Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

2020 ◽  
Vol 3 (2) ◽  
pp. 58-73
Author(s):  
Vijay Bhagat ◽  
Ajaykumar Kada ◽  
Suresh Kumar
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Unmanned Aerial System ◽  
Sustainable Land Management ◽  
Efficient Tool ◽  
Site Specific ◽  
The Earth ◽  
Interesting Area

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

scholarly journals Agricultural Land Suitability Assessment Using Satellite Remote Sensing-Derived Soil-Vegetation Indices

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 223
Author(s):  
Rubaiya Binte Mostafiz ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Agricultural Land ◽  
Expert Knowledge ◽  
Vegetation Indices ◽  
Land Suitability ◽  
Assessment System ◽  
Yield Estimation ◽  
Suitability Assessment ◽  
Land Suitability Assessment

Satellite remote sensing technologies have a high potential in applications for evaluating land conditions and can facilitate optimized planning for agricultural sectors. However, misinformed land selection decisions limit crop yields and increase production-related costs to farmers. Therefore, the purpose of this research was to develop a land suitability assessment system using satellite remote sensing-derived soil-vegetation indicators. A multicriteria decision analysis was conducted by integrating weighted linear combinations and fuzzy multicriteria analyses in a GIS platform for suitability assessment using the following eight criteria: elevation, slope, and LST vegetation indices (SAVI, ARVI, SARVI, MSAVI, and OSAVI). The relative priorities of the indicators were identified using a fuzzy expert system. Furthermore, the results of the land suitability assessment were evaluated by ground truthed yield data. In addition, a yield estimation method was developed using indices representing influential factors. The analysis utilizing equal weights showed that 43% of the land (1832 km2) was highly suitable, 41% of the land (1747 km2) was moderately suitable, and 10% of the land (426 km2) was marginally suitable for improved yield productions. Alternatively, expert knowledge was also considered, along with references, when using the fuzzy membership function; as a result, 48% of the land (2045 km2) was identified as being highly suitable; 39% of the land (2045 km2) was identified as being moderately suitable, and 7% of the land (298 km2) was identified as being marginally suitable. Additionally, 6% (256 km2) of the land was described as not suitable by both methods. Moreover, the yield estimation using SAVI (R2 = 77.3%), ARVI (R2 = 68.9%), SARVI (R2 = 71.1%), MSAVI (R2 = 74.5%) and OSAVI (R2 = 81.2%) showed a good predictive ability. Furthermore, the combined model using these five indices reported the highest accuracy (R2 = 0.839); this model was then applied to develop yield prediction maps for the corresponding years (2017–2020). This research suggests that satellite remote sensing methods in GIS platforms are an effective and convenient way for agricultural land-use planners and land policy makers to select suitable cultivable land areas with potential for increased agricultural production.

Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices

2021 ◽  
Vol 25 (9) ◽  
pp. 30-37
Author(s):  
N.N. Sliusar ◽  
A.P. Belousova ◽  
G.M. Batrakova ◽  
R.D. Garifzyanov ◽  
M. Huber-Humer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Google Earth ◽  
The State ◽  
Landsat 8 ◽  
The Earth

The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.

Žemės stebėjimas iš kosmoso

2021 ◽  
Author(s):  
Justinas Kilpys ◽  
Laurynas Jukna ◽  
Edvinas Stonevičius ◽  
Rasa Šimanauskienė ◽  
Linas Bevainis
Keyword(s):  
Remote Sensing ◽  
Risk Management ◽  
Environmental Monitoring ◽  
Satellite Remote Sensing ◽  
Disaster Risk ◽  
Satellite Observations ◽  
Sensor Data ◽  
Earth Observations ◽  
The Earth ◽  
Insight Into

Title in English: Earth Observations from Space. There are more than 150 environmental satellites orbiting the Earth, and they are constantly monitoring its surface and the processes happening on it. This textbook offers an introduction to the physical concepts of satellite observations, describes how sensor data is transformed into information about the Earth’s surface and how it can be applied. The scientific background of satellite remote sensing is illustrated using examples from applications in agriculture, forestry, environmental monitoring, disaster risk management, and many other areas. Book provides insight into how satellite remote sensing is used to explore and monitor natural and anthropocentric processes on the Earth and serves as introduction to the practical remote sensing.

scholarly journals Use of a GCM to explore sampling issues in connection with satellite remote sensing of the Earth radiation budget

2000 ◽  
Vol 105 (D16) ◽  
pp. 20757-20772 ◽  
Author(s):  
Laura D. Fowler ◽  
Bruce A. Wielicki ◽  
David A. Randall ◽  
Mark D. Branson ◽  
Gary G. Gibson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Radiation Budget ◽  
The Earth ◽  
Earth Radiation Budget ◽  
Earth Radiation

scholarly journals Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods

2015 ◽  
Vol 19 (7) ◽  
pp. 3203-3216 ◽  
Author(s):  
J. Iwema ◽  
R. Rosolem ◽  
R. Baatz ◽  
T. Wagener ◽  
H. R. Bogena
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Satellite Remote Sensing ◽  
Cosmic Ray ◽  
Sampling Strategies ◽  
Site Specific ◽  
Neutron Intensity ◽  
Soil Wetness ◽  
Semi Arid

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N0, HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.

scholarly journals ROLE OF REMOTE SENSING AND GIS IN FORESTRY

2014 ◽  
pp. 231-235
Author(s):  
MEGHA GUPTA ◽  
ANKITA KHARE ◽  
SRASHTI PATHAK
Keyword(s):  
Remote Sensing ◽  
Large Volume ◽  
Spatial Data ◽  
Direct Contact ◽  
Remote Sensing And Gis ◽  
Computer Hardware ◽  
Space Technology ◽  
Common People ◽  
The Earth

The Earth is constantly under observation from dozens of satellites orbiting the planet and collecting data. They are engaged in something called "remote sensing”: the act of obtaining information about something without being in direct contact with it. Now-a-days the field of Remote Sensing and GIS has become exciting and glamorous with rapidly expanding opportunities. Many organizations spend large amounts of money on these fields. Here the question arises why these fields are so important in recent years. Two main reasons are there behind this. Now-a-days scientists, researchers, students, and even common people are showing great interest for better understanding of our environment. Development in complicated space technology which can provide large volume of spatial data, along with declining costs of computer hardware and software has made Remote Sensing and G.I.S. affordable to not only complex environmental/spatial situation but also affordable to an increasingly wider audience.

Geographic Space Ontology, Locus-Object, and Spatial Data Representation Semantic Theory

2014 ◽  
pp. 28-52
Author(s):  
Sébastien Gadal
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
General Framework ◽  
Data Representation ◽  
Semantic Theory ◽  
Semantic Concept ◽  
Geographic Space ◽  
The Earth ◽  
Geographic Object

Within the general framework of the analysis of the geographic space and its ontological components by remote sensing, the author explores the ability of the morphogenetic modeling in the recognition of one major ontological and semantic concept of geography: the “locus-object.” The “locus-object” couple concept results from the interrelation formalization between the geographic locus, the geographic object, and the geo-localization notions. Geographic loci and objects are linked and both geo-localized. The links and relations between locus and object are mathematically formalized by geospatiology, the study of the logical role of space in the study of entities on the surface of the Earth. Morphogenetic modeling recognizes the loci of the geographic space by spatial discontinuities detection. The spatial discontinuities allow the identification of the types of spatial differentiations (boundaries, limits) between two geographic entities. The concept of “locus-object” is one of the key conceptual ontological elements of the geographic space.

scholarly journals Automatic delineation algorithm for site-specific management zones based on satellite remote sensing data

2017 ◽  
Vol 19 (4) ◽  
pp. 684-707 ◽  
Author(s):  
Claudia Georgi ◽  
Daniel Spengler ◽  
Sibylle Itzerott ◽  
Birgit Kleinschmit
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Site Specific ◽  
Management Zones ◽  
Sensing Data ◽  
Specific Management
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