Satellite imaging coral reef resilience at regional scale. A case-study from Saudi Arabia

We propose a framework for spatially estimating a proxy for coral reef resilience using remote sensing. Data spanning large areas of coral reef habitat were obtained using the commercial QuickBird satellite, and freely available imagery (NASA, Google Earth). Principles of coral reef ecology, field observation, and remote observations, were combined to devise mapped indices. These capture important and accessible components of coral reef resilience. Indices are divided between factors known to stress corals, and factors incorporating properties of the reef landscape that resist stress or promote coral growth. The first-basis for a remote sensed resilience index (RSRI), an estimate of expected reef resilience, is proposed. Developed for the Red Sea, the framework of our analysis is flexible and with minimal adaptation, could be extended to other reef regions. We aim to stimulate discussion as to use of remote sensing to do more than simply deliver habitat maps of coral reefs.     

Aerial photosieving of exposed gravel bars for the rapid calibration of airborne grain size maps

In recent years, fluvial remote sensing has seen considerable progress in terms of methods capable of system scale characterisation of river catchments. One key development is automated grain size mapping. It has been shown that high resolution aerial photography can be used to automatically produce grain size maps over entire rivers. However, current aerial grain size mapping procedures all require field calibration data. The collection of such data can be costly and problematic in the case of remote areas. This paper presents a method developed to remove the need for field based calibration data. Called ‘aerial photosieving’, this method consists of using the same very high resolution aerial imagery intended for grain size map production to visually measure particle sizes on‐screen in order to provide calibration data. The paper presents a rigorous comparison of field‐based photosieving calibration data and aerial photosieving calibration data. Statistical tests are used to demonstrate that aerial photosieving gives similar results when compared with field‐based data with only a slight systematic overprediction. The new aerial photosieving method therefore simplifies the overall procedure required for the production of grain size maps and thus improves the cost‐effectiveness and potential availability of this new fluvial remote sensing technology. Copyright © 2010 John Wiley &Sons, Ltd.     

Remote sensing of coral reefs and their physical environment

There has been a vast improvement in access to remotely sensed data in just a few recent years. This revolution of information is the result of heavy investment in new technology by governments and industry, rapid developments in computing power and storage, and easy dissemination of data over the internet. Today, remotely sensed data are available to virtually anyone with a desktop computer. Here, we review the status of one of the most popular areas of marine remote sensing research: coral reefs. Previous reviews have focused on the ability of remote sensing to map the structure and habitat composition of coral reefs, but have neglected to consider the physical environment in which reefs occur. We provide a holistic review of what can, might, and cannot be mapped using remote sensing at this time. We cover aspects of reef structure and health but also discuss the diversity of physical environmental data such as temperature, winds, solar radiation and water quality. There have been numerous recent advances in the remote sensing of reefs and we hope that this paper enhances awareness of the diverse data sources available, and helps practitioners identify realistic objectives for remote sensing in coral reef areas.     

湖泊渔业可持续发展的生态学基础及一个范例

从渔业与环境兼顾的角度出发作者认为湖泊渔业可持续发展的生态学理论基础是渔业生态学和渔业湖沼学. 前者是一门较为成熟的学科研究渔业对象的种群生态学渔产潜力最佳放流密度和规格以及科学的捕捞策略等. 后者研究渔业对湖泊生态系统生物多样性和水质的影响并确定最佳的渔业规模和渔业方式但尚未提出令人满意的理论和完善的实验方法今后应予充分重视. 长江中下游草型湖泊因为其优良的水资源和丰富的生物资源而成为我国内陆水体发展优质高效渔业的重要基地. 以湖北一个浅水草型扁担塘渔业实践为例作者着重强调生态学管理的如下方面1) 沉水植被是草型湖泊优质高效渔业持续发展的基础必须在合理利用的同时加以保护优化甚至重建使生物量和覆盖率保持和达到一定水平. 2) 食物链网的基础环节是渔业对象生长和繁衍的物质基础, 必须进行培育保护以提高其生产力从而为提高渔业产量打下物质基础. 3) 合理放养与捕捞策略是湖泊渔业生态系统良性循环的可靠保证应使高价值的种群规模保持较大水平的输出.     

Estimating snow distribution over a large area and its application for water resources

The spatial and temporal distribution of the snow water equivalent (SWE), snow density and snow depth were estimated by a method combining remote sensing technology and degree‐day techniques over a study area of 370 000 km². The advantages of this simulation model are its simplicity and the availability of degree‐day parameters, which can be successively evaluated by referring to snow area maps created from satellite images. This simulation worked very well for estimating SWE and helped to separate the areas of thin snow cover from heavier snowfall. However, shallow snow in warm regions led to some misjudgments in the snow area maps because of the time lag between when the satellite image was acquired and the simulation itself. Vulnerable areas, where a large variation in the amount of snow affects people's life, could be identified from the differences between heavy and light snow years. This vulnerability stems from a predicted lack of irrigation water for rice production caused by future climate change. The model developed in this study has the potential to contribute to water management activities and decision‐making processes when considering necessary adaptations to future climate change. Copyright © 2007 John Wiley & Sons, Ltd.     

Predicting global landslide spatiotemporal distribution： Integrating landslide susceptibility zoning techniques and real-time satellite rainfall estimates

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of sufficient ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing a preliminary real-time prediction system to identify where rainfall-triggered landslides will occur is proposed by combining two necessary components： surface landslide susceptibility and a real-time space-based rainfall analysis system （http：//trmm.gsfc.nasa.gov）. First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics （digital elevation topography, slope, soil types, soil texture, land cover classification, etc.） using a GIS weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide hazards at areas with high susceptibility. A major outcome of this work is the availability for the first time of a global assessment of landslide hazards, which is only possible because of the utilization of global satellite remote sensing products. This preliminary system can be updated continuously using the new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and mitigation activities across the world.     

Mapping Potential Groundwater‐Dependent Ecosystems for Sustainable Management

Ecosystems which rely on either the surface expression or subsurface presence of groundwater are known as groundwater‐dependent ecosystems (GDEs). A comprehensive inventory of GDE locations at an appropriate management scale is a necessary first‐step for sustainable management of supporting aquifers; however, this information is unavailable for most areas of concern. To address this gap, this study created a two‐step algorithm which analyzed existing geospatial and remote sensing data to identify potential GDEs at both state/province and aquifer/basin scales. At the state/province scale, a geospatial information system (GIS) database was constructed for Texas, including climate, topography, hydrology, and ecology data. From these data, a GDE index was calculated, which combined vegetative and hydrological indicators. The results indicated that central Texas, particularly the Edwards Aquifer region, had highest potential to host GDEs. Next, an aquifer/basin scale remote sensing‐based algorithm was created to provide more detailed maps of GDEs in the Edwards Aquifer region. This algorithm used Landsat ETM+ and MODIS images to track the changes of NDVI for each vegetation pixel. The NDVI dynamics were used to identify the vegetation with high potential to use groundwater—such plants remain high NDVI during extended dry periods and also exhibit low seasonal and inter‐annual NDVI changes between dry and wet seasons/years. The results indicated that 8% of natural vegetation was very likely using groundwater. Of the potential GDEs identified, 75% were located on shallow soil averaging 45 cm in depth. The dominant GDE species were live oak, ashe juniper, and mesquite.     

Spatial assessment of fishing effort around European marine reserves: implications for successful fisheries management

We examined the spatial dynamic of artisanal fishing fleets around five European marine protected areas (MPAs) to derive general implications for the evaluation of MPAs as fisheries management tools. The coastal MPAs studied were located off France, Malta and Spain and presented a variety of spatial designs and processes of establishment. We developed a standardized methodology to define factors influencing effort allocation and to produce fishing effort maps by merging GIS with geostatistical modelling techniques. Results revealed that in most cases the factors “distance to the no-take”, “water depth”, and “distance to the port” had a significant influence on effort allocation by the fishing fleets. Overall, we found local concentration of fishing effort around the MPA borders. Thus, neglecting the pattern of fishing effort distribution in evaluating MPA benefits, such as spillover of biomass, could hamper sound interpretation of MPAs as fisheries management tools.     

中国遥感的回顾与展望

概要地回顾了我国自上世纪50年代以来的遥感研究，主要讨论近二十年来的遥感发展进程，并对新世纪我国遥感发展作出展望。     

Potential application of remote sensing systems to the African rift system

Interdisciplinary interpretation of satellite and geologic-geophysical data can be applied to East Africa as a cost-effective means of regional tectonic evaluation. All available data sources: geologic and geophysical maps and remote sensing images should be used. Remote sensing methods are very efficient for the “synoptic overlook” necessary to pinpoint areas for more detailed investigation.The use of satellite imagery is a way of applying and testing structural frameworks for mineral potential as surface reflections of deep tectonic features can be recognized. Mineralization can be correlated with tectonic lineaments that are probably related to persistent discontinuities in the upper mantle. The outlining of these discontinuities would be of value in the search for the understanding of riftogenesis and in the search for mineralization.This paper is a review of such work with a specific example from Canada, and how the approach can be applied to Africa for continuing research on recent crustal movements.     

Mapping water quality and substrate cover in optically complex coastal and reef waters: an integrated approach

Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs.     

On Creating Global Gridded Terrestrial Water Budget Estimates from Satellite Remote Sensing

The increasing availability and reliability of satellite remote sensing products [e.g., precipitation (P), evapotranspiration (ET), and the total water storage change (TWSC)] make it feasible to estimate the global terrestrial water budget at fine spatial resolution. In this study, we start from a reference water budget dataset that combines all available data sources, including satellite remote sensing, land surface model (LSM) and reanalysis, and investigate the roles of different non-satellite remote sensing products in closing the terrestrial water budget through a sensitivity analysis by removing/replacing one or more categories of products during the budget estimation. We also study the differences made by various satellite products for the same budget variable. We find that the gradual removal of non-satellite data sources will generally worsen the closure errors in the budget estimates, and remote sensing retrievals of P, ET, and TWSC together with runoff (R) from LSM give the worst closure errors. The gauge-corrected satellite precipitation helps to improve the budget closure (4.2–9 % non-closure errors of annual mean precipitation) against using the non-gauge-corrected precipitation (7.6–10.4 % non-closure errors). At last, a data assimilation technique, the constrained Kalman filter, is applied to enforce the water balance, and it is found that the satellite remote sensing products, though with worst closure, yield comparable budget estimates in the constrained system to the reference data. Overall, this study provides a first comparison between the water budget closure using the satellite remote sensing products and a full combination of remote sensing, LSM, and reanalysis products on a quasi-global basis. This study showcases the capability and potential of the satellite remote sensing in closing the terrestrial water budget at fine spatial resolution if properly constrained.     

Radar hydrology: rainfall estimation

Radar observations of rainfall and their use in hydrologic research provide the focus for the paper. Radar-rainfall products are crucial for input to runoff and flood prediction models, validation of satellite remote sensing algorithms, and for statistical characterization of extreme rainfall frequency. In this context we discuss the issues of radar-rainfall product development, and the theoretical and practical requirements of validating radar-rainfall maps and new radar technologies. We discuss a framework for reflectivity based rainfall estimation, including estimation of uncertainty of radar-rainfall estimates. Validation of radar-rainfall products is a major challenge for broad utilization of these products in hydrologic applications. In the discussion of radar-rainfall prediction we focus on orographically induced extreme rainfall and flooding, discuss the issues of detection, statistical sample size, and scale effects. We conclude the paper with a set of recommendations for research priorities and experimental requirements to address them.     

Characterisation of flood inundated areas and delineation of poor drainage soil using ERS-1 SAR imagery

Recent years have been marked by a continuous availability of spatial SAR data since the launch of the European remote sensing satellite (ERS-1) in 1991. Consequently, remote sensing techniques now offer an opportunity to map flood inundation fields caused by river overflow or waterlogging in environments characterized by frequent cloud cover. Indeed, inundation fields can clearly be seen on ERS-1 SAR images taken during flooding periods. However, such an identification can be constrained by the similarity in behaviour between water surfaces and other features of the landscape such as extended asphalt areas, permanent water bodies and less illuminated slopes. For consistent flood inundation extent mapping a more robust approach is required. This is provided by a conceptual flood inundation index that is physically sound in relation to radar imaging. Moreover, this index has proved to be useful for highlighting soils located within inundation fields and having significantly different internal drainage. The results achieved in the framework of the research must be seen in the context of intensive use of remote sensing data to support decision methods for sustainable management of land and water resources. Such decision support methods could be provided by river hydraulic models aimed at assessing environmental effects of inundation floods and at early flood warning systems. © 1997 John Wiley & Sons, Ltd.     

Automatic mapping of snow cover depletion curves using optical remote sensing data under conditions of frequent cloud cover and temporary snow

Snow cover depletion curves are required for several water management applications of snow hydrology and are often difficult to obtain automatically using optical remote sensing data owing to both frequent cloud cover and temporary snow cover. This study develops a methodology to produce accurate snow cover depletion curves automatically using high temporal resolution optical remote sensing data (e.g. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua MODIS or National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR)) by snow cover change trajectory analysis. The method consists of four major steps. The first is to reclassify both cloud‐obscured land and snow into more distinct subclasses and to determine their snow cover status (seasonal snow cover or not) based on the snow cover change trajectories over the whole snowmelt season. The second step is to derive rules based on the analysis of snow cover change trajectories. These rules are subsequently used to determine for a given date, the snow cover status of a pixel based on snow cover maps from the beginning of the snowmelt season to that given date. The third step is to apply a decision‐tree‐like processing flow based on these rules to determine the snow cover status of a pixel for a given date and to create daily seasonal snow cover maps. The final step is to produce snow cover depletion curves using these maps. A case study using this method based on Terra MODIS snow cover map products (MOD10A1) was conducted in the lower and middle reaches of the Kaidu River Watershed (19 000 km²) in the Chinese Tien Shan, Xinjiang Uygur Autonomous Region, China. High resolution remote sensing data (charge coupled device (CCD) camera data with 19·5 m resolution of the China and Brazil Environmental and Resources Satellite (CBERS) data (19·5 m resolution), and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data with 15 m resolution of the Terra) were used to validate the results. The study shows that the seasonal snow cover classification was consistent with that determined using a high spatial resolution dataset, with an accuracy of 87–91%. The snow cover depletion curves clearly reflected the impact of the variation of temperature and the appearance of temporary snow cover on seasonal snow cover. The findings from this case study suggest that the approach is successful in generating accurate snow cover depletion curves automatically under conditions of frequent cloud cover and temporary snow cover using high temporal resolution optical remote sensing data. Copyright © 2007 John Wiley & Sons, Ltd.     

Dynamite fishing in northern Tanzania - pervasive, problematic and yet preventable

Dynamite fishing, although illegal, has resurfaced in recent years as a major threat to the reefs of northern Tanzania. This is despite the fact that institutional arrangements for co-management of the inshore fisheries by local communities and the district governments have been put in place and, through a 12-year donor-funded programme, numerous activities undertaken to build capacity for effective fisheries management. The use of dynamite is having widespread negative impacts, including damage to the reefs and their long-term productivity, deterrence of tourism investors, and potential threat to the large population of coelacanths in the area. The dynamite fishers are able to continue, even though enforcement efforts have been stepped up, because they are members of influential families or otherwise well-connected. Previous similar cases in Tanzania, and examples from elsewhere in the world, suggest that a major initiative is now needed to develop a zero-tolerance approach on the part of fishers and local and national leaders, that will shame the dynamiters through peer pressure, promote full implementation of sanctions and penalties by the judiciary, and lead to public recognition of and support for the work of the enforcement agencies.     

Land cover mapping using time series HJ-1/CCD data

It is very difficult to have remote sensing data with both high spatial resolution and high temporal frequency; thus, two categories of land-use mapping methodology have been developed separately for coarser resolution and finer resolution data. The first category uses time series of data to retrieve the variation of land surface for classification, which are usually used for coarser resolution data with high temporal frequency. The second category uses fine spatial resolution data to classify different land surface. With the launch of Chinese satellite constellation HJ-1in 2008, four 30 m spatial resolution CCDs with about 360 km coverage for each one onboard two satellites made a revisit period of two days, which brought a new type of data with both high spatial resolution and high temporal frequency. Therefore, by taking the spatiotemporal advantage of HJ-1/CCD data we propose a new method for finer resolution land cover mapping using the time series HJ-1/CCD data, which can greatly improve the land cover mapping accuracy. In our two study areas, the very high resolution remote sensing data within Google Earth are used to validate the land cover mapping results, which shows a very high mapping accuracy of 95.76% and 83.78% and a high Kappa coefficient of 0.9423 and 0.8165 in the Dahuofang area of Liaoning Province and the Heiquan area of Gansu Province respectively.     

Influence of land use on the quality of runoff along Israel′s coastal strip (demonstrated in the cities of Herzliya and Ra′anana)

This study presents an analysis of the quality of urban runoff from various land uses by remote‐sensing and GIS technology coupled with hydrological and chemical monitoring. The study areas were located in the cities of Herzliya and Ra′anana, in Israel′s coastal plain, where extensive urbanization has occurred over the last 30 years. Land uses in urban basins were analysed; rain and runoff were measured and sampled at measurement stations representing different land uses (residential, industrial, commercial and roads). The aim was to analyse uses by different remote‐sensing and GIS techniques, to evaluate the quality of urban storm water from various land uses and to verify a method for predicting the impact of urban land uses on the quantity and quality of urban storm water. The quality of urban storm water from residential areas was generally very high, and the water is suitable for reuse or direct recharge into the local aquifer. In light of the serious state of the Israeli water sector and the large amounts of unused runoff produced by Israel′s cities, together with the high quality of urban storm water drained from the residential areas, it is important to exploit this water source. Copyright © 2014 John Wiley & Sons, Ltd.     

Land use and land cover classification using phenological variability from MODIS vegetation in the Upper Pangani River Basin,Eastern Africa

In arid and semi-arid areas, evaporation fluxes are the largest component of the hydrological cycle, with runoff coefficient rarely exceeding 10%. These fluxes are a function of land use and land management and as such an essential component for integrated water resources management. Spatially distributed land use and land cover (LULC) maps distinguishing not only natural land cover but also management practices such as irrigation are therefore essential for comprehensive water management analysis in a river basin. Through remote sensing, LULC can be classified using its unique phenological variability observed over time. For this purpose, sixteen LULC types have been classified in the Upper Pangani River Basin (the headwaters of the Pangani River Basin in Tanzania) using MODIS vegetation satellite data. Ninety-four images based on 8 day temporal and 250 m spatial resolutions were analyzed for the hydrological years 2009 and 2010. Unsupervised and supervised clustering techniques were utilized to identify various LULC types with aid of ground information on crop calendar and the land features of the river basin. Ground truthing data were obtained during two rainfall seasons to assess the classification accuracy. The results showed an overall classification accuracy of 85%, with the producer’s accuracy of 83% and user’s accuracy of 86% for confidence level of 98% in the analysis. The overall Kappa coefficient of 0.85 also showed good agreement between the LULC and the ground data. The land suitability classification based on FAO-SYS framework for the various LULC types were also consistent with the derived classification results. The existing local database on total smallholder irrigation development and sugarcane cultivation (large scale irrigation) showed a 74% and 95% variation respectively to the LULC classification and showed fairly good geographical distribution. The LULC information provides an essential boundary condition for establishing the water use and management of green and blue water resources in the water stress Pangani River Basin.