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What’s (Not) on the Map: Landscape Features from Participatory Sketch Mapping Differ from Local Categories Used in Language

Peer-reviewed publication
Novembro, 2017
Global

Participatory mapping of local land use as the basis for planning and decision-making has become widespread around the globe. However, still relatively little is known about the conceptual underpinnings of geographic information produced through participatory mapping in given cultural and linguistic settings. In this paper, we therefore address the seemingly simple question of what is (not) represented on maps through an exploratory case study comparing land use categories participants represented on sketch maps with categories elicited through more language-focused ethnographic fieldwork.

Classifying and Mapping Periurban Areas of Rapidly Growing Medium-Sized Sub-Saharan African Cities: A Multi-Method Approach Applied to Tamale, Ghana

Peer-reviewed publication
Fevereiro, 2019
África
Gana

Periurban areas of growing cities in developing countries have been conceptualised as highly dynamic landscapes characterised by a mixture of socioeconomic structures, land uses and functions. While the body of conceptual literature on periurban areas has significantly increased over the past two decades, methods for operationalising these multi-dimensional concepts are rather limited. Yet, information about the location and areal extent of periurban areas is needed for integrated planning in the urban–rural interface.

Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform

Peer-reviewed publication
Setembro, 2020
Indonésia

Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover.

Predicted Maps for Soil Organic Matter Evaluation: The Case of Abruzzo Region (Italy)

Peer-reviewed publication
Setembro, 2020
Estados Unidos
Itália

Organic matter, an important component of healthy soils, may be used as an indicator in sustainability assessments. Managing soil carbon storage can foster agricultural productivity and environmental quality, reducing the severity and costs of natural phenomena. Thus, accurately estimating the spatial variability of soil organic matter (SOM) is crucial for sustainable soil management when planning agro-environmental measures at the regional level. SOM variability is very large in Italy, and soil organic carbon (SOC) surveys considering such variability are difficult and onerous.

Events

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Earth Observations for Humanitarian Applications

05 Junho 2024 - 19 Junho 2024

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Earth Observations for Humanitarian Applications. Refugees, internally displaced people (IDPs), and other displaced populations are made more vulnerable to climate change impacts due to their socio-political marginalization. This three-part, intermediate training presents concrete strategies for mapping localized climate conditions with risks faced by refugee and IDP communities around the world.

The training will focus on flood risk assessments and specific challenges for assessing flood risk in refugee and IDP camps; gauging long-term heat stress in refugee camps and the challenges with decision making surrounding heat risk; and monitoring drought effects on agricultural landscapes in refugee settings using Earth observations (EO) to explore the correlations between anomalies in crop productivity and weather-based factors

 

Assessing the Impacts of Fires on Watershed Health

05 Julho 2023 - 12 Julho 2023

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Assessing the Impacts of Fires on Watershed Health. This advanced-level, three-part training will focus on using remote sensing observations for monitoring post-fire impacts on watershed health. Specifically, this training will highlight uses of NASA Earth observations (EO) for pre-fire land cover mapping, watershed delineation and stream mapping, post-fire burn severity mapping, and pre- and post-fire riverine and freshwater water quality.

Fundamentals of Machine Learning for Earth Science

19 Abril 2023 - 03 Maio 2023

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new online introductory webinar series: Fundamentals of Machine Learning for Earth Science. This three-part training, presented in English and Spanish, is open to the public and will provide attendees an overview of machine learning in regards to Earth Science, and how to apply these algorithms and techniques to remote sensing data in a meaningful way. Attendees will also be provided with end-to-end case study examples for generating a simple random forest model for land cover classification from optical remote sensing. We will also present additional case studies to apply the presented workflows using additional NASA data.