Monitoring Indigenous Tropical Montane Forests in the Taita Hills Using Airborne Digital Camera Imagery

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955 2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.

Landslide Susceptible Locations in Western Ghats: Prediction through openModeller

Many shallow landslides are triggered by heavy rainfall on hill slopes resulting in enormous casualties and huge economic losses in mountainous regions. Hill slope failure usually occurs as soil resistance deteriorates in the presence of the acting stress developed due to a number of reasons such as increased soil moisture content, change in land use causing slope instability, etc. Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration and information related to land surface susceptibility. Terrain analysis applications using spatial data such as aspect, slope, flow direction, compound topographic index, etc. along with information derived from remotely sensed data such as land cover / land use maps permit us to quantify and characterise the physical processes governing the landslide occurrence phenomenon. In this work, the probable landslide prone areas are predicted using two different algorithms – GARP (Genetic Algorithm for Rule-set Prediction) and Support Vector Machine (SVM) in a free and open source software package - openModeller. Several environmental layers such as aspect, digital elevation data, flow accumulation, flow direction, slope, land cover, compound topographic index, and precipitation data were used in modelling. A comparison of the simulated outputs, validated by overlaying the actual landslide occurrence points showed 92% accuracy with GARP and 96% accuracy with SVM in predicting landslide prone areas considering precipitation in the wettest month whereas 91% and 94% accuracy were obtained from GARP and SVM considering precipitation in the wettest quarter of the year.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

Climate forcing and response to idealized changes in surface latent and sensible heat

Land use and land cover changes affect the partitioning of latent and sensible heat, which impacts the broader climate system. Increased latent heat flux to the atmosphere has a local cooling influence known as `evaporative cooling', but this energy will be released back to the atmosphere wherever the water condenses. However, the extent to which local evaporative cooling provides a global cooling influence has not been well characterized. Here, we perform a highly idealized set of climate model simulations aimed at understanding the effects that changes in the balance between surface sensible and latent heating have on the global climate system. We find that globally adding a uniform 1 W m(-2) source of latent heat flux along with a uniform 1 W m(-2) sink of sensible heat leads to a decrease in global mean surface air temperature of 0.54 +/- 0.04 K. This occurs largely as a consequence of planetary albedo increases associated with an increase in low elevation cloudiness caused by increased evaporation. Thus, our model results indicate that, on average, when latent heating replaces sensible heating, global, and not merely local, surface temperatures decrease.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Monitoring urbanization and its implications in a mega city from space: Spatiotemporal patterns and its indicators

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources. Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geo-informatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. (C) 2014 Elsevier Ltd. All rights reserved.

Reliability Assessment of a Storm Water Drain Network

Most of the cities in India are undergoing rapid development in recent decades, and many rural localities are undergoing transformation to urban hotspots. These developments have associated land use/land cover (LULC) change that effects runoff response from catchments, which is often evident in the form of increase in runoff peaks, volume and velocity in drain network. Often most of the existing storm water drains are in dilapidated stage owing to improper maintenance or inadequate design. The drains are conventionally designed using procedures that are based on some anticipated future conditions. Further, values of parameters/variables associated with design of the network are traditionally considered to be deterministic. However, in reality, the parameters/variables have uncertainty due to natural and/or inherent randomness. There is a need to consider the uncertainties for designing a storm water drain network that can effectively convey the discharge. The present study evaluates performance of an existing storm water drain network in Bangalore, India, through reliability analysis by Advance First Order Second Moment (AFOSM) method. In the reliability analysis, parameters that are considered to be random variables are roughness coefficient, slope and conduit dimensions. Performance of the existing network is evaluated considering three failure modes. The first failure mode occurs when runoff exceeds capacity of the storm water drain network, while the second failure mode occurs when the actual flow velocity in the storm water drain network exceeds the maximum allowable velocity for erosion control, whereas the third failure mode occurs when the minimum flow velocity is less than the minimum allowable velocity for deposition control. In the analysis, runoff generated from subcatchments of the study area and flow velocity in storm water drains are estimated using Storm Water Management Model (SWMM). Results from the study are presented and discussed. The reliability values are low under the three failure modes, indicating a need to redesign several of the conduits to improve their reliability. This study finds use in devising plans for expansion of the Bangalore storm water drain system. (C) 2015 The Authors. Published by Elsevier B.V.

Modelling the influence of land-use changes on biophysical and biochemical interactions at regional and global scales

Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed. center dot Land-use changes affect global and regional climates through both biochemical and biophysical process. center dot Climate effect from biophysical process depends on the location of land-use change. center dot Climate mitigation strategies such as afforestation/reforestation should consider the net effect of biochemical and biophysical processes for effective mitigation. center dot Climate-smart agriculture could use bio-geoengineering techniques that consider plant biophysical characteristics such as reflectivity and water use efficiency.

Guidance for benthic habitat mapping: an aerial photographic approach

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor.

Transformações socioespaciais em Angra dos Reis e Parati (RJ) de 1960/70 a 2010

Esta pesquisa tem como objetivo analisar as transformações socioespaciais ocorridas em Angra dos Reis e Parati no período que compreende os anos de 1960/70 a 2010. Para isso, discutiu-se o conceito de espaço geográfico considerando obras dos autores Milton Santos, Doreen Massey e Roberto Lobato Corrêa, buscando identificar as concepções destes sobre o conceito em questão e de que maneira as transformações ocorrem nos espaços, alterando sua forma e conteúdo de maneira singular e diversa. A possibilidade do acontecer diferente, da não linearidade dos espaços no tempo e de que a multiplicidade abre caminho para inúmeros arranjos diferenciados, permitem concluir que os espaços são diferentes, ainda que considerado todo o movimento globalizante do qual fazem parte. Para analisar as transformações, utilizou-se imagens de satélite (Landsat 2 e 5) dos anos de 1977, 1990 e 2010 a fim de gerar mapas de onde foi possível verificar a expansão das áreas urbanas. Em conjunto, trabalhou-se com dados econômicos e populacionais de censos produzidos pelo IBGE, dados da EMATER e outros utilizados na elaboração de quadros e tabelas sobre a estrutura socioeconômica dos municípios. Foram selecionadas fotografias antigas fornecidas pelo IPHAN, IBGE e outras fontes para ilustrar as transformações apresentadas. Trabalhou-se com as interações espaciais e os fluxos, apontados por Roberto Lobato Corrêa e Milton Santos, respectivamente, para entender como as organizações espaciais de cada município vão se modificando, na medida em que as interações também se transformam. Por meio de um resgate histórico, retrocedendo um pouco no tempo para o século XIX, buscou-se compreender como o ouro, o café, a ferrovia e o porto explicam, em parte, essa dinâmica diferenciada de transformação. E no decorrer das décadas do século XX, foram identificados os principais elementos que originaram as mudanças analisadas no período escolhido, sendo as usinas nucleares, o estaleiro naval, a rodovia BR-101, o turismo e o terminal de petróleo da Petrobrás. Ao falar da expansão urbana discutiu-se sobre o espaço rural e a sua hibridização, assumindo novas configurações com a incorporação de valores, formas, comportamentos e práticas urbanas.

Enfoque da estatística espacial em modelos dinâmicos de mudança do uso do solo.

O atual nível das mudanças uso do solo causa impactos nas mudanças ambientais globais. Os processos de mudanças do uso e cobertura do solo são processos complexos e não acontecem ao acaso sobre uma região. Geralmente estas mudanças são determinadas localmente, regionalmente ou globalmente por fatores geográficos, ambientais, sociais, econômicos e políticos interagindo em diversas escalas temporais e espaciais. Parte desta complexidade é capturada por modelos de simulação de mudanças do uso e cobertura do solo. Uma etapa do processo de simulação do modelo CLUE-S é a quantificação da influência local dos impulsores de mudança sobre a probabilidade de ocorrência de uma classe de uso do solo. Esta influência local é obtida ajustando um modelo de regressão logística. Um modelo de regressão espacial é proposto como alternativa para selecionar os impulsores de mudanças. Este modelo incorpora a informação da vizinhança espacial existente nos dados que não é considerada na regressão logística. Baseado em um cenário de tendência linear para a demanda agregada do uso do solo, simulações da mudança do uso do solo para a microbacia do Coxim, Mato Grosso do Sul, foram geradas, comparadas e analisadas usando o modelo CLUE-S sob os enfoques da regressão logística e espacial para o período de 2001 a 2011. Ambos os enfoques apresentaram simulações com muito boa concordância, medidas de acurácia global e Kappa altos, com o uso do solo para o ano de referência de 2004. A diferença entre os enfoques foi observada na distribuição espacial da simulação do uso do solo para o ano 2011, sendo o enfoque da regressão espacial que teve a simulação com menor discrepância com a demanda do uso do solo para esse ano.

黄土高原沟壑区王东沟流域土地利用/覆被变化过程初探

黄土高原沟壑区王东沟流域从1986年至2006年的土地利用/覆被发生了较大变化,土地利用动态指数分别为:耕地3.21%,园地-36.11%,林地-4.05%,牧草地4.24%,居民点及独立工矿用地-0.62%,交通运输用地-12.27%,未利用地1.85%;变化趋势是:耕地逐年向园地流转,园地变化烈度较大,其他各类用地变化不太显著。引起这一变化的主要因素是自然、社会、经济、技术以及政策因素。结合这一变化,针对黄土高原沟壑区的实际情况,在黄土高原沟壑区土地利用经营与管理方面,应重视土地产出效益与粮食安全的关系,在保障区域粮食安全的基础上实现效益最大化。

黄河中游地区年径流对土地利用变化时空响应分析

以黄河中游河龙区间为研究区,以水土流失综合治理及生态环境建设导致的土地利用/覆被变化为背景,采用非参数统计法,基于区内38个水文站20世纪50年代至2000年水文数据,分析流域年径流对土地利用/覆被变化响应的时空变异特征,估算影响因素贡献率。结果表明:其中29条流域年径流量呈显著减少趋势,变率为0.17~2.61 mm/a;28条流域年径流量具有显著跃变时间,无定河流域各水文站跃变时间多在1970—1973年间,其余则多为1978—1985年,最晚为1994年;在5%、50%和95%的发生频率上,跃变前后时段年径流量减少幅度以30%~60%普遍,最大分别为73.2%、63.5%和69.7%;河龙区间整体呈显著减少趋势,变率为0.79 mm/a,跃变时间发生在1979年,3个频率上的减少幅度分别为46.5%、42.4%和24.1%。估算的11条流域中有9条土地利用/覆被变化等人类活动对流域径流减少影响程度超过50%。水土保持措施面积的增加,尤其淤地坝等水利水保工程措施的持续修建,对区域地表径流变化具有明显影响。

分布式水文模型的误差分析

分布式水文模型以其具有明确物理意义的参数结构和对空间分异性的全面反映,能够准确详尽地描述和模拟流域内真实的降水径流过程而被广泛需求和关注。在模拟土地利用、土地覆盖、水土流失等各种变化过程的水文响应,面源污染、陆面过程、气候变化影响评价等诸多领域都有广泛的应用。模型的预报精度和误差至关重要,决定了模型的应用和推广。在分析分布式水文模型建立和验证过程的基础上,提出了模型的4类误差来源:被排除在外的因素引起的误差,实测历史记录资料的随机或系统误差,参数误差和模型结构误差,讨论了各类误差的分析与计算方法,为模型的发展和成长提供了依据。

基于RS和GIS的四川省土地利用/覆盖变化及可持续利用研究

LUCC是全球变化研究的核心主题之一，也是社会经济可持续发展的关键问题。改革开放后四川的社会经济发展非常快，在各种因素的驱动下，土地利用/覆盖发生了深刻变化。目前四川省缺乏基于实际调查数据的、全域性的、具有连续时间序列的LUCC和驱动力分析及土地可持续利用研究成果，这对我们从全局上把握全省土地利用现状、发展变化趋势，利用土地政策参与宏观调控，实现长期可持续发展目标，建设资源节约型、环境友好型社会极为不利。本研究针对这一问题，选取全川八大土地利用类型作为研究对象，研究了全省1996年到2006年的土地利用/覆盖格局和变化情况，分析了不同尺度的驱动因素，对全省农用地和建设用地的集约利用状况、潜力进行了分析评价，并提出相应的对策措施。 1．1996年-2006年10年来整个省域的土地利用/覆盖格局变化。 （1）1996年-2006年全省的土地利用/覆盖格局 1996年，全省是一个以农用地为主的土地利用/覆盖格局，林地和牧草地属于优势覆盖类型（合占69.17%），居民点及工矿用地和交通用地合占只有3%左右。 2000年的LUCC格局较为明显的特点是耕地所占比重下降0.4个百分点，水域和未利用土地所占比重有所下降，牧草地保持不变，其余地类所占比重有所上升。 与2000年相比，2004年林草地的优势格局进一步得到强化（合占比重达到70.23%）。耕地面积占幅员面积的比重下降0.83个百分点，略有下降的有未利用土地、水域和牧草地。值得关注的是在“退耕还林还草”的大背景下，牧草地占幅员面积的比重下降0.04个百分点。 到2006年，仍为林草地为主导优势的格局，二者合占上升0.15%。在城市化快速推进的背景下，居民点及工矿用地中的城市用地和建制镇用地占比重超过15%，农村居民点占比重降至76%。交通用地中农村道路占比重降至57.8%,公路用地占比重升至37.5%。五个地貌区的土地利用/覆盖格局与全省的变化基本一致。值得关注的是盆西平原区的交通用地上升幅度和盆地丘陵区的未利用土地的开发利用力度明显大于其它地貌区。 （2）1996-2006年10年间土地利用/覆盖格局的变化 1996-2000年4年间，耕地、水域和未利用地三个地类下降，年均减少0.75、0.19和0.32个百分点。其中耕地年均减少49229.0公顷，约一半流向林地，13.77%流向园地，约20%流向建设用地。另外5个地类面积增长，增长绝对量最大的是林地，年均增长40063.7公顷，交通用地增幅最大，4年年均增长达1.95%。 2001-2004年是西部大开发逐步推进、“退耕还林还草”项目全面展开和土地整理深入实施的关键期，LUCC更为深刻。耕地、未利用地、水域和牧草地四个地类面积下降，其余地类按增长幅度依次是园地、交通用地、居民点及工矿用地和林地。耕地加速下降，年均降幅达到1.59%，其减少去向主要是林地（占66.75%）和园地（占19.84%），其增加来源主要是未利用地、园地和水域。交通用地的增幅最大，为3.96%,其增加主要来源于耕地、未利用土地和林地，分别占49.96%、16.63%和13.09%。居民点及工矿用地增长幅度为3.12%。 从1996年到2006年的10年间，耕地、未利用地、水域和牧草地下降幅度分别为10.36%、3.61%、1.34%和0.26%。园地增幅达23.61%。绝对面积增长最大的则是林地，达630733.3公顷。交通用地和居民点及工矿用地增幅也较大，分别为15.00%和9.31%。 10年间年均总变化量为310326.6公顷，2000年-2004年之间变化最大（为356865.8公顷），高于平均变化量，而1996-2000年间和2004-2006年间都小于平均变化量。 （3）10年间不同地貌区的LUCC变化 盆西平原区的特点是园地大幅上升达77%，居民点及工矿用地和交通用地也大幅上升，耕地、未利用地下降幅度大，该区耕地、水域、未利用地的减少强度和园地、居民点及工矿用地、交通用地的上升强度均居五区第一；盆地丘陵区的特点是牧草地下降幅度大，为-36.89%,交通用地、园地和林地上升幅度较大，该区耕地减少、未利用地减少、林地增加、居民点及工矿用地和交通用地增加的变化强度均居五区相应地类增减的第二位；盆周山地区的特点是耕地减少较多，交通用地和园地增长较大，该区林地变化强度居各区第一位，牧草地和水域变化强度居各区第二位，耕地、居民点及工矿用地和未利用地居各区第三位；川西南山地区的特点是园地、耕地、交通用地和居民点及工矿用地变化幅度大，另外四个地类变化较小。该区减少的牧草地占全省牧草地减少的97.91%，变化强度居各个地貌区的第一位，园地相对变化强度居五区的第二位；川西北高山高原区的特点是耕地大幅下降、园地大幅上升，交通用地升幅也较大，其余地类变化不大。值得注意的是，该区牧草地和水域面积增加，与全省该地类的变化相反。其余地类的相对变化强度均是五个地貌区中最小的。 用变化强度分值考量变化强度，盆西平原区的变化强度最大，盆地丘陵区和盆周山地区的变化强度相当，川西北高山高原区的变化强度则要小得多。 （4）1996年及2006年全省土地利用/覆盖格局的景观生态学分析 全省是以自然景观占优势（占约70%）、农业景观为补充、建设用地景观居于从属地位的土地利用景观格局。景观多样性和均匀度不高。到2006年，全省总的景观格局并无大的改变。总体情况是随着时间的推移和人类活动的加强，区内景观优势度上升、多样性和均匀度变小。但斑块数减少，斑块面积和斑块孔隙度有所增大。斑块的形状指数和分维数均有所下降，表明受人为干扰有加剧的趋势。反映景观格局结构的破碎度指数有轻微下降。景观指数的变化表明全省土地利用有缓慢集中、规模聚集的趋势。 （5）三大生态建设工程对土地利用/覆盖变化的影响 1996-2006年间LUCC与三大生态建设工程实施的耦合分析，发现退耕工程对耕地、林地、牧草地等地类覆盖变化的影响最大，天保工程次之，长防工程最小。 2.四川省LUCC驱动力分析 （1）总体分析： 从整体上分析，人为因素对区域整体LUCC的影响从1996年的63.32%增加到2006年的66.99%，变得日益强烈。同时人为因素影响强度表现出明显的区域差异，地势平缓、经济区位条件好的区域其人为影响强度明显较高。 政策体制转变下的经济高速增长、快速的城市化、工业化过程和生态建设是四川省LUCC宏观尺度的驱动因素。区域的LUCC主要受到了由内向外(从城市到乡村)和由外向内(从山顶向平地)两种作用力的共同推动。局部尺度上，如距离交通线、水利线、中心城市的远近，地形凸起、大型独立项目落址、重污染项目的阻隔等，甚至一些乡规民俗等因素也会成为LUCC的驱动影响因素。在较小的尺度上,人类个体行为选择对LUCC的影响也是存在的。 　　根据驱动因子的特性作者将其划分为驱变、阻变、良性、惰性因子等类型。 （2）分地貌区的驱动因子分析 各地貌区都存在城市化、工业化、生态工程实施、自然灾害等驱动因子，但主次不一。对于盆西平原和盆地丘陵区，城市化、工业化是前两位的因子，而对另外三个地貌区，生态工程实施和产业结构调整则成为第第一、二位的驱动因子。 （3）分地类的驱动因子分析（以坡耕地为例） 分坡度的耕地变化分析发现，耕地减少主要集中在2°以下的平地、15°-25°和25°以上三个坡度级，是其它坡度级耕地减幅的三倍左右。这表明耕地减少受城市化进程和“退耕还林还草”工程驱动影响尤为巨大。 3.土地利用格局优化、集约利用评价和可持续利用及对策研究 （1）土地利用格局优化的战略选择及调整预测 土地利用格局调整的战略是农业生产用地、建设用地和生态及其他用地占幅员的比重分别稳定在13%、7%和80%左右，重点是三大类别内部二级和三级地类的合理调整。 （2）全省土地集约利用评价 全省农用地利用集约度为0.46，总体上集约度不高，处于较适度利用阶段。建设用地利用集约度为0.38，处于较适度利用阶段。集约利用提升空间较大。 农用地的潜力主要在于加强土地保育、完善利用制度、提高单产。城市建设用地的包括存量潜力、强度潜力、结构潜力，空间很大。农村居民点整理潜力可以逐步挖掘。 （3）新增建设用地集约利用的统筹安排 据测算，到2020年，四川省城市建设用地需求量在463850-492360hm2之间，城镇各业新增建设用地规模为361276.79hm2，占用耕地200565.94 hm2。2004-2020年间四川省农村居民点整理潜力33.86万hm2。农村居民点建设用地需求量为70.57万公顷。 （4）土地集约利用措施与坡耕地可持续利用战略 提出了土地集约利用的措施。在对坡耕地生态系统结构与功能分析的基础上，提出坡耕地可持续利用战略与生态恢复战略，并从技术和政策层面提出了坡耕地合理利用和生态退耕的措施和建议。 LUCC is one of the key questions of global change and sustainable development of society. After the opening and reform of China, the society and economy of Sichuan Province developed very fast ,the land-use/cover changed very strong droved by many factors .But nowadays we have no constant spatial-temporal study and driving force analysis about the whole province based on investigation. And it is lack of land sustainable utilization study based on correlative study. So we choose all the land resource in Sichuan, combine RS and GIS and field investigation, and take statistic-mathematic means and system analysis, to study the LUCC patterns and different scale driving force of different physiognomy regions, land cover types and periods; to analyze the current situation and potential of land resource intensive utilization, and gave out corresponding measurements. We found that forest and grassland are the dominant cover types of Sichuan provincial land –use/cover pattern, and becoming more and more stronger from 1996 to 2006,the natural landscape is the metric and occupy 70%,the diversity and evenness index are not high; the totally change quantity from 2000 to 2004 is the biggest; cultivated land especially steep cultivated land ,garden plot, forestry land ,settlement and industry land and traffic land changed relative stronger; among five physiognomy regions ,the changing intensity of PEN XI PING YUAN QU is the biggest, CHUAN XI BEI GAO SHAN GAO QU is smallest; under the background of policy system changing, the fast developing of economy, fast urbanization and industrialization and ecology construction are the macro-scale driving force of Sichuan provincial LUCC; to compare the impacts of “TUI GENG GONG CHENG” on LUCC especially to cultivated land ,forestry land and grassland is strongest, “TIAN BAO GONG CHENG ” is stronger,“ HANG FANG GONG CHENG” is smallest; the intensive utilization level of farmland and construction land of whole province is relative moderation, there is huge potential to excavate and fulfill the increasing demand of construction land；we must take synthetic measurements to accelerate the sustainable utilization of land resource, including administrative, economical ,technological and ecological policies.