scholarly journals Utilization of UAV (Unmanned Aerial Vehicle) technology for mapping and identification of agroforestry land cover patterns in Namolandur Village, North Sumatra

2021 ◽  
Vol 912 (1) ◽  
pp. 012075
Author(s):  
H Arinah ◽  
A S Thoha ◽  
Z Mardiyadi ◽  
O A Lubis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Unmanned Aerial Vehicle ◽  
Rural Areas ◽  
Human Life ◽  
Low Cost ◽  
Unmanned Aircraft ◽  
Fish Ponds ◽  
Land Utilization ◽  
Aerial Vehicle

Abstract Agroforestry-based land use is widely used in society, particularly in rural areas. With a combination of tree crops (annual) and crops (seasonal), agroforestry patterns can maximize land utilization. Unmanned aircraft, often known as drones, can map and detect land cover to optimise land usage based on agroforestry. Drones have various advantages, including low cost, ease of acquisition, and the ability to utilize them in high-risk situations without endangering human life or in difficult or inaccessible places. They can also fly at low altitudes, resulting in cloud-free shots and sharper images. This research focuses on using an unmanned aerial vehicle (UAV) to map agroforestry patterns in Namolandur Village and detect and determine the area of each agroforestry pattern land cover using aerial camera photos. Using the Mavic 2 pro drone and Pix4D Mapper software for aerial photo processing, Namolandur village became the research subject. The data analysis revealed that agrisilviculture, agrosilvofishery, and agrosilvopastoral were the forms of land use with agroforestry patterns in the village of Namolandur. In addition, water guava, duku fruit (Lansium domestika), oil palm, coconut, and a combination of fish ponds, cattle, and goats are among the geographical analysis of the area and each form of land use.

scholarly journals Photogrammetric mapping using unmanned aerial vehicle

2014 ◽  
Vol XL-1 ◽  
pp. 129-133 ◽  
Author(s):  
N. Graça ◽  
E. Mitishita ◽  
J. Gonçalves
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Rural Areas ◽  
Low Cost ◽  
Direct Determination ◽  
Aerial Images ◽  
Image Block ◽  
Exterior Orientation ◽  
Aerial Vehicle ◽  
Urban And Rural Areas ◽  
Orientation Parameters

Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

scholarly journals Unmanned Aerial Vehicle (UAV) for Mapping Plantation Area

2019 ◽  
Vol 7 (1) ◽  
pp. 79-89
Author(s):  
Sugeng Sugeng ◽  
Ramadhan Adi Putra ◽  
Refinda Fazar Muslim ◽  
Yogi Septianto
Keyword(s):  
Land Use ◽  
Unmanned Aerial Vehicle ◽  
Palm Oil ◽  
Land Use Planning ◽  
Oil Palm ◽  
Unmanned Aircraft ◽  
Mapping Data ◽  
Oil Companies ◽  
Aerial Vehicle ◽  
Mapping Techniques

The development of oil palm plantations from the beginning of planting in 1848 until now can be said to be very significant. As the largest palm oil production country in the world Indonesia has many developing palm oil companies, both national and international. To monitor the vast oil palm plantations, a cheaper and more efficient technological innovation is needed. In order to observe the vast plantation area and the different topography of the land, which can complicate logistical access especially if there is rain making access difficult to pass, we conduct research on monitoring and mapping oil palm plantation areas. The monitoring function is to monitor plantation logistics lines such as, finding a faster route by looking at the contour of the land so as to facilitate transportation access from collectors to each existing post. As for mapping, it functions to map an area of ​​225 hectares with the aim of assessing the condition of oil palm plantations, especially assets from the garden itself. this activity is commonly referred to as landholders by surveying assets or inventory. The use of mapping techniques using unmanned aircraft has several advantages, one of which is more accurate mapping than using satellite imagery. From this mapping data can be developed again such as census mapping data, land use maps, land use planning, and monitoring of pests and weeds. The methods we use include improving the quality of camera resolution, adjusting aircraft height, adjusting aircraft speed, making good airframes, using 2 axis gimbals and special image processing methods Keywords : Mapping, Unmanned Aerial Vehicle (UAV), Plantation, Remote Sense,  Aerial Photo

scholarly journals THE PREDICTION OF POSITION AND ORIENTATION PARAMETERS OF UAV FOR VIDEO IMAGING

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 407-413 ◽  
Author(s):  
D. Wierzbicki
Keyword(s):  
Standard Deviation ◽  
Unmanned Aerial Vehicle ◽  
Prediction Models ◽  
Low Cost ◽  
Digital Camera ◽  
Unmanned Aircraft ◽  
Navigation Data ◽  
Aerial Vehicle ◽  
Position And Orientation ◽  
Trigonometric Model

The paper presents the results of the prediction for the parameters of the position and orientation of the unmanned aerial vehicle (UAV) equipped with compact digital camera. Issue focus in this paper is to achieve optimal accuracy and reliability of the geo-referenced video frames on the basis of data from the navigation sensors mounted on UAV. In experiments two mathematical models were used for the process of the prediction: the polynomial model and the trigonometric model. The forecast values of position and orientation of UAV were compared with readings low cost GPS and INS sensors mounted on the unmanned Trimble UX-5 platform. Research experiment was conducted on the preview of navigation data from 23 measuring epochs. The forecast coordinate values and angles of the turnover and the actual readings of the sensor Trimble UX-5 were compared in this paper. Based on the results of the comparison it was determined that: the best results of co-ordinate comparison of an unmanned aerial vehicle received for the storage with, whereas worst for the coordinate Y on the base of both prediction models, obtained value of standard deviation for the coordinate XYZ from both prediction models does not cross over a admissible criterion 10 m for the term of the exactitudes of the position of a unmanned aircraft. The best results of the comparison of the angles of the turn of a unmanned aircraft received for the angle Pitch, whereas worst for the angles Heading and Roll on the base of both prediction models. Obtained value of standard deviation for the angles of turn HPR from both prediction models does not exceed a admissible exactitude 5° only for the angle Pitch, however crosses over this value for the angles Heading and Roll.

Ecological Waste Treatment and Utilization Systems on Low-Cost, Energy-Saving/Generating and Resources Recoverable Technology for Water Pollution Control in China

1991 ◽  
Vol 24 (5) ◽  
pp. 9-19 ◽  
Author(s):  
Baozhen Wang
Keyword(s):  
Pollution Control ◽  
Rural Areas ◽  
Waste Treatment ◽  
Low Cost ◽  
Fish Ponds ◽  
Receiving Waters ◽  
Recoverable Resources ◽  
Urban And Rural Areas ◽  
Rice Fish ◽  
Utilization Of Wastes

Various ecological waste treatment and utilization systems (EWTUS) available in urban and rural areas in China are described, among which are land treatment and utilization systems (LTUS), eco-pond systems mainly consisting of macrohydrophytes-growing ponds, fish ponds and duck/geese ponds, and comprehensive circulation eco–systems for the treatment and utilization of wastes in rural areas, such as semi–closed eco–system in fish ponds, “rice–fish” and “rice–azolla–fish” symbiotic systems, recycling eco–systems with methane-generating digesters as central link, and comprehensive recycling eco–systems with digesters and eco–ponds as central link. In the various EWTUS, the sewage and wastewaters and other wastes are utilized and converted into various forms of recoverable resources and/or energy, while they are being purified to good quality effluents, meeting their respective discharge standards, and hence acceptable to receiving waters.

scholarly journals Crowdsourcing LUCAS: Citizens Generating Reference Land Cover and Land Use Data with a Mobile App

2020 ◽  
Author(s):  
Juan Carlos Laso Bayas ◽  
Linda See ◽  
Hedwig Bartl ◽  
Tobias Sturn ◽  
Mathias Karner ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Survey Data ◽  
Target Location ◽  
Low Cost ◽  
Mobile App ◽  
Sample Survey ◽  
In Situ Data

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

scholarly journals Multi-Temporal Landsat8 Satellite Data Based Crops and Other Land Use Spatial Estimation in Okara District of Pakistan

2018 ◽  
Author(s):  
Ibrar ul Hassan Akhtar ◽  
Athar Hussain ◽  
Kashif Javed ◽  
Hammad Ghazanfar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Urban Areas ◽  
Integrated Approach ◽  
Kappa Statistics ◽  
Digital Information ◽  
Land Use Land Cover ◽  
Land Utilization ◽  
Cropping Patterns

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land. 

scholarly journals Analyses of Nocturnal Temperature Cooling-Rate Response to Historical Local-Scale Urban Land-Use/Land Cover Change

2011 ◽  
Vol 50 (9) ◽  
pp. 1872-1883 ◽  
Author(s):  
Winston T. L. Chow ◽  
Bohumil M. Svoma
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Cooling Rate ◽  
Rural Areas ◽  
Urban Areas ◽  
Local Scale ◽  
Urban Land Use ◽  
Cooling Rates ◽  
Near Surface ◽  
Over Time

AbstractUrbanization affects near-surface climates by increasing city temperatures relative to rural temperatures [i.e., the urban heat island (UHI) effect]. This effect is usually measured as the relative temperature difference between urban areas and a rural location. Use of this measure is potentially problematic, however, mainly because of unclear “rural” definitions across different cities. An alternative metric is proposed—surface temperature cooling/warming rates—that directly measures how variations in land-use and land cover (LULC) affect temperatures for a specific urban area. In this study, the impact of local-scale (<1 km2), historical LULC change was examined on near-surface nocturnal meteorological station temperatures sited within metropolitan Phoenix, Arizona, for 1) urban versus rural areas, 2) areas that underwent rural-to-urban transition over a 20-yr period, and 3) different seasons. Temperature data were analyzed during ideal synoptic conditions of clear and calm weather that do not inhibit surface cooling and that also qualified with respect to measured near-surface wind impacts. Results indicated that 1) urban areas generally observed lower cooling-rate magnitudes than did rural areas, 2) urbanization significantly reduced cooling rates over time, and 3) mean cooling-rate magnitudes were typically larger in summer than in winter. Significant variations in mean nocturnal urban wind speeds were also observed over time, suggesting a possible UHI-induced circulation system that may have influenced local-scale station cooling rates.

scholarly journals Suitability of a Non-Dispersive Infrared Methane Sensor Package for Flux Quantification Using an Unmanned Aerial Vehicle

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4705 ◽  
Author(s):  
Adil Shah ◽  
Joseph Pitt ◽  
Khristopher Kabbabe ◽  
Grant Allen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Mole Fraction ◽  
Low Cost ◽  
Methane Flux ◽  
Gain Factor ◽  
Measured Signal ◽  
Allan Deviation ◽  
Methane Sensor ◽  
Aerial Vehicle ◽  
Flux Quantification

Point-source methane emission flux quantification is required to help constrain the global methane budget. Facility-scale fluxes can be derived using in situ methane mole fraction sampling, near-to-source, which may be acquired from an unmanned aerial vehicle (UAV) platform. We test a new non-dispersive infrared methane sensor by mounting it onto a small UAV, which flew downwind of a controlled methane release. Nine UAV flight surveys were conducted on a downwind vertical sampling plane, perpendicular to mean wind direction. The sensor was first packaged in an enclosure prior to sampling which contained a pump and a recording computer, with a total mass of 1.0 kg. The packaged sensor was then characterised to derive a gain factor of 0.92 ± 0.07, independent of water mole fraction, and an Allan deviation precision (at 1 Hz) of ±1.16 ppm. This poor instrumental precision and possible short-term drifts made it non-trivial to define a background mole fraction during UAV surveys, which may be important where any measured signal is small compared to sources of instrumental uncertainty and drift. This rendered the sensor incapable of deriving a meaningful flux from UAV sampling for emissions of the order of 1 g s−1. Nevertheless, the sensor may indeed be useful when sampling mole fraction enhancements of the order of at least 10 ppm (an order of magnitude above the 1 Hz Allan deviation), either from stationary ground-based sampling (in baseline studies) or from mobile sampling downwind of sources with greater source flux than those observed in this study. While many methods utilising low-cost sensors to determine methane flux are being developed, this study highlights the importance of adequately characterising and testing all new sensors before they are used in scientific research.

Sign in / Sign up

Export Citation Format

Share Document