Peer Review #3 of "Status of the undisturbed mangroves at Brunei Bay, East Malaysia: a preliminary assessment based on remote sensing and ground-truth observations (v0.1)"

Brunei Bay, which receives freshwater discharge from four major rivers, namely Limbang, Sundar, Weston and Menumbok, hosts a luxuriant mangrove cover in East Malaysia. However, this relatively undisturbed mangrove forest has been less scientifically explored, especially in terms of vegetation structure, ecosystem services and functioning, and land-use/cover changes. In the present study, mangrove areal extent together with species composition and distribution at the four notified estuaries was evaluated through remote sensing (Advanced Land Observation Satellite—ALOS) and ground-truth (Point-Centred Quarter Method—PCQM) observations. As of 2010, the total mangrove cover was found to be ca. 35,183.74 ha, of which Weston and Menumbok occupied more than two-folds (58%), followed by Sundar (27%) and Limbang (15%). The medium resolution ALOS data were efficient for mapping dominant mangrove species such asNypa fruticans,Rhizophora apiculata,Sonneratia caseolaris,S. albaandXylocarpus granatumin the vicinity (accuracy: 80%). The PCQM estimates found a higher basal area at Limbang and Menumbok—suggestive of more mature vegetation, compared to Sundar and Weston. Mangrove stand structural complexity (derived from the complexity index) was also high in the order of Limbang > Menumbok > Sundar > Weston and supporting the perspective of less/undisturbed vegetation at two former locations. Both remote sensing and ground-truth observations have complementarily represented the distribution ofSonneratiaspp. as pioneer vegetation at shallow river mouths,N. fruticansin the areas of strong freshwater discharge,R. apiculatain the areas of strong neritic incursion andX. granatumat interior/elevated grounds. The results from this study would be able to serve as strong baseline data for future mangrove investigations at Brunei Bay, including for monitoring and management purposes locally at present.

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Peer review report 2 On “Improving the performance of remote sensing models for capturing intra- and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data”

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2016.01.115 ◽

2016 ◽

Vol 217 ◽

pp. 62

Author(s):

Anonymous

Keyword(s):

Remote Sensing ◽

Peer Review ◽

Annual Variations

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Using remote sensing to assess tsunami-induced impacts on coastal forest ecosystems at the Andaman Sea coast of Thailand

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-729-2010 ◽

2010 ◽

Vol 10 (4) ◽

pp. 729-745 ◽

Cited By ~ 27

Author(s):

H. Roemer ◽

G. Kaiser ◽

H. Sterr ◽

R. Ludwig

Keyword(s):

Remote Sensing ◽

Forest Ecosystems ◽

Ground Truth ◽

Andaman Sea ◽

Coastal Forest ◽

Coastal Forests ◽

Change Detection Algorithms ◽

Damage Maps ◽

2004 Tsunami ◽

Sea Coast

Abstract. The December 2004 tsunami strongly impacted coastal ecosystems along the Andaman Sea coast of Thailand. In this paper tsunami-induced damage of five different coastal forest ecosystems at the Phang-Nga province coast is analysed with a remote sensing driven approach based on multi-date IKONOS imagery. Two change detection algorithms, change vector analysis (CVA) and direct multi-date classification (DMC), are applied and compared regarding their applicability to assess tsunami impacts. The analysis shows that DMC outperforms CVA in terms of accuracy (Kappa values for DMC ranging between 0.947 and 0.950 and between 0.610–0.730 for CVA respectively) and the degree of detail of the created change classes. Results from DMC show that mangroves were the worst damaged among the five forests, with a 55% of directly damaged forest in the study area, followed by casuarina forest and coconut plantation. Additionally this study points out the uncertainties in both methods which are mainly due to a lack of ground truth information for the time between the two acquisition dates of satellite images. The created damage maps help to better understand the way the tsunami impacted coastal forests and give basic information for estimating tsunami sensitivity of coastal forests.

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Groundwater Potential Zones in Relation to Catchment Condition in Orenburg, Russia

Information Technology and Nanotechnology ◽

10.18287/1613-0073-2019-2391-60-65 ◽

2019 ◽

pp. 60-65

Author(s):

K Choudhary ◽

M S Boori ◽

A Kupriyanov

Keyword(s):

Remote Sensing ◽

Land Use ◽

Remote Sensing Data ◽

Ground Truth ◽

Groundwater Potential ◽

Groundwater Potential Zone ◽

Potential Zone ◽

Ground Truth Data ◽

Groundwater Availability ◽

Sensing Data

The main objective of this study was to detect groundwater availability for agriculture in the Orenburg, Russia. Remote sensing data (RS) and geographic information system (GIS) were used to locate potential zones for groundwater in Orenburg. Diverse maps such as a base map, geomorphological, geological structural, lithology, drainage, slope, land use/cover and groundwater potential zone were prepared using the satellite remote sensing data, ground truth data, and secondary data. ArcGIS software was utilized to manipulate these data sets. The groundwater availability of the study was classified into different classes such as very high, high, moderate, low and very low based on its hydro-geomorphological conditions. The land use/cover map was prepared using a digital classification technique with the limited ground truth for mapping irrigated areas in the Orenburg, Russia.

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