Satellite remote sensing in the policy sphere

2019 ◽  
pp. 133-147
Author(s):  
Nathalie Pettorelli
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Remote Sensing ◽  
Natural Capital ◽  
Remote Sensing Data ◽  
Resource Monitoring ◽  
Biodiversity Indicators ◽  
Sensing Technology ◽  
Essential Biodiversity Variables ◽  
Natural Resource Monitoring

This chapter focuses on the interface between satellite remote sensing and policy relevant to the management of natural resources, looking at ways for this technology to support decision making at the national to international scale. First, it briefly introduces (1) the main international conventions that are relevant to the management of natural resources and that could easily benefit from an increased consideration for satellite remote sensing technology, and (2) the main platforms facilitating the integration of satellite remote sensing data at the convention level. Second, it introduces the most popular conceptual frameworks that are being considered to help coordinate and structure natural resource monitoring efforts worldwide, namely the essential biodiversity variables framework, the biodiversity indicators framework, the ecosystem services framework, and the natural capital accounting framework. The final part highlights current challenges and lists a series of possible ways forward.

Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding

2017 ◽  
Vol 98 (11) ◽  
pp. 2397-2410 ◽  
Author(s):  
Justin L. Huntington ◽  
Katherine C. Hegewisch ◽  
Britta Daudert ◽  
Charles G. Morton ◽  
John T. Abatzoglou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Computing ◽  
Big Data ◽  
Natural Resource ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Resource Monitoring ◽  
Sensing Data ◽  
Process Understanding ◽  
Natural Resource Monitoring

Abstract The paucity of long-term observations, particularly in regions with heterogeneous climate and land cover, can hinder incorporating climate data at appropriate spatial scales for decision-making and scientific research. Numerous gridded climate, weather, and remote sensing products have been developed to address the needs of both land managers and scientists, in turn enhancing scientific knowledge and strengthening early-warning systems. However, these data remain largely inaccessible for a broader segment of users given the computational demands of big data. Climate Engine (http://ClimateEngine.org) is a web-based application that overcomes many computational barriers that users face by employing Google’s parallel cloud-computing platform, Google Earth Engine, to process, visualize, download, and share climate and remote sensing datasets in real time. The software application development and design of Climate Engine is briefly outlined to illustrate the potential for high-performance processing of big data using cloud computing. Second, several examples are presented to highlight a range of climate research and applications related to drought, fire, ecology, and agriculture that can be rapidly generated using Climate Engine. The ability to access climate and remote sensing data archives with on-demand parallel cloud computing has created vast opportunities for advanced natural resource monitoring and process understanding.

scholarly journals Mangrove Conservation Strategy in Bedono Village, Sayung District, Demak Regency Based on Remote Sensing Satellite Data

2019 ◽  
Vol 125 ◽  
pp. 02010
Author(s):  
Atmari ◽  
Denny Nugroho Sugianto ◽  
Fuad Muhammad
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Mangrove Ecosystem ◽  
Conservation Strategy ◽  
Government Agencies ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Mangrove Conservation

The mangrove ecosystem is an ecosystem unit in the form of a stretch containing biological natural resources dominated by trees that grow in coastal areas and river estuaries and is influenced by tides. The purpose of this study was to determine the vegetation in Bedono Village, Sayung District, Demak Regency by using remote sensing technology for conservation. Remote sensing technology has recently been used by government agencies or non-government agencies because it is considered more effective and efficient. Based on remote sensing data, the mangrove ecosystem in Bedono Village, Sayung Subdistrict, Demak Regency experienced an increase in the category of moderate and heavy mangroves in 2004-2009.

Future directions and challenges ahead

2019 ◽  
pp. 148-160
Author(s):  
Nathalie Pettorelli
Keyword(s):  
Remote Sensing ◽  
Environmental Management ◽  
Satellite Data ◽  
Satellite Remote Sensing ◽  
Multiple Scales ◽  
Remote Sensing Data ◽  
Future Directions ◽  
Sensing Technology ◽  
Ecosystem Accounting ◽  
Expected Benefits

This final chapter is dedicated to discussing possible new ways forward, aiming to highlight future opportunities and challenges likely to be connected with the continued development of remote sensing technology and associated algorithms to manipulate, visualise, and interpret satellite data. The first section discusses future directions in remote sensing, looking at upcoming sensors and expected benefits for the environmental management community; introducing the concept of big data analysis and its potential to drive a step-change in analytical processes; and detailing upcoming opportunities associated with the rise of nanosatellites and unmanned aerial vehicles. The second part of the chapter focuses on upcoming opportunities associated with the use of satellite remote sensing data for natural resource management, discussing how satellite data could support the development of rewilding as an alternative to traditional biodiversity conservation approaches; the assessment of collapse risk for ecosystems around the world; ecosystem accounting initiatives; and the enforcement of environmental policy at multiple scales. The third part details the challenges associated with building a consensus on how to prioritise satellite missions and data collection; and reflects on upcoming issues related to validation, capacity building, and scale. The chapter ends with a general conclusion that summarises some of the key principles that underpin the future success of satellite remote sensing in environmental management.

Identification of Potentially Unmanageable Ice Features

2017 ◽  
Author(s):  
Svetlana Shafrova ◽  
Dmitri Matskevitch ◽  
Curtis Holub ◽  
Ted Kokkinis
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Near Field ◽  
Remote Sensing Data ◽  
Data Interpretation ◽  
Dual Frequency ◽  
Sensing Technology ◽  
Field Reconnaissance ◽  
Remote Sensing Systems ◽  
Remote Sensing Methods

Satellite remote sensing technology plays an important role in ice monitoring and characterization in support of ice management operations for Arctic floating drilling that previously have been described by industry to include three stages: (1) far-field reconnaissance for potentially unmanageable ice features (2) mid-field verification of ice breakability and (3) near-field ice floe size reduction. The paper discusses the application of satellite remote sensing methods for identification of Potentially Unmanageable Ice Features (PUIF) as well as challenges associated with satellite data interpretation and feature tracking. Examples of PUIF identification using both publicly and commercially available satellite imagery and other remote sensing data collected during the Oden Arctic Technology Research Cruise 2015 (OATRC 2015) are presented and the challenges with the PUIF detection and monitoring are discussed. In addition, airborne remote sensing systems for PUIF identification, both existing (such as Electromagnetic Induction (EMI)) and under development (such as dual frequency radar, multi-band synthetic aperture radar), are discussed and their capabilities contrasted and compared to satellite-based methods. Furthermore, potential ways of optimally combining airborne and satellite remote sensing are proposed.

Monitoring land use change in the Lake Taupo catchment between 1975, 1990 and 2002 using satellite remote sensing data

2007 ◽  
pp. 17-22
Author(s):  
H. Lilienthal ◽  
A. Brauer ◽  
K. Betteridge ◽  
E. Schnug
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Native Vegetation ◽  
Lake Water Quality ◽  
Livestock Farming ◽  
Slow Decline

Conversion of native vegetation into farmed grassland in the Lake Taupo catchment commenced in the late 1950s. The lake's iconic value is being threatened by the slow decline in lake water quality that has become apparent since the 1970s. Keywords: satellite remote sensing, nitrate leaching, land use change, livestock farming, land management

Small-scale vegetation mapping of large territories: perspectives of using modern remote sensing and GIS technologies, the Indian experiences

1996 ◽  
pp. 51-54 ◽  
Author(s):  
N. V. M. Unni
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Forest Cover ◽  
Human Life ◽  
Remote Sensing Data ◽  
Modern World ◽  
Small Scale ◽  
Vegetation Map ◽  
Gis Technologies ◽  
Forest Cover Mapping

The recognition of versatile importance of vegetation for the human life resulted in the emergence of vegetation science and many its applications in the modern world. Hence a vegetation map should be versatile enough to provide the basis for these applications. Thus, a vegetation map should contain not only information on vegetation types and their derivatives but also the geospheric and climatic background. While the geospheric information could be obtained, mapped and generalized directly using satellite remote sensing, a computerized Geographic Information System can integrate it with meaningful vegetation information classes for large areas. Such aft approach was developed with respect to mapping forest vegetation in India at. 1 : 100 000 (1983) and is in progress now (forest cover mapping at 1 : 250 000). Several review works reporting the experimental and operational use of satellite remote sensing data in India were published in the last years (Unni, 1991, 1992, 1994).

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