable data source that can be repetitively acquired with a unique and consistent traits are those derived from satellite imageries. It had been known that since the 1990s, earth resources remote sensing sensor is progressively developed either with finer spatial resolution, higher spectral resolution, more frequent revisit or wider dynamic range. The advent of high spectral resolution (e.g. hyperspectral) is quite challenging and prospectively gives a significant contribution, especially in forest management with higher level of detailed information. Without having adequate spatial information supported by strong scientific arguments, the forestry sector will be persistently pressured by many other sectors.

Measurement of porto-systemic shunting in mice by novel three-dimensional micro-single photon emission computed tomography imaging enabling longitudinal follow-up

The reference method for diagnosing porto-systemic shunting (PSS) in experimental portal hypertension involves measuring (51)Chrome ((51)Cr)-labelled microspheres. Unfortunately, this technique necessitates the sacrifice of animals. Alternatively, (99m)technetium-macroaggregated albumin ((99m)Tc-MAA) has been used; however, planar scintigraphy imaging techniques are not quantitatively accurate and adequate spatial information is not attained. Here, we describe a reliable, minimally invasive and rapid in vivo imaging technique, using three-dimensional single photon emission computed tomography (3D SPECT) modus, that allows more accurate quantification, serial measurements and spatial discrimination. Partial portal vein ligation, common bile duct ligation and sham were induced in male mice. A mixture of (51)Cr microspheres and (99m)Tc-macroaggregated albumin particles was injected into the splenic pulpa. All mice were scanned in vivo with microSPECT (1 mm spatial resolution) and, when mandatory for localisation, a microSPECT-CT was acquired. A relative quantitative analysis was performed based on the 3D reconstructed datasets. Additionally, (51)Cr was measured in the same animals to calculate the correlation coefficient between the (99m)Tc detection and the gold standard (51)Cr. In each measuring modality, the PSS fraction was calculated using the formula: [(lung counts)/(lung counts+liver counts)] x 100. A significant correlation between the (99m)Tc detection and (51)Cr was demonstrated in partial portal vein ligation, common bile duct ligation and sham mice and there was a good agreement between the two modalities. MicroSPECT scanning delivers high spatial resolution and 3D image reconstructions. We have demonstrated that quantitative high-resolution microSPECT imaging with (99m)Tc-MAA is useful for detecting the extent of PSS in a non-sacrificing set-up. This technology permits serial measurements and high-throughput screening to detect baseline PSS, which is especially important in pharmacological studies.

Mapping the spatial variation of soil water content at the field scale with different ground penetrating radar techniques

Summary Two ground penetrating radar (GPR) techniques were used to estimate the shallow soil water content at the field scale. The first technique is based on the ground wave velocity measured with a bistatic impulse radar connected to 450 MHz ground-coupled antennas. The second technique is based on inverse modeling of an off-ground monostatic TEM horn antenna in the 0.8–1.6 GHz frequency range. Data were collected on a 8 by 9 m partially irrigated intensive research plot and along four 148.5 m transects. Time domain reflectometry, capacitance sensors, and volumetric soil samples were used as reference measurements. The aim of the study was to test the applicability of the ground wave method and the off-ground inverse modeling approach at the field scale for a soil with a silt loam texture. The results for the ground wave technique were difficult to interpret due to the strong attenuation of the GPR signal, which is related to the silt loam texture at the test site. The root mean square error of the ground wave technique was 0.076 m 3 m −3 when compared to the TDR measurements and 0.102 m 3 m −3 when compared with the volumetric soil samples. The off-ground monostatic GPR measured less within-field soil water content variability than the reference measurements, resulting in a root mean square error of 0.053 m 3 m −3 when compared with the TDR measurements and an error of 0.051 m 3 m −3 when compared with the volumetric soil samples. The variability between the two GPR measurements was even larger with a RSME of 0.115 m 3 m −3 . In summary, both GPR methods did not provide adequate spatial information on soil water content variation at the field scale. The main reason for the deviating results of the ground wave method was the poor data quality due to high silt and clay content at the test site. Additional reasons were shallow reflections and the dry upper soil layer that cannot be detected by the ground wave method. In the case of off-ground GPR, the high sensitivity to the dry surface layer is the most likely reason for the observed deviations. The off-ground GPR results might be improved by using a different antenna that allows data acquisition in a lower frequency range.

3D-Segmentation of the 18F-choline PET Signal for Target Volume Definition in Radiation Therapy of the Prostate

Volumetric assessment of PET signals becomes increasingly relevant for radiotherapy (RT) planning. Here, we investigate the utility of 18F-choline PET signals to serve as a structure for semi-automatic segmentation for forward treatment planning of prostate cancer. 18F-choline PET and CT scans of ten patients with histologically proven prostate cancer without extracapsular growth were acquired using a combined PET/CT scanner. Target volumes were manually delineated on CT images using standard software. Volumes were also obtained from 18F-choline PET images using an asymmetrical segmentation algorithm. PTVs were derived from CT 18F-choline PET based clinical target volumes (CTVs) by automatic expansion and comparative planning was performed. As a read-out for dose given to non-target structures, dose to the rectal wall was assessed. Planning target volumes (PTVs) derived from CT and 18F-choline PET yielded comparable results. Optimal matching of CT and 18F-choline PET derived volumes in the lateral and cranial-caudal directions was obtained using a background-subtracted signal thresholds of 23.0+/-2.6%. In antero-posterior direction, where adaptation compensating for rectal signal overflow was required, optimal matching was achieved with a threshold of 49.5+/-4.6%. 3D-conformal planning with CT or 18F-choline PET resulted in comparable doses to the rectal wall. Choline PET signals of the prostate provide adequate spatial information amendable to standardized asymmetrical region growing algorithms for PET-based target volume definition for external beam RT.

Environmental vulnerability: Problem of an adequate spatial information unit as disclosed by the project ONIX-GPOV

Environmental vulnerability: Problem of an adequate spatial information unit as disclosed by the project ONIX-GPOV

The Utilization of External and Movement Cues in Simple Spatial Tasks by Blind and Sighted Children

The role of visual experience in coding spatial position by movements or by external cues was examined in simple (nonrotational) shift tasks with blind and sighted children. Age and the salience of external cues were also of interest. Results showed that the congenitally totally blind used movement cues significantly more even when external cues were present and prominent. The blind with minimal visual experience coded by external cues, but made errors beyond the age by which blindfolded sighted children performed correctly. It was argued that visual experience affects coding by drawing attention to external cues, and by providing more adequate spatial information than other sources usually available to the blind. In its absence, movement coding and self-reference can become preferred strategies.

SELECTIVE REGISTRATION OF INFORMATION IN VISUAL JUDGMENT OF SURFACE SLANT.

Two surface textures projected theoretically adequate spatial information but induced different constant errors over a series of 32 Ss' slant judgments. On measuring judgmental errors for a surface combining both textures, the errors replicated those for one of the original textures, thereby suggesting selective registration from the total available information.