Satellite Remote Sensing and GIS Applications in Agricultural Meteorology | WMO

 

meteorological application of remote sensing

In this paper, current status of using remote sensing (space- and surfacebased)-in WMO Regions II and V(Asia and the SouthWest Pacific) - monitoring and for analysis of meteorological variables and climatologproducing ies is presented. Specifically, application of remote sensing data and methodologies lightning climatology, to producing deriving. As an important means of spatial data acquisition, UAV remote sensing has the advantages of long battery life, real-time image transmission, high-risk area detection, low cost, and flexibility. It is widely used in many fields. Application of remote sensing of UAVs in meteorological monitoring. Remote Sensing and GIS Application in Agro-ecological zoning by N.R. Patel [PDF - MB] pages Crop Growth Modeling and its Applications in Agricultural Meteorology by V. Radha Krishna Murthy [PDF - MB] pages Crop Growth and Productivity Monitoring and Simulation using Remote Sensing and GIS by V.K. Dadhwal [PDF - MB].



E-mail address: cjt bham. Use the link below to share a full-text version of this article with your friends and colleagues. Learn more. The last decade has seen a considerable increase in the amount and availability of remotely sensed data. This paper reviews the satellites, sensors and studies relevant to land surface temperature measurements in the context of meteorology and climatology. The focus is on using the thermal infrared part of the electromagnetic spectrum for useful measurements of land meteorological application of remote sensing temperature, which can be beneficial for a number of uses, for example urban heat island measurements.

Usage is growing within the fields of meteorology and climatology, and works in unison with the use of Geographical Information Systems GIS Chapman and Thornes, ; Dyras et al. Techniques can provide increased spatial coverage when compared to weather station data Mendelsohn et al.

Regardless of the scale of the study, remote sensing offers an opportunity to provide a consistent and repeatable methodology, suited equally to both quick pilot studies as well as long term monitoring campaigns. Although the initial cost of remote meteorological application of remote sensing platforms is high, the ease of data availability to end researchers, combined with the often extensive temporal and spatial coverage available, offers a marked improvement to traditional fieldwork campaign studies.

This review looks at remote sensing as a tool for meteorology and climatology, meteorological application of remote sensing, with a particular focus on using remotely sensed data to calculate land surface temperature LST. The UHI was first investigated through satellite techniques in the s Matson et al. Exploration of the UHI effect via satellite techniques is the primary focus of this review and specific studies will be discussed under relevant sensor headings, meteorological application of remote sensing.

Remotely sensed data can be a useful resource for the modelling community; helping to define input data such as short wave net radiation for land surface models Kim and Liang,or increasing the utility of surface energy balance Senay et al. A number of reviews exist in this general area. For example, see Kidd et al. This review differs from other articles as it details multiple sources of data including timing and availability.

This section outlines the theory behind deriving LST from remote sensing techniques, and covers some fundamental details that need to be understood if data are to be used accurately and usefully for sensing the weather.

If more detailed information is required, the physics behind deriving LST is explained in more detail in Dash et al. Several textbooks are also available e. Lillesand et al. Alternatively, meteorological application of remote sensing, the specification documents of individual sensors or platforms can be inspected see links in Table II. A fundamental requirement for remote sensing is the detection of electromagnetic radiation EMR by sensors on a remote sensing platform.

This is useful as different objects emit EMR in different ways, so the spectral response can be analysed. However, one exception to this is passive microwave which has been used for LST measurement in China Chen et al. Passive microwave measurements tend to be limited in the sense that they typically offer a very coarse resolution in the tens of kilometres.

For this reason, this review will focus on TIR sensors, which are more commonly used and offer higher resolution data. The electromagnetic spectrum arranged by wavelength.

Thermal infrared highlighted in bold. Adapted from Lillesand et al. This includes upwelling radiance emitted from the ground, upwelling radiance from the atmosphere, and the downwelling radiance emitted by the atmosphere and reflected from the ground, meteorological application of remote sensing.

During the day there is both emission and reflection of EMR, but during the night sensed EMR is restricted to only emission. TOA radiances are then converted to LST by correcting for three main effects; atmospheric attenuation, angular effects and spectral emissivity values at the surface, meteorological application of remote sensing.

Atmospheric attenuation absorption, reflection or refraction and scattering will alter the EMR as it passes through the atmosphere, resulting in differences between TOA radiances and LST. Within TIR wavelengths, most attenuation is due to water vapour and aerosols. Angular effects are a product of the variety in viewing angles resulting in wavelength shifting which must be compensated for when estimating radiances Dash et al.

Spectral emissivity refers to the relative ability of a surface to emit radiation and can be highly variable due to the heterogeneity of land, and is influenced by surface cover, vegetation cover and soil moisture.

Quantification of emissivity is achieved by considering the ratio of energy emitted by a surface with respect to the energy emitted by a black body at the same temperature. However, calculations are complicated because natural surfaces do not behave like a black body and thus need correction using typical emissivity values Table I. These corrections are done through complex algorithms, alongside extensive validation and verification, resulting in a final product that can be used by a meteorologist.

Orbital satellite remote sensing methods are limited by image acquisition time which is set by the orbital characteristics of the relevant satellite and means that readings at specific times cannot be obtained or requested unless they match the orbit. Geostationary satellites, which stay in the same position relative to the Earth, offer a greatly increased temporal resolution at the expense of reducing spatial resolution and coverage area.

However, not all images may be accurate, meteorological application of remote sensing, as high zenith angles result in a lengthened atmospheric path that can result in less accurate images Streutker, Many images come with additional metadata such as quality control scientific data sets that can help recognize this problem.

It is also worth noting that not all images are readily available, despite orbital paths. Archives may be corrupt, or the satellite may have been offline or manoeuvering in such a way that meant observations were not collected.

Meteorological application of remote sensing, if a study has a specific temporal requirement it can therefore be useful to check multiple potential sources.

Choice of image timing is also important. For example, Rigo et al. Similarly, Hartz et al. Limitations of resolution are being investigated, and algorithms have been developed to sharpen thermal images to increase the resolution Dominguez et al. A serious limitation of TIR satellite remote sensing techniques is the requirement for clear skies in order to derive accurate readings. Hence, cloud cover can be a serious problem.

Dependent on the research requirements, composite images from multiple passes can often be created in order to construct an image without cloud cover limitations Neteler,or algorithms can be used to estimate pixels Jin and Dickinson, Alternatively, modelling or passive microwave remote sensing could be used Wan, if increased coverage is required.

An effect of this is that seasonal differences can influence image availability increased cloud cover and accuracy increased rainfall causing wet surfaces leading to unreliable LST measurementsfor example winter study periods can be more difficult Rajasekar and Weng, Two main algorithmic approaches are used for conversions, the radiative transfer equation RTE and the generalized split window technique GSW.

These techniques are explained in detail elsewhere Dash et al. Nine different split window algorithms have been evaluated Yu et al. This is one difficulty with remotely sensed imagery covering large areas: assumptions of average emissivity across a heterogeneous area.

The differences between satellite derived LST and ground measured air meteorological application of remote sensing is one area that is still not fully understood, and is the subject of ongoing work. Reviews Arnfield, ; Weng, cite research that details both similarities between air and LST Nichol, and differences Weller and Thornes, Related work includes comparing LST and air temperatures over large areas and multiple ecosystems in Africa Vancutsem et al.

There is a number of different satellite remote sensing platforms with multiple sensors in the TIR spectrum, giving the modern meteorologist a number of potentially useful datasets to measure LST.

Datasets are available for different time periods, at different resolutions, with varying accuracy, therefore this section outlines the various datasets available, ordered by launch date Figure 2. Currently operating satellites are also summarized in Table II.

This review will focus on satellite based sensors, meteorological application of remote sensing, as they offer global coverage and good availability. Airborne sensors e. Similarly meteorological application of remote sensing paper does not detail private or commercial satellites, as meteorological application of remote sensing are generally not as accessible for researchers.

Timeline of satellite launches and associated sensor data availability. Data availability to indicates ongoing availability. A strength of the AVHRR sensor is that there is a relatively long historical record of data, and correspondingly a significant body of research that has used the sensor for many different uses.

This long term record is not possible with most other sensors as the historical data are not available, as the satellites and sensors were not developed or in space.

Matson et al. The Landsat series of satellites are probably the most well known, with the longest record of Earth observations from space. The Landsat data archive has only been freely available sincetherefore the number of studies has increased in recent years. A disadvantage of data from Landsat is that they are not collected at night, and the thermal calibration is meteorological application of remote sensing. In the USA, Aniello et al.

One satellite image was used and the results showed that micro UHIs were highest in the centre and were generally resulting from a lack of tree cover. Weng et al. Weng used three Landsat TM images fromand to study the UHI in Guangzhou, China alongside fractal analysis with the result that showed two significant heat islands existed in the city. Further work has been done in China Chen et al. The combination of remote sensing and modelling was found to be mutually complementary.

Resampling generally using the nearest neighbour algorithm the thermal band to lower resolutions e. Landsat meteorological application of remote sensing a great strength in terms of spatial resolution, however its 16 day revisit time and lack of night time image acquisition is limiting at the temporal scale.

Stathopoulou and Cartalis discusses how future studies may focus on a time series of images as the UHI strongly depends on synoptic weather conditions. GOES related studies discuss algorithm development for dual thermal channel sensors e. An illustration of an advantage of geostationary satellites is shown by Sun et al. Globally, Hung et al. Atmospheric studies estimate aerosol optical depth an important influence on the radiation budget in America, Canada, China and Africa Liang et al.

A strength of the Meteorological application of remote sensing sensor is the compromise between regular image acquisition and reasonable spatial resolution, in comparison to other sensors that offer higher spatial resolution but lower temporal resolution e. Landsator higher temporal resolution but lower spatial resolution e.

ASTER is based on the NASA Terra satellite platform, but is fundamentally different from other sensors discussed in this review in that it is request only, with fees payable for data. Hence, data are only acquired if a specific request has been detailed and paid for, and therefore the historical data are limited and costly. This is a significant restriction, given the difficulties of ensuring suitable atmospheric and weather conditions for a specific future request, and obviously limits historical studies.

However, the 90 m resolution is high, only comparable with Landsat when considering the spatial scale, and ASTER has the potential for better temporal coverage, given the Terra satellite has a twice daily pass. ASTER images have been used for a number of studies. They were used to compare LST to urban biophysical descriptors such as impervious surface, green vegetation and soil in Indianapolis, USA through linear spectral mixture analysis and multiple regression models, with the results that impervious surfaces and hot objects were positively correlated with LST, whereas vegetation and cold objects were negatively correlated Lu and Weng, Land surface emissivity and radiometric temperatures have been compared with good agreement over desert in the USA and savannah in Africa Meteorological application of remote sensing et al.

 

 

meteorological application of remote sensing

 

Jan 14,  · Remote sensing is the examination or the gathering of information about a place from a distance. Such examination can occur with devices (e.g. - cameras) based on the ground, and/or sensors or cameras based on ships, aircraft, satellites, or other spacecraft. PRINCIPLES OF REMOTE SENSING Shefali Aggarwal Photogrammetry and Remote Sensing Division Indian Institute of Remote Sensing, Dehra Dun Abstract: Remote sensing is a technique to observe the earth surface or the atmosphere from out of space using satellites (space borne) or from the air using aircrafts (airborne). 4 Satellite Remote Sensing and GIS Applications in Agricultural Meteorology assessment and management of natural resources. In this regard, the Commission pointed out that long-term planning and training of technical personnel was a key ingredient in ensuring full success in the use of current.