INDO-FRENCH HIGH-RESOLUTION THERMAL INFRARED SPACE MISSION FOR EARTH NATURAL RESOURCES ASSESSMENT AND MONITORING – CONCEPT AND DEFINITION OF TRISHNA

<p><strong>Abstract.</strong> The Indian and French Space Agencies, ISRO and CNES, have conceptualized a space-borne Thermal Infrared Reflectance (TIR) mission, TRISHNA (Thermal infRared Imaging Satellite for High-resolution Natural Resource Assessment). The primary design drivers of TRISHNA are the monitoring of (i) terrestrial water stress and use, and of (ii) coastal and continental water. A suit of four TIR bands and six optical bands is planned. The TIR bands will be centred at 8.6&thinsp;&mu;m, 9.1&thinsp;&mu;m, 10.3&thinsp;&mu;m and 11.5&thinsp;&mu;m to provide noon-night global observations at 57m nadir resolution over land and coastal regions. The field of view (FOV) is &plusmn;34&deg; and the orbit of 761&thinsp;km altitude was designed to allow 3 sub-cycle acquisitions during the 8-day cycle. The optical bands correspond to blue, green, red, and NIR plus two SWIR bands at 1.38&thinsp;&mu;m and 1.61&thinsp;&mu;m. The green, red, NIR and the 1.61&thinsp;&mu;m SWIR bands will have better radiometry quality than those of AWiFS. ISRO and CNES will develop optical and TIR payloads, respectively. Assessing evapotranspiration and furthermore Gross and Net Primary Productivity (GPP and NPP) will in turn assist in quantifying water use in rainfed and irrigated agriculture, water stress and water use efficiency, with expected applications to agricultural drought and early warning, crop yield prediction, water allocation, implementation of water rights, crop insurance business and agro-advisories to farmers. The other scientific objectives of TRISHNA are also briefly described. TRISHNA instrument will fly aboard a ISRO spacecraft scheduled to be launched from 2024 for a minimum period of 5 years’ mission lifetime.</p>

Download Full-text

Unsustainability Syndrome—From Meteorological to Agricultural Drought in Arid and Semi-Arid Regions

Water ◽

10.3390/w12030838 ◽

2020 ◽

Vol 12 (3) ◽

pp. 838 ◽

Cited By ~ 2

Author(s):

Ali Torabi Haghighi ◽

Nizar Abou Zaki ◽

Pekka M. Rossi ◽

Roohollah Noori ◽

Ali Akbar Hekmatzadeh ◽

...

Keyword(s):

Water Resources ◽

Water Use ◽

Arid Regions ◽

Drought Index ◽

Agricultural Drought ◽

Irrigated Agriculture ◽

Fars Province ◽

Water Capacity ◽

Irrigated Area ◽

Semi Arid

Water is the most important resource for sustainable agriculture in arid and semi-arid regions, where agriculture is the mainstay for rural societies. By relating the water usage to renewable water resources, we define three stages from sustainable to unsustainable water resources: (1) sustainable, where water use is matched by renewable water capacity, ensuring sustainable water resources; (2) transitional, where water use occasionally exceeds renewable water capacity; and (3) unsustainable, with lack of water resources for agriculture, society, and the environment. Using available drought indicators (standardized precipitation index (SPI) and streamflow drought index (SDI)) and two new indices for agricultural drought (overall agricultural drought index (OADI) and agricultural drought index (ADI)), we evaluated these stages using the example of Fars province in southern Iran in the period 1977–2016. A hyper-arid climate prevailed for an average of 32% of the province’s spatio-temporal coverage during the study period. The area increased significantly from 30.6% in the first decade (1977–1986) to 44.4% in the last (2006–2015). The spatiotemporal distribution of meteorological drought showed no significant negative trends in annual precipitation during 1977–2016, but the occurrence of hydrological droughts increased significantly in the period 1997–2016. The expansion of irrigated area, with more than 60% of rainfed agriculture replaced by irrigated agriculture (especially between 1997 and 2006), exerted substantial pressure on surface water and groundwater resources. Together, climate change, reduced river flow, and significant declines in groundwater level in major aquifers led to unsustainable use of water resources, a considerable reduction in irrigated area, and unsustainability in agricultural production in the period 2006–2015. Analysis of causes and effects of meteorological, hydrological, and agricultural drought in the area identified three clear stages: before 1997 being sustainable, 1997–2006 being transitional, and after 2006 being unsustainable.

Download Full-text

Yield, Mineral Composition, Water Relations, and Water Use Efficiency of Grafted Mini-watermelon Plants Under Deficit Irrigation

HortScience ◽

10.21273/hortsci.43.3.730 ◽

2008 ◽

Vol 43 (3) ◽

pp. 730-736 ◽

Cited By ~ 109

Author(s):

Youssef Rouphael ◽

Mariateresa Cardarelli ◽

Giuseppe Colla ◽

Elvira Rea

Keyword(s):

Water Stress ◽

Plant Growth ◽

Water Use Efficiency ◽

Water Use ◽

Water Relations ◽

Fruit Quality ◽

Stress Conditions ◽

Irrigated Agriculture ◽

Marketable Yield ◽

Use Efficiency

Limited water supply in the Mediterranean region is a major problem in irrigated agriculture. Grafting may enhance drought resistance, plant water use efficiency, and plant growth. An experiment was conducted in two consecutive growing seasons to determine yield, plant growth, fruit quality, leaf gas exchange, water relations, macroelements content in fruits and leaves, and water use efficiency of mini-watermelon plants [Citrullus lanatus (Thunb.) Matsum. and Nakai cv. Ingrid], either ungrafted or grafted onto the commercial rootstock ‘PS 1313’ (Cucurbita maxima Duchesne × Cucurbita moschata Duchesne), under open field conditions. Irrigation treatments were 1.0, 0.75, and 0.5 evapotranspiration rates. In both years (2006 and 2007), marketable yield decreased linearly in response to an increase in water stress. When averaged over year and irrigation rate, the total and marketable yields were higher by 115% and 61% in grafted than in ungrafted plants, respectively. The fruit quality parameters of grafted mini-watermelons such as fruit dry matter and total soluble solids content were similar in comparison with those of ungrafted plants, whereas titratable acidity, K, and Mg concentrations improved significantly. In both grafting combinations, yield water use efficiency (WUEy) increased under water stress conditions with higher WUE values recorded in grafted than ungrafted plants. The concentration of N, K, and Mg in leaves was higher by 7.4%, 25.6%, and 38.8%, respectively, in grafted than in ungrafted plants. The net assimilation of CO2, stomatal conductance, relative water content, leaf, and osmotic potential decreased under water stress conditions. The sensitivity to water stress was similar between grafted and ungrafted plants, and the higher marketable yield from grafted plants was mainly the result of an improvement in nutritional status and higher CO2 assimilation and water uptake from the soil.

Download Full-text

Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission

Remote Sensing ◽

10.3390/rs11101251 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1251 ◽

Cited By ~ 6

Author(s):

Carlos Granero-Belinchon ◽

Aurelie Michel ◽

Jean-Pierre Lagouarde ◽

Jose A. Sobrino ◽

Xavier Briottet

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Infrared Imaging ◽

Thermal Infrared ◽

Resource Assessment ◽

Regression Kriging ◽

Scale Invariant ◽

Thermal Infrared Imaging ◽

Spatio Temporal ◽

Classification Index

This work is linked to the future Indian–French high spatio-temporal TRISHNA (Thermal infraRed Imaging Satellite for High-resolution natural resource Assessment) mission, which includes shortwave and thermal infrared bands, and is devoted amongst other things to the monitoring of urban heat island events. In this article, the performance of seven empirical thermal unmixing techniques applied on simulated TRISHNA satellite images of an urban scenario is studied across spatial resolutions. For this purpose, Top Of Atmosphere (TOA) images in the shortwave and Thermal InfraRed (TIR) ranges are constructed at different resolutions (20 m, 40 m, 60 m, 80 m, and 100 m) and according to TRISHNA specifications (spectral bands and sensor properties). These images are synthesized by correcting and undersampling DESIREX 2008 Airborne Hyperspectral Scanner (AHS) images of Madrid at 4 m resolution. This allows to compare the Land Surface Temperature (LST) retrieval of several unmixing techniques applied on different resolution images, as well as to characterize the evolution of the performance of each technique across resolutions. The seven unmixing techniques are: Disaggregation of radiometric surface Temperature (DisTrad), Thermal imagery sHARPening (TsHARP), Area-To-Point Regression Kriging (ATPRK), Adaptive Area-To-Point Regression Kriging (AATPRK), Urban Thermal Sharpener (HUTS), Multiple Linear Regressions (MLR), and two combinations of ground classification (index-based classification and K-means classification) with DisTrad. Studying these unmixing techniques across resolutions also allows to validate the scale invariance hypotheses on which the techniques hinge. Each thermal unmixing technique has been tested with several shortwave indices, in order to choose the best one. It is shown that (i) ATPRK outperforms the other compared techniques when characterizing the LST of Madrid, (ii) the unmixing performance of any technique is degraded when the coarse spatial resolution increases, (iii) the used shortwave index does not strongly influence the unmixing performance, and (iv) even if the scale-invariant hypotheses behind these techniques remain empirical, this does not affect the unmixing performances within this range of resolutions.

Download Full-text

Alfalfa (Medicago sativa L.) crop vigor and yield characterization using high-resolution aerial multispectral and thermal infrared imaging technique

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2021.105999 ◽

2021 ◽

Vol 182 ◽

pp. 105999

Author(s):

Abhilash K. Chandel ◽

Lav R. Khot ◽

Long-Xi Yu

Keyword(s):

High Resolution ◽

Medicago Sativa ◽

Infrared Imaging ◽

Imaging Technique ◽

Thermal Infrared ◽

Thermal Infrared Imaging ◽

Medicago Sativa L

Download Full-text

High-resolution satellite and airborne thermal infrared imaging of the 2006 eruption of Augustine Volcano: Chapter 22 in The 2006 eruption of Augustine Volcano, Alaska

Professional Paper ◽

10.3133/pp176922 ◽

2010 ◽

pp. 527-552

Author(s):

Rick L. Wessels ◽

Michelle L. Coombs ◽

David J. Schneider ◽

Jonathan Dehn ◽

Michael S. Ramsey

Keyword(s):

High Resolution ◽

Infrared Imaging ◽

Thermal Infrared ◽

Thermal Infrared Imaging ◽

2006 Eruption

Download Full-text

High-resolution Thermal Infrared Imaging of 3200 Phaethon

The Astronomical Journal ◽

10.3847/1538-3881/ab13a9 ◽

2019 ◽

Vol 157 (5) ◽

pp. 193 ◽

Cited By ~ 3

Author(s):

David Jewitt ◽

Daniel Asmus ◽

Bin Yang ◽

Jing Li

Keyword(s):

High Resolution ◽

Infrared Imaging ◽

Thermal Infrared ◽

Thermal Infrared Imaging

Download Full-text

Using Imaging Spectrometry to Study Changes in Crop Area in California’s Central Valley during Drought

Remote Sensing ◽

10.3390/rs10101556 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1556 ◽

Cited By ~ 4

Author(s):

Sarah Shivers ◽

Dar Roberts ◽

Joseph McFadden ◽

Christina Tague

Keyword(s):

Random Forest ◽

Water Use ◽

Agricultural Sector ◽

Infrared Imaging ◽

Central Valley ◽

Adaptation Strategy ◽

Random Forest Classifier ◽

Irrigated Agriculture ◽

Time Step ◽

Crop Area

In California, predicted climate warming increases the likelihood of extreme droughts. As irrigated agriculture accounts for 80% of the state’s managed water supply, the response of the agricultural sector will play a large role in future drought impacts. This study examined one drought adaptation strategy, changes in planting decisions, using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery from June 2013, 2014, and 2015 from the Central Valley of California. We used the random forest classifier to classify crops into categories of similar water use. Classification accuracy was assessed using the random forest out-of-bag accuracy, and an independently validated accuracy at both the pixel and field levels. These results were then compared to simulated Landsat Operational Land Imager (OLI) and simulated Sentinel-2B results. The classification was further analyzed for method portability and band importance. The resultant crop maps were used to analyze changes in crop area as one measure of agricultural adaptation in times of drought. The results showed overall field-level accuracies of 94.4% with AVIRIS, as opposed to 90.4% with Landsat OLI and 91.7% with Sentinel, indicating that hyperspectral imagery has the potential to identify crops by water-use group at a single time step at higher accuracies than multispectral sensors. Crop maps produced using the random forest classifier indicated that the total crop area decreased as the drought persisted from 2013 to 2015. Changes in area by crop type revealed that decisions regarding which crop to grow and which to fallow in times of drought were not driven by the average water requirements of crop groups, but rather showed possible linkages to crop value and/or crop permanence.

Download Full-text