Resultados de búsqueda - Sense data.

Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles por Caballero, Gabriel, Pezzola, Nestor Alejandro, Winschel, Cristina Ines, Casella, Alejandra An, Sanchez Angonova, Paolo Andres, Orden, Luciano, Berger, Katja, Verrelst, Jochem, Delegido, Jesús

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Reliabilitet i mätning av trädhöjd por Holmgren, Robert

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Climate change impacts livestock carrying capacity in East Africa por Duku, Confidence, Diro, Gulilat T., Demissie, Teferi, Solomon, Dawit

“…Existing approaches to livestock carrying capacity often rely on either localized ground surveys, which are insufficient for capturing the spatial variability and dynamic responses of rangelands at regional scales, or on process-based models, which require extensive calibration and are often unsuitable for data-scarce regions such as East Africa. Here, we address this gap by developing a novel machine learning-based approach that integrates remote sensing-derived biomass data with climate projections to estimate future changes in livestock carrying capacity and to diagnose their primary drivers. …”
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Development of a composite drought indicator for operational drought monitoring in the MENA Region por Bergaoui, Karim, Belhaj Fraj, Makram, Fragaszy, Stephen, Ghanim, A., Hamadin, O., Al‑Karablieh, E., Al‑Bakri, J., Fakih, M., Fayad, A., Comair, F., Yessef, M., Mansour, H. B., Belgrissi, H., Arsenault, K., Peters‑Lidard, C., Kumar, S., Hazra, A., Nie, W., Hayes, M., Svoboda, M., McDonnell, Rachael

“…The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. …”
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Monitoring changes in the cultivation of pigeonpea and groundnut in Malawi using time series satellite imagery for sustainable food systems por Gumma, Murali K., Tsusaka, T.W., Mohammed, I., Chavula, G., Ganga, R. N. V. P. R., Okori, Patrick, Ojiewo, Christopher Ochieng, Siambi, M., Varshney, Rajeev K., Whitbread, Anthony M.

“…Information on the spatial extent of these crops is useful for estimating food supply, understanding export potential, and planning policy changes as examples of various applications. Remote sensing analysis offers a number of efficient approaches to deliver spatial, reproducible data on land use and land cover (LULC) and changes therein. …”
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Advances in Amazonian Peatland Discrimination With Multi-Temporal PALSAR Refines Estimates of Peatland Distribution, C Stocks and Deforestation por Bourgeau-Chavez, L.L., Grelik, S.L., Battaglia, M.J., Leisman, D.J., Chimner, R.A., Hribljan, J.A., Lilleskov, E.A., Draper, F.C., Zutta, B.R., Hergoualc'h, Kristell, Bhomia, R.K., Lähteenoja, O.

“…There is a data gap in our current knowledge of the geospatial distribution, type and extent of C rich peatlands across the globe. …”
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Can a history of crop rotations improve the prediction of soil organic carbon in the Andes? Integrating machine learning multi-annual crop classification as a proxy of soil managem... por Bueno, M., Loayza, H., Ninanya, J., Rinza, J., Briceño, P., Silva, L., Mestanza, C., Otiniano, R., Kreuze, Jan F., Ramirez, D.

“…Crop rotation (CR) was incorporated into a modeling exercise using remote sensing data, fieldwork, and farmer surveys. A multi-year classification model with seven cropland classes was developed using data collected from 534 fields across 2022-2024, including 189 soil samples. …”
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Crop insurance: Ethiopia por Tadesse, Mulugeta, Tekle, W., Schmitter, Petra, Dembélé, Moctar

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Methods for the quantification of GHG emissions at the landscape level for developing countries in smallholder contexts por Milne, E, Neufeldt, Henry, Rosenstock, Todd S., Smalligan, M, Cerri, Carlos Eduardo, Malin, Daniella, Easter, M., Bernoux, Martial, Ogle, Stephen Michael, Casarim, F, Pearson, T, Bird, D.N., Steglish, E, Ostwald, M, Denef, K, Paustian, Keith

“…Landscape scale assessments of GHGs require a combination of ground sampling, use of data from census, remote sensing (RS) or other sources and modelling. …”
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Calibrated Models for Major Crops and Cropping System using Existing Datasets in Morocco and Uzbekistan por Devkota, Krishna, Devkota Wasti, Mina Kumari

“…Those input datasets for the model are derived from different sources, such as field experiments, household surveys, web-based data sources, remote sensing data, published literature, etc. …”
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Rapid emergency response mapping for the 2016 floods in Kelani river basin, Sri Lanka por Alahacoon, Niranga, Pani, Peejush, Matheswaran, Karthikeyan, Samansiri, Srimal, Amarnath, Giriraj

“…Paper presented at the 37th Asian Conference on Remote Sensing (ACRS): Promoting Spatial Data Infrastructure for Sustainable Economic Development, Colombo, Sri Lanka, 17-21 October 2016. …”
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Mapping Natural Resource (weather, soil, water, crop vegetation) to Identify Hot Spots in Uzbekistan por Devkota, Krishna, Atassi, Layal, Devkota Wasti, Mina Kumari

“…Considering the major parameters of climate, soil, and water, a hotspot/suitability map of Uzbekistan for wheat cultivation is developed. Remote sensing data such as Sentinel-2, Landsat-8, and MODIS satellites and the data sources such as FAO (soil salinity and soil organic carbon), ISRIC (soil parameters), and ESRI (10-m land use land cover) were used for mapping specific natural resources to identify hot-spots of climatic parameters. …”
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Mapping Natural Resource (weather, soil, water, crop vegetation) to Identify Hotspots in Morocco por Devkota, Krishna, Atassi, Layal, Devkota Wasti, Mina Kumari

“…Considering the major parameters of climate, soil, and water, a hotspot/suitability map of Morocco for wheat cultivation is developed. Remote sensing data such as Sentinel-2, Landsat-8, and MODIS satellites and the data sources such as FAO (soil salinity and soil organic carbon), ISRIC (soil parameters), and ESRI (10-m land use land cover) were used for mapping specific natural resources to identify hotspots of climatic parameters. …”
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Mapping Natural Resource (weather, soil, water, crop vegetation) to Identify Hotspots in Egypt por Devkota, Krishna, Atassi, Layal, Devkota Wasti, Mina Kumari

“…Considering the major parameters of climate, soil, and water, a hotspot/suitability map of Egypt for wheat cultivation is developed. Remote sensing data such as Sentinel-2, Landsat-8, and MODIS satellites and the data sources such as FAO (soil salinity and soil organic carbon), ISRIC (soil parameters), and ESRI (10-m land use land cover) were used for mapping specific natural resources to identify hot-spots of climatic parameters. …”
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RIICE tool for near real time monitoring of rice area, yield and climate change impacts in Mali and spillover countries por Mathieu, Renaud, Murugesan, Deiveegan, Maunahan, Aileen, Quicho, Emma, Sataphaty, Sushree, Dossou-Yovo, Elliott Ronald, Salif, Doumba, Akpoffo, Marius, Gatti, Luca

“…Reliable and seasonally updated information on the effective rice cultivated area, forecasted, harvested yield and climate change impacts are essential requirements for governments to support decision-making related to food security, management of natural resources, agricultural productivity, and insurance. The Remote Sensing based Information for Insurance and Crops in Emerging Economies (RIICE) was calibrated and validated in Mali to provide the government with reliable rice production data at harvest time and yield losses due to climate related stresses (flood and drought) to support planning in rice development and reduce the vulnerability of smallholder rice farmers by contributing to setting up affordable insurance schemes and scaling climate resilient innovations to the most affected people. …”
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How countries link REDD+ interventions to drivers in their readiness plans: implications for monitoring systems por Salvini, Giulia, Herold, Martin, Sy, Veronique de, Kissinger, G., Brockhaus, Maria, Skutsch, M.

“…The majority of the countries making this link have better driver data quality, in particularly those that present their data in ratio or ordinal terms. …”
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Project Completion Report of Index-Based Agriculture Insurance in Haor Area por Amarnath, Giriraj, Ahmed, Syed Moinuddin, Pavez, Ali T.

“…To implement Index Based Crop Insurance across the country the government needs to develop a number of high end technology and infrastructure to support them. Satellite remote sensing, real time data provider weather stations, digitalization of transaction methods, utilizing local authorities as structural distribution channel etc. are the most important initiatives that needs to be undertaken besides building stronger collaborations between respective departments and ministries of the government to get the most out this project.…”
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Quality Control of CyGNSS Reflectivity for Robust Spatiotemporal Detection of Tropical Wetlands por Arai, Hironori, Zribi, Mehrez, Oyoshi, Kei, Dassas, Karin, Huc, Mireille, Sobue, Shinichi, Thuy Le Toan

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Spatiotemporal characterization of droughts and vegetation response in Northwest Africa from 1981 to 2020 por Nguyen Quang Thi, Ajit Govind, Manh-Hung Le, Nguyen Thuy Linh, Tran Thi Mai Anh, Nguyen Khac Hai, Tuyen V. Ha

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Application of geographically weighted regression to improve grain yield prediction from unmanned aerial system imagery por Haghighattalab, Atena, Crain, Jared, Mondal, Suchismita, Rutkoski, Jessica, Singh, Ravi Prakash, Poland, Jesse

“…Phenological data are important ratings of the in‐season growth of crops, though this assessment is generally limited at both spatial and temporal levels during the crop cycle for large breeding nurseries. …”
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