Consulta: subjectFacets:"Satellite image"
Registros recuperados: 7
Data/hora: 10/06/2024 18:13:28

Remote Sensing-Driven Pacific Oyster (Crassostrea gigas) Growth Modeling to Inform Offshore Aquaculture Site Selection
Provedor de dados: 5
Autores: Palmer, Stephanie C. J.; Gernez, Pierre M.; Thomas, Yoann; Simis, Stefan; Miller, Peter I.; Glize, Philippe; Barillé, Laurent.
Aquaculture increasingly contributes to global seafood production, requiring new farm sites for continued growth. In France, oyster cultivation has conventionally taken place in the intertidal zone, where there is little or no further room for expansion. Despite interest in moving production further offshore, more information is needed regarding the biological potential for offshore oyster growth, including its spatial and temporal variability. This study shows the use of remotely-sensed chlorophyll-a and total suspended matter concentrations retrieved from the Medium Resolution Imaging Spectrometer (MERIS), and sea surface temperature from the Advanced Very High Resolution Radiometer (AVHRR), all validated using in situ matchup measurements, as input to...
Tipo: Text
Palavras-chave: Satellite image; Time series; Bivalve; Dynamic energy budget; Growth modeling; MERIS; AVHRR; Marine spatial planning.
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00605/71722/70185.pdf

Generating Global Crop Distribution Maps: From Census to Grid
Provedor de dados: 31
Autores: You,   Liangzhi; Wood,   Stanley; Wood-Sichra,   Ulrike.
In order to evaluate food security, technology potential and the environmental impacts of production in a strategic and regional context, it is critical to have reliable information on the spatial distribution and coincidence of people, agricultural production, and environmental services. This paper proposes a spatial allocation model for generating highly disaggregated, crop-specific production data by a triangulation of any and all relevant background and partial information. This includes national or sub-national crop production statistics, satellite data on land cover, maps of irrigated areas, biophysical crop suitability assessments, population density, secondary data on irrigation and rainfed production systems, cropping intensity, and crop prices....
Tipo: Conference Paper or Presentation
Palavras-chave: Global; Cross entropy; Satellite image; Spatial allocation; Agricultural production; Crop suitability; Crop Production/Industries; C6; Q15; Q24.
Ano: 2006
URL: http://purl.umn.edu/25737

Generating Plausible Crop Distribution and Performance Maps for Sub-Saharan Africa Using a Spatially Disaggregated Data Fusion and Optimization Approach
Provedor de dados: 31
Autores: You,   Liangzhi; Wood,   Stanley; Wood-Sichra,   Ulrike.
Agricultural production statistics reported at country or sub-national geopolitical scales are used in a wide range of economic analyses, and spatially explicit (geo-referenced) production data are increasingly needed to support improved approaches to the planning and implementation of agricultural development. However, it is extremely challenging to compile and maintain collections of sub-national crop production data, particularly for poorer regions of the world. Large gaps exist in our knowledge of the current geographic distribution and spatial patterns of crop performance, and these gaps are unlikely to be filled in the near future. Regardless, the spatial scale of many sub-national statistical reporting units remains too coarse to capture the...
Tipo: Working or Discussion Paper
Palavras-chave: Sub-Saharan Africa; Cross-entropy; Satellite image; Spatial allocation; Agricultural production; Crop suitability; Crop Production/Industries.
Ano: 2007
URL: http://purl.umn.edu/42374

GENERATING PLAUSIBLE CROP DISTRIBUTION MAPS FOR SUB-SAHARA AFRICA USING SPATIAL ALLOCATION MODEL
Provedor de dados: 31
Autores: You,   Liangzhi; Wood,   Stanley; Wood-Sichra,   Ulrike.
Spatial data, which are data that include the coordinates (either by latitude/longitude or by other addressing methods) on the surface of the earth, are essential for agricultural development. As fundamental parameters for agriculture policy research agricultural production statistics by geopolitical units such as country or sub-national entities have been used in many econometric analyses. However, collecting sub-national data is quite difficult in particular for developing countries. Even with great effort and only on regional scales, enormous data gaps exist and are unlikely to be filled. On the other hand, the spatial scale of even the subnational unit is relatively large for detailed spatial analysis. To fill these spatial data gaps we proposed a...
Tipo: Conference Paper or Presentation
Palavras-chave: Sub-Sahara Africa; Cross entropy; Satellite image; Spatial allocation; Agricultural production; Crop suitability; Crop Production/Industries; C60; Q15; Q24.
Ano: 2004
URL: http://purl.umn.edu/19965

การประยุกต์ใช้ภาพถ่ายดาวเทียมธีออสเพื่อประเมินเนื้อที่ปลูกข้าวนาปี ในจังหวัดเชียงรายและแม่ฮ่องสอน
Provedor de dados: 106
Autores: Piyapan Srikoom; Amornrat Intrmun; Nong-Nouch Pradit; Kingkaew Kunket.
In the Upper North of Thailand, the biggest wet season rice area is Chiang Rai province whereas the smallest is Mae Hong Son. In each year the rice area data from each organizes are different. Application of geographic information technologies by translating THEOS satellite image is one of channel for the classification of rice-growing areas of the two provinces. It can be use to predict the rice yield as well as use for the data base for rice research in Chiang Rai and also rice production for food security forecast of Mae Hong Son province. The implementation of Chiang Rai rice growing area is total 1,245,342 rais, with quite similar to the statistic data from the Bureau of Agricultural Economics in 2010 with amount of 1,261.022 rais, both different in...
Tipo: PhysicalObject
Palavras-chave: Wet season rice; Satellite image; THEOS satellite; GIS; Chiang Rai province; Mae Hong Son province; ข้าวนาปี; ภาพถ่ายดาวเทียม; ดาวเทียมธีออส; ระบบสารสนเทศทางภูมิศาสตร์; พื้นที่ปลูกข้าว; ผลผลิต; การพยากรณ์; จ.เชียงราย; จ.แม่ฮ่องสอน.
Ano: 2013
URL: http://anchan.lib.ku.ac.th/agnet/handle/001/5611

การประยุกต์ใช้ภาพถ่ายดาวเทียมธีออสเพื่อประเมินพื้นที่ปลูกข้าวนาปีในจังหวัดเชียงรายและแม่ฮ่องสอน
Provedor de dados: 106
Autores: Piyapan Srikoom; Amornrat Intrmun; Nong-Nouch Pradit; Kingkaew Kunket.
In the Upper North of Thailand, The biggest wet season rice area is in Chiang Rai province whereas the smallest is in Mae Hong Son. In each year, the rice area data from each organizes are different. Application of geographic information technologies by translating THEOS satellite image is an alternative method for rice area evaluation. It can be used to predict the rice yield in Chiang Rai as well as  for the data management for food security of Mae Hong Son province. The research found that Chiang Rai rice growing area covered the total of 1,245,342 rais, which was similar to the area reported by the Office of Agricultural Economics in 2010. Mae Hong Son Province covered the total of 113,842 rais, which had 17 percent higher than the area reported by the...
Tipo: PhysicalObject
Palavras-chave: Rice production; Satellite image; THEOS satellite; Chiang Rai province; Mae Hong Son province; Wet season; การผลิตข้าว; ภาพถ่ายดาวเทียม; ดาวเทียมธีออส; จ.เชียงราย; จังหวัดแม่ฮ่องสอน; ฤดูนาปี.
Ano: 2013
URL: http://anchan.lib.ku.ac.th/agnet/handle/001/5447

Temporal monitoring of corn (Zea mays L.) yield using grami model, satellite imagery, and climate data in a semi-arid area
Provedor de dados: 111
Autores: Asghari, Fatemeh; Sharif, Mohammad; Kheirkhah Zarkesh, Mirmasoud; Porhemmat, Jahangir.
Corn yield estimation constitutes a critical issue in agricultural management and food supply, especially in demographic pressure and climate change contexts. In light of precision and smart agriculture, this study aims to develop a diagnostic approach to temporally monitor and estimate corn yields using GRAMI (a model for simulating the growth and yield of grain crops), satellite images, and climate data at regional scale. The GRAMI-corn model is controlled by vegetation indices (VIs) derived from Landsat 8 satellite images and calibrated by climate data. The model performed and validated using information collected from twenty-five cornfields in a semiarid region in Ravansar, Iran. The average of under- or over-estimate yields was 919 kg ha−1. In...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Cor; Yield estimate; GRAMI; Climate data; Satellite image; Landsat 8.
Ano: 2022
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7241