Assessing farmland dynamics and land degradation on Sahelian landscapes using remotely sensed and socioeconomic data

Through the integration of SPOT HRV, biophysical and socioeconomic information, the study identified population carrying capacities and their vulnerability to land degradation. Land use intensification on the landscapes was quantified into expansion, early and late phases based on the Ruthenberg index calculated using a biennial series of SPOT images for the period 1986-96. Subsequently, farmland dynamic on different landscapes was calculated while observed patterns were linked with agricultural intensification and population carrying capacity. Results show a pattern of agricultural land degradation due to increasing pressure of population and agricultural intensification within a system characterised by little or no use of inputs. Fifty-six percent of the study area supports a population density higher than the carrying capacity (≤ 15 pers/km^-2). Sixty-three percent of the study area is under early to late phases of agricultural intensification. Between 1986-96, cultivation declined 2-3% annually on landscapes with Low risk of degradation but increased by 1-2% on those with Average/Extreme risks. This emphasises the process of land abandonment as farmers move on to cultivating marginal lands despite above normal seasonal rainfalls observed during most of the period. By 1996, cultivation tended to include fields much farther away from the vicinity of villages, compared with 10 years earlier. Furthermore, by 1996, farmlands in the zones of late intensification declined from 12 to 4% and increased from 6 to 11% in the zone under the expansion phase. Indicating that by 1996 substantial amount of the land area required increasing lengths of fallowing. The spatial GIS modelling approach allowed not only identification of zones but synthesis of the observed pattern of landscape degradation. The paper highlights the need for combining remote sensing, biophysical and socio-economic data in environmental degradation studies in developing countries with their poor data availability. The role of developing countries scientists is stressed in taking the forefront to tackle environmental problems, which affect their region. The paper calls for increased co-operation between these scientists and regional and international data providers to overcome data availability problems and pave the way for better local and regional studies on environmental degradation.     

Predicting gully rejuvenation after wildfire using remotely sensed burn severity data

The loss of surface vegetation and reduced infiltration caused by wildfires can trigger gully rejuvenation, resulting in damage to downstream aquatic resources and risk to human life and property. We developed a spatially explicit metric of burn severity — the Burn Severity Distribution Index (BSDI) — and tested its ability to predict post-fire gully rejuvenation in 1st and 2nd order basins burned in the 2000 Valley Complex fires in the Sapphire Mountains of western Montana. The BSDI was derived from burn severity data interpreted from Landsat 7 satellite imagery using the Normalized Burn Ratio (NBR) method, and ranged from 0.0 for completely unburned basins to 4.0 for basins burned entirely at high severity. In July 2001 rainstorms with peak 30-minute intensities of up to 17 mm h^− 1 triggered gully rejuvenation in 66 of the 171 basins examined. The frequency of gully rejuvenation was higher in basins with higher BSDI values, increasing from zero for basins with a BSDI less than 1.3 to 67% for basins with a BSDI greater than 3.0. Binary logistic regression indicated that BSDI was a more significant predictor of gully rejuvenation than basin morphometric variables. The absence of gully rejuvenation in several basins with a high BSDI was attributed to low gradient, dense riparian vegetation, or concentration of high burn severity at lower elevations in the basin. The presence of gully rejuvenation in several basins with a low BSDI was associated with false negative NBR classification errors in northwest aspects, and concentration of severe burn impacts in the drainage headslopes. BSDI is a useful metric for predicting gully rejuvenation after wildfire. The use of the BSDI in Burned Area Emergency Response team assessments could improve the planning, implementation, and monitoring of burned area recovery treatments.     

基于遥感的民勤绿洲植被覆盖变化定量监测

基于混合像元条件下的TM影像植被覆盖度遥感反演,定量研究了甘肃省民勤绿洲1987年至2001年植被覆盖时空变化的规律与特点。结果表明,15年中,民勤绿洲的植被覆盖发生了很大的变化,农田植被(耕地)面积增加了53.11%,而中、高盖度植被的面积却减少了25.21%,这对民勤绿洲的长久生态安全构成了严重的威胁。民勤绿洲植被覆盖变化的空间转化过程复杂,但总体属于开垦—植被退化型。15年中因开垦和植被退化而损失的中、高盖度植被达42204.81hm2,占原面积的81.73%,而且损失的主要是绿洲边缘的防风固沙植被,其中因开垦损失的面积为18776.08hm2,占损失面积的44.5%。超采地下水引起的地下水位快速下降是导致绿洲边缘天然和人工灌丛植被退化的主要原因。控制开垦并培育相对稳定的灌丛型植被,应该是研究区生态环境建设的重点。     

一种改进的土壤水分微波遥感反演模型

利用微波遥感数据反演地表土壤水分有着较好的物理基础,可实现大范围土壤水分状况的遥感监测。本文基于被动微波传感器AMSR-E的X波段数据,将土壤水分值分解成基准值和日变化量两个部分,并分别建立反演模型,同时引入降雨修正因子来进一步提高土壤水分的估算精度;利用IDL语言实现了我们所研发的模型,并集成为新疆土壤水分遥感反演系统模块之一;利用Watch Dog2400与传统铝盒采样获取的新疆地面土壤水分数据,提取适合的模型经验参数,并对模型结果进行精度评价。结果表明,经改进的模型反演得到的新疆土壤水分结果比美国冰雪数据中心的土壤水分产品在精度上有显著提高:均方根误差由8.4%降低为4.25%;所研发的软件模块可为相关应用部门提供快速的大范围土壤水分监测产品。     

遥感影像地形校正研究进展及其比较实验

地形校正作为复杂地形区遥感影像预处理的重要步骤,对提高地表参数遥感定量化精度具有重要意义。为此,在简述地形校正含义与目标的基础上,回顾并总结了国内外各种地形校正方法并将其划分为基于波段比、DEM和超球面3类方法,以期为地形校正及相关研究提供参考。在DEM的支持下,采用11种地形校正方法对ETM+影像进行了校正比较实验,研究表明:(1)VECA、b、C、Teillet-回归、SCS+C、Minnaert和Minnaert-SCS校正7种地形校正效果较好,可用于遥感影像的地形校正;而Cosine-T、Cosine-C、SCS和Cosine-b校正存在过度校正现象,不宜选择。(2)VECA与b校正模型校正效果最好,且VECA校正比b校正可操作性更强。在此基础上,从地形效应的理论诠释与数学表达、DEM数据、地形校正应用研究3个方面探讨了目前该领域存在的一些问题和难点,并对今后可能的工作重点和研究方向提出了建议。     

Estimating and simulating the degree of serpentinization of peridotites using hyperspectral remotely sensed imagery

The mineral products resulting from the process of serpentinization, by which primary magnesium silicate minerals in peridotites are replaced by hydrous serpentine-group minerals, are of economic importance since Alpine-type peridotites are the host rocks for virtually all large asbestos deposits, which may be attributed mainly to the serpentine-group mineral chrysotile. Conventional field mapping of the distribution of highly serpentinized areas is time consuming and requires detailed sampling and laboratory analysis. In 0.4- to 2.5-m reflectance spectra of serpentinized peridotites, serpentinization is responsible for a decrease in contrast of olivine-pyroxene iron absorption features and an appearance and increase in OH^– absorption features near 1.4 m and 2.3 m associated with serpentine minerals. The degree of serpentinization is positively correlated with the depth of the 1.4-m and 2.3-m absorption features for samples containing more than 55 weight percent serpentine minerals. Small amounts of magnetite in a sample obscure the spectral contrast and decrease the overall brightness of weakly serpentinized samples. A methodology is used for mapping serpentine minerals in ultrabasic rocks from imaging spectrometer data, which includes (1) vegetation masking, (2) calculating the absorption band depth of the 2.3-m absorption feature in unmasked pixels, (3) translating this value into percent serpentine minerals using an empirical linear model, and (4) estimating the degree of serpentinization at the remaining locations using conditional simulation techniques or ordinary block kriging. From the results of this study, it can be concluded that mapping the degree of serpentinization from high-spectral resolution imagery is possible within marginal statistical fluctuations. Conditional simulation reproduces the spatial and statistical variability of the data set; however, it sacrifices the local accuracy. Direct estimation using ordinary kriging provides a better local estimate but does not honor the statistics and spatial dispersion of the original data.The spectral analyses presented in this publication were carried out at the Jet Propulsion Laboratory in Pasadena, California. The author would like to thank Mrs. Cindy Grove for her help in processing the samples. Dr. Harold Lang is thanked for advice in interpreting the spectra. The article benefitted from critical comments by Dr. Roger Clark and Dr. John Mustard, and various discussions with Prof. Salemon Kroonenberg and Prof. Andrea Fabbri. The Spectral Image Processing System (SIPS) developed at the Center for the Study of Earth from Space (CSES) of the University of Colorado, Boulder, was used for the GERIS data calibration. This article benefitted from a critical review by Dr. Daniel H. Knepper, Jr.     

Modeling spatial and temporal change of soil erosion based on multi-temporal remotely sensed data

In order to monitor the pattern, distribution, and trend of land use/cover change (LUCC) and its impacts on soil erosion, it is highly appropriate to adopt Remote Sensing (RS) data and Geographic Information System (GIS) to analyze, assess, simulate, and predict the spatial and temporal evolution dynamics. In this paper, multi-temporal Landsat TM/ETM+ remotely sensed data are used to generate land cover maps by image classification, and the Cellular Automata Markov (CA_Markov) model is employed to simulate the evolution and trend of landscape pattern change. Furthermore, the Revised Universal Soil Loss Equation (RUSLE) is used to evaluate the situation of soil erosion in the case study mining area. The trend of soil erosion is analyzed according to total/average amount of soil erosion, and the rainfall (R), cover management (C), and support practice (P) factors in RUSLE relevant to soil erosion are determined. The change trends of soil erosion and the relationship between land cover types and soil erosion amount are analyzed. The results demonstrate that the CA_Markov model is suitable to simulate and predict LUCC trends with good efficiency and accuracy, and RUSLE can calculate the total soil erosion effectively. In the study area, there was minimal erosion grade and this is expected to continue to decline in the next few years, according to our prediction results.     

Merged remotely sensed data for geomorphological investigations in deserts: examples from central Saudi Arabia

Image merging has gained acceptance in geological remote sensing, however it has rarely been applied in geomorphology. We report on the usefulness of principal components substitution (PCS) to merge IRS panchromatic data with multispectral Thematic Mapper (TM) imagery, to map commonly encountered desert geomorphological features, and in relative age dating of alluvial surfaces. The merged data were applied to the identification and mapping of geomorphological features along two geolo-gically different mountain fronts in central Saudi Arabia. Two types of geomorphological maps have been created. A morphogenetic map that distinguishes between aeolian landforms, fluvial landforms, desert pavements, and gypsum crusts. Second, a morphochronological map, which shows the relative age of four geomorphic surfaces developed on an alluvial fan. The construction of the two maps is supported by field observations and laboratory measurements. Using the optimum index factor (OIF), a TM band 1, 5 and 7 image (of 20 merged composites) was found to be the optimum colour composite image for the geomorphological features in this arid environment. We discuss our findings in the context of the spatial and spectral properties required for applied geomorphological remote sensing.     

ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data

The spatial resolution of imaging sensors has increased dramatically in recent years, and so too have the challenges associated with extracting meaningful information from their data products. Object-based image analysis (OBIA) is gaining rapid popularity in remote sensing science as a means of bridging very high spatial resolution (VHSR) imagery and GIS. Multiscalar image segmentation is a fundamental step in OBIA, yet there is currently no tool available to objectively guide the selection of appropriate scales for segmentation. We present a technique for estimating the scale parameter in image segmentation of remotely sensed data with Definiens Developer®. The degree of heterogeneity within an image-object is controlled by a subjective measure called the ‘scale parameter’, as implemented in the mentioned software. We propose a tool, called estimation of scale parameter (ESP), that builds on the idea of local variance (LV) of object heterogeneity within a scene. The ESP tool iteratively generates image-objects at multiple scale levels in a bottom-up approach and calculates the LV for each scale. Variation in heterogeneity is explored by evaluating LV plotted against the corresponding scale. The thresholds in rates of change of LV (ROC-LV) indicate the scale levels at which the image can be segmented in the most appropriate manner, relative to the data properties at the scene level. Our tests on different types of imagery indicated fast processing times and accurate results. The simple yet robust ESP tool enables fast and objective parametrization when performing image segmentation and holds great potential for OBIA applications.     

Geomorphological observations and related natural hazards using merged remotely sensed data: a case study in the Corinthos area (NE Peloponnese, S. Greece)

Natural hazards are mostly related to the activation of combined geomorphological and geological processes that control landform development. The study area is located in the NE part of Peloponnese (Corinthos prefecture). It is a typical agricultural area with intense relief, the result of active tectonics and important human intervention. This study demonstrates the benefits from the synergism of SAR data (ERS-2) and optical data (SPOT2-XS) in order to highlight the possible natural-hazardprone areas. These data give different and complementary information since the radar signal depends mostly on topography, surface roughness and soil moisture, whereas the visible/infrared channels provide spectral information mostly on vegetation and land use/cover. The application presented here was focused on the enhancement of the high erosion risk areas, the improvement of the terrain interpretation, the mapping and highlighting of the landform morphology, and a more accurate determination of the main factors that control the flooding risk of Corinthos town.     

Estimating agricultural production in marginal and food insecure areas in Kenya using very high resolution remotely sensed imagery

Regularly monitoring the amount of food produced in food insecure, isolated, subsistence farming areas can be used to help identify households or communities who may be in need of additional food resources. Measuring seasonal food production in developing countries, particularly at a sub-national level, is complicated by lack of data. In this study we use high resolution remotely sensed data to calculate cultivated area in two different growing areas, during two different seasons in Kenya. The results of the research support the usefulness of this approach for agricultural monitoring in the developing world and suggest that monitoring cultivated area requires attention to the specific growing characteristics of an area.     

Coupling numerical simulation with remotely sensed information for the study of frozen soil dynamics

The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil.     

Use of remotely sensed data in mapping underwater landscapes of Srednyaya Bay (Peter the Great Gulf,Sea of Japan)

We examine the selection criteria for satellite images and methods of processing them in the process of mapping underwater landscapes using remotely sensed data, discuss the interpretation principles and algorithms as well as some issues related to the support of observations with field material. It is shown that a detailed landscape mapping of shallow marine waters by methods of visual and automated interpretation requires multispectral superhigh spatial resolution images. Results of investigations made on underwater profiles by using lightweight diving outfits were employed to describe seven types of underwater landscapes, and echo sounder measurements were used in constructing the digital elevation model for the bottom of Srednyaya Bay. It is established that the regions for which it was possible to carry out a reliable interpretation of data from the IKONOS-2 spacecraft are in the range of depths between 0 and 10 m and make up about three-fourths of the area of the bay bottom. Ten facies were identified and put on the map, for each of which we determined the area, the range of depths and the mean depth of propagation. Remotely sensed data were used to assess the contribution (in the spatial structure of the geosystem) of algal vegetation on the littoral; the eelgrass fields were ranked according to the degree of projective cover. As a result of a clustering according to the similarity of spectral attributes, we identified ten groups of pixels of the image analyzed. An analysis is made of the agreement between the distribution of facies identified by expert interpretation and results of an automated classification of pixels, and the contours of landscape units were updated. The conclusion is drawn regarding integration of the computer-aided and visual approaches to interpretation of remotely sensed data for shallow marine waters leading to a “hybrid” express method of mapping landscapes of shallow marine waters.     

Classification of river basins and hydrological regionalization (as exemplified by Japan)

A set of problems related to formation of areas homogeneous in hydrological aspect is considered. A methodology of regionalization is proposed. New analytical methods of the methodology are intended of solving such problems as (i) the problem of regionalization and (ii) the problem of constructing of a classification for river drainage basins. Efficiency of the methods proposed has been tested on the problems, which arise in the process of constructing classifications for river drainage basins, and also on the problem of territorial regionalization of Japan islands. Investigations, which presume obtaining a set of morphometric and hydrographic characteristics of catchment areas, allow one to study conditions of extreme inundations. It has been discovered that boundaries of the areas have striking similarities in the spatial location of geological structures. Furthermore, these are coincide with the boundaries of the main tectonic fields.     

Assessing Mongolian snow disaster risk using livestock and satellite data

In Mongolia, several record-breaking disastrous dzuds (mass livestock loss directly induced by harsh winter conditions but often influenced by drought in the previous summer) occurred from 1999 to 2003. To understand the mechanism of this climatic disaster, we conducted a tree regression analysis. The predictor variables included two indices developed from remote sensing data—the Normalized Difference Vegetation Index (NDVI) and the Snow Water Equivalent (SWE)—as well as the previous year's livestock numbers and mortality rates. According to the model, serious livestock mortality was associated with low NDVI values (i.e., poor vegetation) in August of the previous year, high SWE values (i.e., significant snow accumulation) in December of the previous year, a high previous year's mortality, and high previous year's livestock population. This result suggests that for dzud risk assessment, we need to monitor snowfall in winter, the vegetation condition in the previous summer, and the density and health condition of the livestock. The tree-based model developed in this study is effective only for a white dzud (deep snow), the most common type of dzud. The large cross-validation error indicates that more data are needed before using the model in order to make predictions.     

国际河流流域整体开发和管理的实施

本文通过分析目前整体开发和管理实践中存在的主要问题,提出国际河流与国家河流相比较,其开发和管理的特点,最后就实现国际河流整体开发和管理中的动力、合作层次、协议、制度协调等方面问题提出相应的观点。     

Assessing potential land suitable for surface irrigation using groundwater in Ethiopia

Although Ethiopia has abundant land for irrigation, only a fraction of its potential land is being utilized. This study evaluates suitability of lands for irrigation using groundwater in Ethiopia using GIS-based Multi-Criteria Evaluation (MCE) techniques in order to enhance the country's agricultural industry. Key factors that significantly affect irrigation suitability evaluated in this study include physical land features (land use, soil, and slope), climate (rainfall and evapotranspiration), and market access (proximity to roads and access to market). These factors were weighted using a pair-wise comparison matrix, then reclassified and overlaid to identify suitable areas for groundwater irrigation using a 1-km grid. Groundwater data from the British Geological Survey were used to estimate the groundwater potential, which indicates the corresponding irrigation potential for major crops. Results indicated that more than 6 million ha of land are suitable for irrigation in Ethiopia. A large portion of the irrigable land is located in the Abbay, Rift Valley, Omo Ghibe, and Awash River basins. These basins have access to shallow groundwater (i.e., depth of groundwater less than 20 m from the surface) making it easier to extract. The comparison between available groundwater and total crop water requirements indicate that groundwater alone may not be sufficient to supply all suitable land. The study estimates that only 8% of the suitable land can be irrigated with the available shallow groundwater. However, groundwater is a viable option for supplementing surface water resources for irrigation in several basins in the country.     

Icings in the river basins of Primorski Krai and their influence on landscapes

We examine the types of icings (aufeis) in the river basins of Primorski Krai. An assessment is made of the conditions for their formation in autumn and winter and for their decay in the spring-summer time. Depending on the type of icings, we identified the character of their impact on the main components of landscape: relief, hydrological regime of streams, soil, vegetation, etc. The emphasis in this study is on the icing formations in the zone of seasonally frozen earth materials and, to a lesser extent, in areas of permafrost islands.     

Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee,Wisconsin

There have been a great number of debates about the impacts of trees on crimes: some researchers believed that trees are a crime facilitator because of the concealment provision for potential criminals, while others argued that they are a crime deterrent because of the increased surveillance possibility and the therapeutic effect on psychological fatigue. To better answer this question, this study incorporated detailed tree features by using multi-source remotely sensed data at a very high resolution into environmental criminology analysis across the entire City of Milwaukee. Trees were extracted from aerial photographs, and broken down into two categories based on their heights to consider the effects of tree height on view obstruction. By controlling for confounding socioeconomic variables, the relationship between crimes and a series of composition and configuration indicators of trees with different height were investigated by using global and local spatial regressions. Results from classic and spatial statistical techniques finds complicated relationship between crimes and trees, which can be summarized in two aspects. First, the mixed effects of trees can be observed among different crime types. Second, the trends of spatial nonstationarity of the composition and configuration of trees with different heights were observed across the entire study area. The study outcomes could provide reasonable implications for making appropriate policies for crime prevention through environmental design to strengthen neighborhoods and communities in a city.     

The erosion-accumulative processes within the basins of small rivers of southern East Siberia

The mean values of potential soil loss and of sediments that are removed from the gullies are calculated, and the data on the rates of erosion-accumulative processes on arable lands, in gully-dried-up river-bed systems are provided. For the Yelovka and Kuitunka rivers the basin component of the erosion-accumulative processes has been assessed qualitatively. The sequences of erosion loss to drainage basins of small rivers as well as of scouring and accumulation are determined.