scholarly journals FASAL concept in meeting the requirements of assessment and forecasting crop production affected by extreme weather events

MAUSAM ◽  
2021 ◽  
Vol 67 (1) ◽  
pp. 93-104
Author(s):  
JAI SINGH PARIHAR
Keyword(s):  
Remote Sensing ◽  
Crop Production ◽  
Remote Sensing Data ◽  
Extreme Weather ◽  
Crop Damage ◽  
Extreme Weather Events ◽  
Production Forecast ◽  
Sensing Data ◽  
Production Forecasting ◽  
Weather Events

The research in remote sensing application in India started first in agriculture way back in 1969. With the improvement in satellite sensors, data processing algorithms, models and computational power over time, this research culminated into development of operational projects of CAPE and FASAL, tackling an important issue of operationally providing pre-harvest crop production forecast to stakeholders. This review paper details the sequential developments in the use of remote sensing data for crop production forecasting. The scientific developments in the use of single and multi-temporal optical and microwave satellite images for crop identification and yield estimation in India have been reviewed.  The case studies on use of remote sensing data for crop assessment under extreme weather events are also presented. These include the assessment of crop damage due to extreme weather events of floods, drought, and hailstorm. Examples on use of remote sensing for crop damage assessment due to pest and diseases and forecasting their incidence using satellite derived weather parameters are reviewed.

scholarly journals Establishing an operational system for assessment and forecasting the impact of extreme weather events on crop production

MAUSAM ◽  
2021 ◽  
Vol 67 (1) ◽  
pp. 289-296
Author(s):  
SHIBENDU S. RAY ◽  
SURESH K. SINGH ◽  
NEETU . ◽  
S. MAMATHA
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Crop Production ◽  
Large Scale ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Wheat Crop ◽  
Production Forecasting ◽  
Weather Events ◽  
The Impact

Crop production forecasting is essential for various economic policy and decision making. There is a very successful operational programme in the country, called FASAL, which uses multiple approaches for pre-harvest production forecasting.  With the increase in the frequency of extreme events and their large-scale impact on agriculture, there is a strong need to use remote sensing technology for assessing the impact.  Various works have been done in this direction. This article provides three such case studies, where remote sensing along with other data have been used for assessment of flood inundation of rice crop post Phailin cyclone, period operational district/sub-district level drought assessment and understanding the impact of recent hailstorm/unseasonal rainfall on wheat crop. The case studies highlight the great scope of remote sensing data for assessment of the impact of extreme weather events on crop production.

scholarly journals Consequences of Climate Change Impacts and Incidences of Extreme Weather Events in Relation to Crop Production in Bhutan

2020 ◽  
Vol 12 (10) ◽  
pp. 4319 ◽  
Author(s):  
Ngawang Chhogyel ◽  
Lalit Kumar ◽  
Yadunath Bajgai
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Climate Change Impacts ◽  
Extreme Weather ◽  
Crop Damage ◽  
Extreme Weather Events ◽  
Cropping Pattern ◽  
The People ◽  
Weather Events

Being a country in the Himalayas, Bhutan is highly prone to the vagaries of weather events that affect agricultural production and the subsequent livelihood of the people. To identify the main issues that affect crop production and the decisions of farmers, a survey was conducted in three different agro-ecosystems in Bhutan. Our key findings indicate that farming and the decisions of farmers were largely affected by different climatic and non-climatic factors. These were in descending order of importance: irrigation availability > farm labour > crop seasonality > crop damage (climatic) > land holding > crop damage (wildlife) > crop damage (diseases and pests). The most important consequences of climate change impacts were the drying of irrigation sources (4.35) and crop losses due to weather events (4.10), whereas land fallowing, the occurrence of flood and soil erosion, weed pressure and changes in cropping pattern (with mean ratings of 2.53–3.03) experienced lesser consequences. The extreme weather events, such as untimely rains, drought and windstorms, were rated as the ‘most common’ to ‘common’ occurrences, thus inflicting a crop loss of 1–19%. These confirm our hearsay knowledge that extreme weather events have major consequences on irrigation water, which is said to be either drying or getting smaller in comparison to the past. Therefore, Bhutan must step up its on-ground farmer-support system towards improving the country’s food production, whilst embracing climate smart farm technologies for adapting to the impacts of change.

scholarly journals The role of agrarian science in transforming methods of using the Earth remote sensing data into publicly available technology

2021 ◽  
Author(s):  
V.I. Medennikov ◽  
Yu.A. Flerov
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Crop Production ◽  
Remote Sensing Data ◽  
Earth Remote Sensing ◽  
Conceptual Information ◽  
Sensing Data ◽  
The Earth ◽  
Available Technology

Improvement of the Earth remote sensing technology has led to an active implementation of its results in many areas of human activity with a significant expansion of both the number of industries using remote sensing data and the range of problems to be solved. Agriculture is perhaps the only industry where there is a symbiosis of this data obtained from both spacecraft, unmanned aerial vehicles, and ground vehicles with a significant intersection of information used in many sectors of economy, such as cartography, ecology, land management, logistics, construction, weather and climate, etc. Such an integrated use of heterogeneous information from various sources requires developing a digital decryption tool (standard) in the form of a unified geographic information system and a unified conceptual information model of crop production. From such a geographic information system, users could obtain unified digitized images, which would be ready for use and entering into their databases, whereas a unified conceptual information model of crop production, integrating all the knowledge of this industry, should turn into a kind of a publicly available technology. On the other hand, digitalization of the economy has significantly expanded the range of problems to be solved not only in production, but also in science, allowing for purely theoretical scientific research to actively penetrate into production. This also requires appropriate digital standards and managerial structures.

scholarly journals Detection of Changes in Terrestrial Ecosystems of Ukraine Using Remote Sensing Data

2020 ◽  
Vol 29 (1) ◽  
pp. 102-110 ◽  
Author(s):  
Vadym I. Lyalko ◽  
Inna F. Romanciuc ◽  
Lesia A. Yelistratova ◽  
Aleksandr A. Apostolov ◽  
Viktor M. Chekhniy
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Moisture Content ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Quantitative Information ◽  
Extreme Weather Events ◽  
Natural Soil ◽  
Sensing Data

In recent years, Ukraine has been affected by climate change. This has led to frequent extreme weather events (heavy / high rains, floods, droughts, squalls). As a result of droughts, desertification is one of the most dangerous and transient consequences of modern climate change. The research is devoted to the diagnostic assessment of the modern climate of Ukraine. Remote sensing data and instrumental observations of 30 weather stations of Ukraine were used. Temperature increase was registered in the study area by all stations, which significantly affected the level of precipitation. At the moment there is not enough moisture for the Earth’s surface. Precipitation in Ukraine is currently characterized by an uneven distribution. It leads to accelerated processes of soil degradation and it’s fertility loss. The aim of the study was to identify areas prone to desertification using satellite imagery and meteorological observations. Over the past 17 years (2000-2017), the average air temperature in Ukraine has increased by 1.5 ºC. Particularly anomalous warming has been recorded in recent years, starting in 2015. During the XXI century, a slight decrease in precipitation was observed in Ukraine. Both a decrease in precipitation and an increase in temperature may lead to a decrease in soil moisture levels. According to ground meteorological data, the tendency of dryness in Ukraine was confirmed. Lack of water leads to prompt manifestation of this process. Water indexes were used to estimate the moisture content of surface soils. It is possible to assess the susceptibility of the desert area to climate change. Relevant quantitative information on water availability in Ukraine is provided. Two water indices (Normalized Difference Infrared Index NDII and Ratio Drought Index RDI) have been taken estimate the moisture content. It can be estimated from the MODIS MOD13C2 product data obtained from the MODIS satellite sensor and used for regional research. The main conclusion of this study is to determine the changes in natural terrestrial ecosystems in Ukraine. This was shown on the basis of temperature and humidity. Such trends may lead to changes in the biodiversity of the territory and loss of natural soil properties.

scholarly journals A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 131 ◽  
Author(s):  
Md Shahinoor Rahman ◽  
Liping Di
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Damage Assessment ◽  
Remote Sensing Data ◽  
Crop Damage ◽  
Optical Remote Sensing ◽  
Crop Loss ◽  
Loss Assessment ◽  
Sensing Data ◽  
Crop Loss Assessment

This article reviews case studies which have used remote sensing data for different aspects of flood crop loss assessment. The review systematically finds a total of 62 empirical case studies from the past three decades. The number of case studies has recently been increased because of increased availability of remote sensing data. In the past, flood crop loss assessment was very generalized and time-intensive because of the dependency on the survey-based data collection. Remote sensing data availability makes rapid flood loss assessment possible. This study groups flood crop loss assessment approaches into three broad categories: flood-intensity-based approach, crop-condition-based approach, and a hybrid approach of the two. Flood crop damage assessment is more precise when both flood information and crop condition are incorporated in damage assessment models. This review discusses the strengths and weaknesses of different loss assessment approaches. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat are the dominant sources of optical remote sensing data for flood crop loss assessment. Remote-sensing-based vegetation indices (VIs) have significantly been utilized for crop damage assessments in recent years. Many case studies also relied on microwave remote sensing data, because of the inability of optical remote sensing to see through clouds. Recent free-of-charge availability of synthetic-aperture radar (SAR) data from Sentinel-1 will advance flood crop damage assessment. Data for the validation of loss assessment models are scarce. Recent advancements of data archiving and distribution through web technologies will be helpful for loss assessment and validation.

scholarly journals Quantifying the Response of German Forests to Drought Events via Satellite Imagery

2021 ◽  
Vol 13 (9) ◽  
pp. 1845
Author(s):  
Marius Philipp ◽  
Martin Wegmann ◽  
Carina Kübert-Flock
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Spatial Scales ◽  
Spectral Response ◽  
Remote Sensing Data ◽  
Extreme Weather Events ◽  
Ecosystem Functions ◽  
Drought Severity ◽  
Sensing Data

Forest systems provide crucial ecosystem functions to our environment, such as balancing carbon stocks and influencing the local, regional and global climate. A trend towards an increasing frequency of climate change induced extreme weather events, including drought, is hereby a major challenge for forest management. Within this context, the application of remote sensing data provides a powerful means for fast, operational and inexpensive investigations over large spatial scales and time. This study was dedicated to explore the potential of satellite data in combination with harmonic analyses for quantifying the vegetation response to drought events in German forests. The harmonic modelling method was compared with a z-score standardization approach and correlated against both, meteorological and topographical data. Optical satellite imagery from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used in combination with three commonly applied vegetation indices. Highest correlation scores based on the harmonic modelling technique were computed for the 6th harmonic degree. MODIS imagery in combination with the Normalized Difference Vegetation Index (NDVI) generated hereby best results for measuring spectral response to drought conditions. Strongest correlation between remote sensing data and meteorological measures were observed for soil moisture and the self-calibrated Palmer Drought Severity Index (scPDSI). Furthermore, forests regions over sandy soils with pine as the dominant tree type were identified to be particularly vulnerable to drought. In addition, topographical analyses suggested mitigated drought affects along hill slopes. While the proposed approaches provide valuable information about vegetation dynamics as a response to meteorological weather conditions, standardized in-situ measurements over larger spatial scales and related to drought quantification are required for further in-depth quality assessment of the used methods and data.

ASSESSMENT OF THE BIOMASS OF SPRING WHEAT SOWING

1970 ◽  
pp. 4-8
Author(s):  
I. M. Mikhaylenko ◽  
V. N. Timoshin ◽  
V. E. Veller
Keyword(s):  
Remote Sensing ◽  
Crop Production ◽  
Vegetation Indices ◽  
Morphological Structure ◽  
Remote Sensing Data ◽  
Estimation Algorithm ◽  
The State ◽  
Approximation Schemes ◽  
Sensing Data ◽  
Estimation Algorithms

The use of Earth remote sensing data (ERS) is a key information technology in modern crop production, as it allows you to assess the parameters of the state of crops of crops, the number of which can reach up to ten. Based on such assessments, managerial decisions are made aimed at obtaining specified final results. It is impossible to assess these parameters by the currently widely used vegetation indices, due to their scalar shape and dimensionless size. The paper develops a classical approach to the problem of assessing the parameters of the state of crops of crops, in which remote sensing data are considered as an indirect measurement of the estimated parameters. The difference of this article from previous works of a similar orientation is that crops with a more complex morphological structure are considered as an object of evaluation, which inevitably leads to a complication of the estimation algorithm. In addition, such an important feature of agricultural objects as their spatial distribution is considered here. To take it into account, a new kind of mathematical models is used in which spatial coordinates are introduced. Due to the significant complication of modeling and estimation algorithms based on such models, approximation schemes that are simpler in terms of software implementation are proposed. The basis of such schemes is the basic estimation algorithms, by which first estimates are formed for 20-30 elementary sowing areas, using which spatial variations of the estimates and reflection parameters are used on the used channels of the remote sensing system, and then linear spatial corrector parameters are constructed from these variations.

EFFECTIVE APPROACHES TO IDENTIFYING WEEDS USING DIGITAL TECHNOLOGIES

2020 ◽  
Author(s):  
E.P Tarik ◽  
◽  
P.A. Dmitriev ◽  
T.V. Varduny ◽  
D.P. Kupryushkin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Environmental Pollution ◽  
Crop Production ◽  
Spectral Characteristics ◽  
Digital Technologies ◽  
Remote Sensing Data ◽  
Precision Farming ◽  
Traditional Methods ◽  
Sensing Data

Traditional methods used in crop production lead to environmental pollution and producers incur unnecessary costs. The latest trends in the development of agriculture are directed towards precision farming. Tools for efficient and accurate farming are seen in the identification of remote sensing data and the use of spectral sensors that quickly determine the required indicators. For the development of this direction, it is necessary to accurately identify the spectral characteristics of weeds.

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