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Remote Sensing
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Remote Sensing on Earth Observation and Ecosystem Services
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Remote Sensing on Earth Observation and Ecosystem Services

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 April 2011) | Viewed by 19553

Special Issue Editors

Dr. Jan De Leeuw

E-Mail Website
Guest Editor
ICRAF World Agroforestry Centre, United Nations Avenue, Gigiri, PO Box 30677, Nairobi 00100, Kenya
Interests: mapping of environment and agriculture; drought early warning systems; remote sensing for index-based insurance; participatory mapping; remote sensing and impact assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Steffen Fritz

E-Mail Website
Guest Editor
International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria
Interests: remote sensing; cropland; crowdsourcing; mapping uncertainty; climate change; agricultural monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The recognition that resources and functions supplied by nature benefit mankind recently entered the mainstream of social and economic thought and associated policies. Ecosystem services include the provisioning of products like food and water (examples of provisioning services), the regulation of our environment; for example climate through sequestration of carbon by the oceans, terrestrial vegetation and soils or the control of pests and diseases (which are regulating services), the maintenance of the capacity to support productivity, for example healthy soils that support sustainable agricultural production (an example of a supporting service) and cultural and recreational benefits (these are cultural services).

A first attempt to quantify the value of ecosystem services provided by nature (US$ 33 trillion) was made by Constanza (1995). More recently the 2004 Millennium Ecosystem Assessment popularized the concept and a variety of initiatives have been developed since then to sustain this natural wealth, including proper accounting for ecosystem services and policies to restore, strengthen or sustain the delivery of these. In addition Carpenter summarized a research agenda to understanding ecosystem services. Yet, many ecosystem services are under pressure from human activities due to growth at the expense of the benefits provided by nature.

Spatial information plays an increasingly important role to locate, value and price ecosystem services, as the availability of ecosystem services and the possibilities to manage their delivery vary geographically. Remote sensing and associated spatial modeling techniques hold particular potential for efficient accounting over large areas and the development and implementation of policies and interventions aimed at managing, conserving or restoring ecosystem services. Increasingly also, financial incentives, such as payments for ecosystem services (PES), are used to stimulate land and water uses compatible with delivery of ecosystem services, and spatial information is used to support the arrangements between beneficiaries and providers of ecosystem services.

This special issue of Remote Sensing solicits papers that present innovative remote sensing applications and related spatial modeling techniques to support the accounting and mainstreaming of ecosystem services in land and water management and the development and implementation of policies and arrangements aimed at their conservation and sustainable use.

Dr. Jan de Leeuw
Dr. Steffen Fritz
Guest Editors

Keywords

  • ecosystem services; PES
  • remote sensing; earth observation
  • mapping; assessment
  • valuation
  • accounting
  • natural capital
  • governance
  • decision making

Published Papers (2 papers)

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3397 KiB  
Article
Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners
by Sung-Eun Jung, Doo-Ahn Kwak, Taejin Park, Woo-Kyun Lee and Seongjin Yoo
Remote Sens. 2011, 3(11), 2346-2363; https://doi.org/10.3390/rs3112346 - 28 Oct 2011
Cited by 70 | Viewed by 9219
Abstract
In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial [...] Read more.
In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial laser scanner (TLS). These ALS- and TLS-derived tree parameters were compared because TLS has been introduced as an instrument to measure objects more precisely. ALS-estimated TH was extracted from the highest value within a crown boundary delineated with the crown height model (CHM). The ALS-derived CBH of individual trees was estimated by k-means clustering method using the ALS data within the boundary. The ALS-derived CA was calculated simply with the crown boundary, after which CV was computed automatically using the crown geometric volume (CGV). On the other hand, all TLS-derived parameters were detected manually and precisely except the TLS-derived CGV. As a result, the ALS-extracted TH, CA, and CGV values were underestimated whereas CBH was overestimated when compared with the TLS-derived parameters. The coefficients of determination (R2) from the regression analysis between the ALS and TLS estimations were approximately 0.94, 0.75, 0.69 and 0.58, and root mean square errors (RMSEs) were approximately 0.0184 m, 0.4929 m, 2.3216 m2 and 13.2087 m3 for TH, CBH, CA and CGV, respectively. Thereby, the error rate decreased to 0.0089, 0.0727 and 0.0875 for TH, CA and CGV via the combination of ALS and TLS data. Full article
(This article belongs to the Special Issue Remote Sensing on Earth Observation and Ecosystem Services)
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670 KiB  
Article
Consequences of Uncertainty in Global-Scale Land Cover Maps for Mapping Ecosystem Functions: An Analysis of Pollination Efficiency
by Catharina J.E. Schulp and Rob Alkemade
Remote Sens. 2011, 3(9), 2057-2075; https://doi.org/10.3390/rs3092057 - 16 Sep 2011
Cited by 45 | Viewed by 9696
Abstract
Mapping ecosystem services (ESs) is an important tool for providing the quantitative information necessary for the optimal use and protection of ecosystems and biodiversity. A common mapping approach is to apply established empirical relationships to ecosystem property maps. Often, ecosystem properties that provide [...] Read more.
Mapping ecosystem services (ESs) is an important tool for providing the quantitative information necessary for the optimal use and protection of ecosystems and biodiversity. A common mapping approach is to apply established empirical relationships to ecosystem property maps. Often, ecosystem properties that provide services to humanity are strongly related to the land use and land cover, where the spatial allocation of the land cover in the landscape is especially important. Land use and land cover maps are, therefore, essential for ES mapping. However, insight into the uncertainties in land cover maps and how these propagate into ES maps is lacking. To analyze the effects of these uncertainties, we mapped pollination efficiency as an example of an ecosystem function, using two continental-scale land cover maps and two global-scale land cover maps. We compared the outputs with maps based on a detailed national-scale map. The ecosystem properties and functions could be mapped using the GLOBCOVER map with a reasonable to good accuracy. In homogeneous landscapes, an even coarser resolution map would suffice. For mapping ESs that depend on the spatial allocation of land cover in the landscape, a classification of satellite images using fractional land cover or mosaic classes is an asset. Full article
(This article belongs to the Special Issue Remote Sensing on Earth Observation and Ecosystem Services)
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