Special Issue "Ecological Status and Change by Remote Sensing"

Guest Editor
Dr. Duccio Rocchini
Edmund Mach Foundation, IASMA Research and Innovation Centre, Environment and Natural Resources Area, GIS and Remote Sensing Unit, Via Mach 1, 38010 San Michele all'Adige (TN), Italy
Website: http://www.rocchini.net/
E-Mail:
Interests: ecological heterogeneity and biodiversity estimate by satellite imagery; change detection of spatial patterns and generating ecological processes; plant community ecology; relational database generation for remote sensing and field survey data management and statistical analysis; fuzzy set theory and land use mapping

Evaluating ecological patterns and processes is crucial for ecosystem conservation. In this view, remote sensing is a powerful tool for monitoring ecosystem status and change, involving several tasks like biodiversity estimate, landscape ecology, species distribution modeling.
The aim of this special issue is to publish straightforward research or review papers on the matter in order to stimulate further discussion on the potential of remote sensing in the ecological framework.

All manuscripts should be submitted to remotesensing@mdpi.org with a copy to the Guest Editor. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this Open Access journal is 300 CHF per accepted paper. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

• biodiversity
• biogeography
• conservation
• ecology
• ecological processes
• ecological gradients
• environment
• GIS
• natural dynamics
• multitemporl analysis
• remote sensing
• Satellite Imagery Time Series
• sensor comparison
• species distribution modelling
• species fiversity modelling
• complex terrain
• map reconstruction
• MODIS LST
• time series

Tentative Title: A Bi-temporal Change Detection Study Using Hyperspectral Data in a Thornbush Savanna of Central Namibia
Author: Jens Oldeland, University of Hamburg, Faculty of Biology, Ohnhorststr. 18, D-22609 Hamburg, Germany

Title: On the Suitability of Phenological Metrics to Map Plant Communities in Dry Savanna Ecosystems: A Case Study in the Kalahari of NE Namibia
Authors: C. Hüttich ¹ , U. Gessner ¹, M. Herold ², B. Strohbach ³, M. Schmidt ^1,4, M. Keil ⁴, S. Dech, S. ^1,4
Affiliations: ¹ Department of Remote Sensing, University of Wuerzburg, Wuerzburg, Germany; E-Mail: christian.huettich@uni-wuerzburg.de
² Friedrich-Schiller-University, ESA GOFC-GOLD Project Office, Jena, Germany
³ National Botanical Research Institute of Namibia, Windhoek, Namibia
⁴ German Remote Sensing Data Center, German Aerospace Center, Oberpfaffenhofen, Germany
Abstract: The evaluation of the recent status of biodiversity in Southern Africa’s Savannas is a major challenge for land management and conservation purposes. This paper presents an integrated concept for vegetation type mapping in a dry savanna ecosystem based on local scale in-situ botanical survey data with high resolution (Landsat) and coarse scale (MODIS) satellite time series data by applying a semi-automated training database generation procedure using object-oriented image segmentation techniques. A tree-based Random Forest classifier was used for mapping plant community associations in the Kalahari of NE Namibia based on inter-annual phenological metrics. The utilization of long-term inter-annual time temporal segments obtained the best classification accuracies (Kappa = 0.93) compared to classification sets based on seasonal feature sets. A relationship between annual classification accuracies and bi-annual precipitation rates could be outlined where increased error rates were achieved due to increased precipitation rates. The spectral and temporal variable importance was analysed and showed increased ranking positions for the Enhanced Vegetation Index (EVI) and the blue and middle Infrared band information indicating that soil reflectance information were crucial for an accurate spectral discrimination of Kalahari vegetation types. Inter-annual phenological metrics derived from MODIS time series proved to be applicable for mapping plant community pattern in dry semi-arid savanna ecosystems.
Keywords: land cover, plant communities, remote sensing, Kalahari, random forest classification, MODIS, EVI, time series

Tentative Title: Evaluating the Effects of Environmental Changes on the Gross Productivity of Italian Forests
Authors: Fabio Maselli ¹, Marco Moriondo ¹, Marta Chiesi ¹, Gherardo Chirici ², Nicola Puletti ³, Anna Barbati ⁴, Piermaria Corona ⁴
Affiliation: ¹ IBIMET-CNR, Via Madonna del Piano 10, 50019 Firenze, Italy; Email maselli@ibimet.cnr.it
² DISTAT, Università del Molise, Italy
³ DISTAF, Università di Firenze, Italy
⁴ DISAFRI, Università della Tuscia, Italy
Abstract: A ten-year data-set descriptive of Italian forest gross primary productivity (GPP) has been recently constructed by the application of C-Fix, a parametric model driven by remote sensing and ancillary data. This data-set is currently used to develop multivariate regression models which link the inter-year GPP variations of five forest types (white fir, beech, chestnut, deciduous and evergreen oaks) to seasonal values of temperature and precipitation. The five models obtained, which explain from 54 to 84% of the inter-year GPP variations, are then applied to predict the effects of expected environmental changes (+2°C and increased CO₂ concentration). The results show a variable responses of forest GPP to the simulated climate change, depending on the main ecosystem features. The effects of increasing CO₂ concentration are instead always positive and very similar to those given by a combination of the two environmental factors. These findings are analyzed with reference to previous studies on the subject, particularly concerning Mediterranean environments. The analysis indicates that the current statistical methodology yields plausible scenarios which can cast light on the important issue of forest carbon pool variations under expected global changes.
Keywords: Mediterranean forest, GPP, C-Fix, environmental change

Submitted Papers

Title: Remote Sensing and Mapping of Tamarisk along the Colorado River, USA: A Comparative Use of Hyperion, Thematic Mapper and QuickBird data
Authors: Gregory A. Carter^1,2 , Kelly L. Lucas¹, Gabriel A. Blossom¹, Cheryl L. Lassitter³, Dan M. Holiday^1,3, David S. Mooneyhan¹, Danielle R. Fastring⁴, Tracy R. Holcombe⁵ and Jerry A. Griffith²
Affiliations: ¹Gulf Coast Geospatial Center, University of Southern Mississippi, Gulfport, MS, 39501, USA
²Department of Geography and Geology, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
³Department of Coastal Sciences, University of Southern Mississippi, Ocean Springs, MS, 39564, USA
⁴Department of Community Health Sciences, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
⁵USGS Fort Collins Science Center, Fort Collins, CO, 80526, USA
Corresponding author: Gregory A. Carter. Email greg.carter@gcgcusm.org, telephone 228.276.1722
Abstract: Tamarisk (Tamarix spp., saltcedar) is a well-known invasive phreatophyte introduced from Asia to North America in the 1800s. This report compares the efficacy of Landsat 5 Thematic Mapper (TM5), QuickBird (QB) and EO-1 Hyperion data in discriminating tamarisk populations near De Beque, Colorado, USA. As a result of highly correlated reflectance among the spectral bands provided by each sensor, relatively standard image analysis methods were employed. Multispectral data at high spatial resolution (QB, 2.5 m Ground Spatial Distance or GSD) proved more effective in tamarisk delineation than either multispectral (TM5) or hyperspectral (Hyperion) data at moderate spatial resolution (30 m GSD).
Keywords: invasive species; Tamarisk; hyperion; thematic napper; QuickBird; image resolution

Title: Towards a Framework for the Use of Remote Sensing for Long-Term Ecological Monitoring: The Doñana Experience
Author: Ricardo Díaz-Delgado
Affiliation: Remote Sensing and GIS Lab Estación Biológica de Doñana-CSIC Sevilla, Spain; E-Mail: rdiaz@ebd.csic.es
Abstract: The manuscript reviews the use of remote sensing as a valid tool for long term ecological monitoring at landscape scale. The many different uses of remote images provide synoptic, repetitive and quantitative measurements of crucial ecological parameters related to habitat, land use and cover, biodiversity, landscape metrics, energy fluxes, primary productivity, alien species, water quality, etc. However, spatial, spectral and temporal resolution of remote sensing sources constraint the use and applicability of this information source for comparability of long term ecological monitoring indicators. This paper reviews the various approaches dealing with the use of remote sensing as a reliable tool for long term monitoring of ecological data, especially in protected areas with special emphasis on the successful experience on Doñana Natural Space.