Trade-offs between carbon,water, soil and food in Guanzhong-Tianshui economic region from remotely sensed data

It is important to ensure the efficient supply of land ecosystem services when the competition for land is increasing. In this paper we simulated the ecosystem services function under two scenarios, including carbon sequestration, agricultural production, water and soil conservation, and analyzed the tradeoffs among these ecosystem services in Guanzhong-Tianshui region from 2000 to 2050. Then the productive efficiency of ecosystem services was assessed under two scenarios and compared their production possibility frontiers (PPFs). Through the simulation analysis of their optimum allocation, we also provide the scientific evidence to the development of ecosystem. The natural rules were revealed that if these trade-offs emphasize the potential to sequester carbon in the landscape, along with very little loss of agricultural production, much more water is used. It could be identified to adhere to combine the exploitation and utilization, remediation and protection for land to promote the effective circulation of land eco-system, and meet the society’s preferences for land ecosystem service function by adjusting the use of multiple eco-services.     

Local spatial context measurements used to explore the relationship between land cover and land use functions

Research making use of satellite data for land change science has developed in the last decades. However, analysis of land use has not developed with the same speed as development of new satellite sensors and available land cover data. Improvement of land use analysis is possible, but more advanced methods are needed which make it possible to link image data to analysis of land use functions. To make this linking possible, variable which affect farmer's long term decisions must be taken into account in analysis as well as the relative importance of the landscape itself.A GIS-based tool for the measurement of local spatial context in satellite data is presented in this paper and used to explore the relationship between land covers present in satellite data and land use represented in official databases. By the use of the developed tool, a land configuration image (LCI) over the Siljan area in northern Sweden was produced and used for analysis. The results are twofold. First, the produced LCI holds new information about variables that are relevant for the interpretation of land use. Second, the comparison with statistics of agricultural production shows that production in the study area varies depending on the relative land configuration. Villages consisting of relatively large-scale arable fields and less diverse landscape are less diverse in production than villages which consist of smaller-scale and more heterogonous landscapes. The result is especially relevant for land use studies and policymakers working on environmental and agricultural policies. We conclude that local spatial context is an endogenous variable in the relation between landscape configuration and agricultural land use.     

区域土地灌溉环境评价与决策分析

国土资源是人们赖以生存和发展的物质基础,土地灌溉环境作为国土资源调查的重要内容,其关键基础设施机井的空间配置对于农业生产具有重要的现实意义。本文以北京市通州区永乐店镇为研究区,基于国土资源调查的多源空间数据,提出了一种对现有土地灌溉环境进行定量评价和优化决策的方法。结果表明,研究区既有机井配置有待进一步改进,优化方案给出的183口新增机井合理分配在优化单元内,能够满足当地农民的土地灌溉需求,同时为土地灌溉环境中机井的更新配置提供了依据。     

Change detection: how has urban expansion in Buenos Aires metropolitan region affected croplands

Cropland is one of the essential elements of our ecological systems for producing agricultural products. In developing countries, urban expansion is a frequently appearing phenomena, which is a type of land cover land use (LCLU) change. This change can drastically alter the features on the land surface including croplands. It can lead to detrimental consequences which has considerable effects on the social-ecological systems when croplands are lost. Argentina is an extremely agricultural intense developing country, and Buenos Aires province is a top agricultural production site and has been urbanizing during the last 30 years. Thus studying and analyzing the metropolitan area of this province will contribute to our understanding of the relationship between urban expansion and its effect on croplands. So far, no research has used measurable quantitative methodologies on the Buenos Aires metropolitan region (BAMR) to reveal the relationship between urbanization and cropland. By using 30-meter resolution Landsat images of June 1985 and July 2015, this study finds urban land has expanded from 937.16?km² to 1835.47?km², and 30.28% of the new urban lands comes from existing croplands.     

Integrating multiple land cover maps through a multi-criteria analysis to improve agricultural monitoring in Africa

Monitoring agricultural land cover is highly relevant for global early warning systems such as ASAP (Anomaly hot Spots of Agricultural Production), because it represents the basis for detecting production deficits in food security assessment. Given the significant inconsistencies among existing land cover datasets, there is a need to obtain a more accurate representation of the spatial distribution and extent of agricultural area in Africa. In this research, we explore a fusion approach that combines the strength of individual datasets and minimises their limitations. Specifically, a semi-automatic method is developed, relying on multi-criteria analysis (MCA) complemented with manual fine-tuning using the best-rated datasets, to generate two hybrid and static agricultural masks – one for cropland and another for grassland. Following a comprehensive selection of land cover maps, each dataset is evaluated at country level according to five criteria: timeliness, spatial resolution, comparison with FAO statistics, accuracy assessment and expert evaluation. A sensitivity analysis is performed, based on an evaluation of the impact of weight settings on the resulting land cover. The proposed methodology is capable of improving agricultural characterisation in Africa. As a result, two static masks at 250 m spatial resolution for the nominal year 2016 are provided.     

基于目标规划与模拟退火算法的土地利用分区优化方法

以兰州市榆中县为实验区,选取分区适宜性、规划协调性和空间紧凑性作为分区目标,基于目标规划和模拟退火算法对实验区进行土地利用分区优化。结果表明,不同情景下的分区方案能很好地满足决策者设定的目标偏好值;从空间特征分析的结果看,本分区方案较原有分区方案对各个分区目标进行了优化,更好地满足了农业生产、经济发展以及生态保护的要求。     

Implementation of novel polygon-based obfuscation methods to improve privacy of agricultural data

Geoprivacy protection is a significant concern when sharing data. To support sustainable land management by leveraging existing agricultural data, research is needed to identify how the polygon nature of static field parcels can be obfuscated to allow data sharing among individuals and organizations. In this study, five adaptive polygon-based obfuscation methods including PN*Rand, PDonut-k, PDensity-k, PAHilb, and PDonut_AHilb methods were developed and applied on the Irish Nutrient Management Planning Online (NMP Online) agricultural dataset. The polygon-based obfuscation methods introduced in this study were designed with the consideration of properties of spatial polygon objects including the spatial coordinates, shape and size of the polygon, topology, and spatial relationship between adjacent polygons that can be used to identify real-world objects. These methods were developed to guarantee that there is no false-identification and non-unique obfuscation which is important for static polygon objects in terms of accuracy and privacy protection. Qualitative approaches were developed to identify the optimal values of inner and outer radii of donut shape based on k-anonymity satisfaction and subsequently obtain the optimal value of k-anonymity. Several evaluation methods were implemented to compare the methods performance. Density-based methods particularly PDonut-AHilb provide the best trade-off between field parcel confidentiality and spatial pattern preservation and should be considered for researchers and practitioners obfuscating polygon data.     

MAPGIS耕地综合生产能力评价研究

本文基于MAPG IS和农用地分等成果,运用模型法、系统分析方法,研究了耕地综合生产能力的评价方法,并以实际生产能力为本底,分别以利用生产能力和自然生产能力为预期,测算耕地生产能力的现实潜力和理论潜力,从而得出耕地生产能力及潜力的分布规律,并以扶风县为例进行了论证,提出了提高耕地综合生产能力的建议。     

Land cover classification and economic assessment of citrus groves using remote sensing

The citrus industry has the second largest impact on Florida's economy, following tourism. Estimation of citrus area coverage and annual forecasts of Florida's citrus production are currently dependent on labor-intensive interpretation of aerial photographs. Remotely sensed data from satellites has been widely applied in agricultural yield estimation and cropland management. Satellite data can potentially be obtained throughout the year, making it especially suitable for the detection of land cover change in agriculture and horticulture, plant health status, soil and moisture conditions, and effects of crop management practices. In this study, we analyzed land cover of citrus crops in Florida using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery from the University of Maryland Global Land Cover Facility (GLCF). We hypothesized that an interdisciplinary approach combining citrus production (economic) data with citrus land cover area per county would yield a correlation between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. While the data from official sources based on aerial photography were positively correlated, there were serious discrepancies between agriculture census data and satellite-derived cropland area using medium-resolution satellite imagery. If these discrepancies can be resolved by using imagery of higher spatial resolution, a stronger correlation would be observed for citrus production based on satellite data. This would allow us to predict the economic impact of citrus from satellite-derived spectral data analysis to determine final crop harvests.     

GIS辅助下的农村土地精细化管理与服务实践

粗放的农村土地管理方式已经不能适应社会的发展要求,特别是在经济发达地区,必须借助现代信息技术提升管理与服务水平。本文针对当前农业部门管理农村土地、服务农民和农业企业的现实需求,围绕农村土地承包经营、农村土地流转和土地生产需要,提出了基于GIS技术的农村土地精细化管理和信息化服务系统的建设目标、设计思路,重点阐述系统数据获取、数据库设计及系统实现与应用。对农村土地精细化管理与服务信息系统建设进行了有益的探索。     

沿边开放开发进程中农用地多功能性评价

农用地多功能利用是黑龙江省沿边开放带土地利用效率提升及生态经济协调发展的客观要求,农用地利用多功能性评价是其基础工作。该文系统地研究了农用地利用多功能性评价方法,测度了1996年、2004年、2013年黑龙江省农用地利用多功能状态及期间变化。研究表明,1996~2013年黑龙江省农用地利用总功能缓慢提高,多功能协调性逐步提升;农用地利用由单一功能逐渐向多功能转变。为扩大农用地利用多功能整体效应并提高农用地利用多功能协调性,稳定生产功能、加快提高经济功能、重点遏制生态功能退化、逐步提高社会功能是沿边开放带今后的农用地利用方向。     

江汉平原粮食产量空间格局分析

基于湖北省第一次地理国情普查数据、基础地理信息数据和统计年鉴等资料,采用洛伦兹曲线、Moran指数等对江汉平原典型4个粮食主产区监利县、洪湖市、仙桃市、潜江市的粮食产量空间格局进行了分析和研究。研究表明:①洪湖市耕地资源与粮食产量间的对应关系较为平等,粮食单产稳定,粮食生产空间聚集显著;②监利县、潜江市与仙桃市的耕地、粮食产量表现出极弱空间相关性或无相关性,粮食生产能力相对较差,耕地资源及产量未表现出空间聚集优势。该结论可为农业部门制定农业生产计划和发展规划提供良好的数据支撑,为地理国情普查成果的应用提供借鉴。     

Interpretation of crop growth patterns by means of NDVI‐time series in Zambia

A method to correlate crop production in Zambia to the yearly evolution of the Normalized Difference Vegetation Index (NDVI) is proposed. The method consists of the analysis of remote sensing data together with meteorological data and simulated crop production to obtain indicators of crop production. The accuracy of these indicators is assessed with statistical data.

The main objective was to assess whether the NDVI‐time series extracted from NOAA‐AVHRR‐images , having a pixel resolution of 73 km may give reliable information on crop production in Zambia where agricultural areas cover just 1% of the land area.

The mean NDVI‐value of several pixels, e.g. for one province or other administrative units, relates to the dominant type of vegetation in the area under consideration.

It is shown that the 7.3 km NDVI‐data give reliable indications on crop production in Zambia, when small areas (200–450 km² large ) are considered where agricultural land use is intensive. This implies that preliminary analysis is required to localize the agricultural areas. This has been done by means of high resolution satellite images i.e. LANDSAT‐MultiSpectral Scanner.

Consequently, the NDVI‐time series of the ‘agricultural ‘ pixels are used to calculate crop growth indicators which can be applied to assess the crop production.     

Precision Farming with Geoinformatics: A New Paradigm for Agricultural Production in a Developing Country

This paper critically evaluates conventional agricultural land suitability and appraisal methods in a developing country and points out their shortcomings. It also evaluates the new paradigm of precision farming with geoinformatics techniques and highlights the beneficial aspects to land use and agricultural production. In this context the paper shows that traditional physiographic, taxonomic, and land use systems prove inadequate while geoinformatics (using remote sensing data and GPS controlled point observations and soil sample data) work best in modern precision farming. An application of the new paradigm in the Orle River basin in Edo State, Nigeria is used to illustrate how precision farming strategies incorporating geoinformatics might be implemented in Africa.     

Quantifying Four Decades of Changes in Land Use and Land Cover in India’s Kailash Sacred Landscape: Suggested Option for Priority Based Patch Level Future Forest Conservation

Effective quantification of land cover changes remains a challenge in Himalayan hills and mountains, and has a colossal value addition for natural resource management. Here we present a new robust method for classifying land cover vegetation at physiognomic scale along steep elevational gradients from ~?200 to ~?7000 masl in the Kailash Sacred Landscape, Western Himalaya, India along with four decades of land use and land cover changes (1976–2011) using remote sensing techniques coupled with intensive ground surveys. Results show that forest cover loss was minimum ca 7.14% of existing forest in 1976; but, however forest fragmentation is high especially in montane broad-leaved and subtropical needle leaved forests. This change largely impacted the quality of valuable tree species such as Quercus spp. Post 1976, continuous migration forced conversion of high altitude agricultural lands into grasslands and scrublands. Human settlement expansion was high especially in low altitudinal range valleys between 1000 and 2000 masl and has increased 6.76 fold since 1976, leading to high forest fragmentation in spite of reduced agriculture area in the landscape. Our physiognomic level classified land cover map will be a key for forest managers to prioritize conservation zones for protecting this unique forest land.     

Integrated approach of using remote sensing and GIS to study watershed prioritization and productivity

Soil data obtained from soil resource inventory, land and climate were derived from the remote sensing satellite data (Landsat TM, bands 1 to 7) and were integrated in GIS environment to obtain the soil erosion loss using USLE model for the watershed area. The priorities of different sub-watershed areas for soil conservation measures were identified. Land productivity index was also used as a measure for land evaluation. Different soil and land attribute maps were generated in GIS, and R,K,LS,C and P factor maps were derived. By integrating these soil erosion map was generated. The mapping units, found not suitable for agriculture production, were delineated and mapped as non-arable land. The area suitable for agricultural production was carved out for imparting the productivity analysis; the land suitable for raising agricultural crops was delineated into different mapping units as productivity ratings good, fair, moderate and poor. The analysis performed using remote sensing and GIS helped to generate the attribute maps with more accuracy and the ability of integrating these in GIS environment provided the ease to get the required kind of analysis. Conventional methods of land evaluation procedures in terms of either soil erosion or productivity are found not comparable with the out put generated by using remote sensing and GIS as the limitations in generating the attribute maps and their integration. The results obtained in this case study show the use of different kinds of data derived from different sources in land evaluation appraisals.     

城市化的农用地评价比较研究——以南京市江宁、六合区为例

我国城市化步入快速发展时期,城市用地的迅速增长,使得大量的农用地正在快速转变为非农业用地。本文以GIS技术为核心,在快速城市化的背景下,综合考虑农用地的经济价值和社会价值影响因素,建立评价模型,通过对南京市江宁区和六合区为例进行实证比较研究,探索农用地评价的方法和规律,为农用地的征用、整理、分等、定级和估价提供一定科学依据。     

A combined deficit index for regional agricultural drought assessment over semi-arid tract of India using geostationary meteorological satellite data

The untimely onset and uneven distribution of south-west monsoon rainfall lead to agricultural drought causing reduction in food-grain production with high vulnerability over semi-arid tract (SAT) of India. A combined deficit index (CDI) has been developed from tri-monthly sum of deficit in antecedent rainfall and deficit in monthly vegetation vigor with a lag period of one month between the two. The formulation of CDI used a core biophysical (e.g., NDVI) and a hydro-meteorological (e.g., rainfall) variables derived using observation from Indian geostationary satellites. The CDI was tested and evaluated in two drought years (2009 and 2012) within a span of five years (2009–2013) over SAT. The index was found to have good correlation (0.49–0.68) with standardized precipitation index (SPI) computed from rain-gauge measurements but showed lower correlation with anomaly in monthly land surface temperature (LST). Significant correlations were found between CDI and reduction in agricultural carbon productivity (0.67–0.83), evapotranspiration (0.64–0.73), agricultural grain yield (0.70–0.85). Inconsistent correlation between CDI and ET reduction was noticed in 2012 in contrast to consistent correlation between CDI and reduction in carbon productivity both in 2009 and 2012. The comparison of CDI-based drought-affected area with those from existing operational approach showed 75% overlapping regions though class-to-class matching was only 40–45%. The results demonstrated that CDI is a potential indicator for assessment of late-season regional agricultural drought based on lag-response between water supply and crop vigor.     

基于阜新市的土壤多样性与土地利用类型关联性分析

以阜新市为研究对象,将土地利用动态演变的模拟和预测以及关联分析测度方法应用于土壤多样性和土地利用类型关联性分析的研究中。选取1985—2015年间8个时期的遥感影像进行土地利用分类,并基于土壤矢量数据,对阜新市土壤和土地利用的多样性进行初步分析和定量化研究,探究了土壤与土地利用之间的关联性。研究结果表明:对阜新市土壤多样性指数影响因子的关联度从大到小依次是城镇、农用地、林地、水域、其他,关联度值分别为0.850 6、0.747 7、0.779 5、0.803 3、0.641 9,选取城镇、农用地、林地和水域这4个因子作为多元线性回归模型中的自变量参数,对土壤多样性指数进行预测,得到相关系数R=0.990,因此,4个因子对土壤多样性指数影响具有较强的关联性。由此可见,大规模土地利用变化是引起土壤多样性变化的一个首要驱动因子。     

基于NDVI时间序列数据的江西省水稻种植制度变化研究

利用Savitzky-Golay滤波对覆盖江西省范围的SPOT VGT NDVI时间序列数据进行平滑处理的基础上,结合坡度数据,通过非监督分类的方法提取了江西省2000、2005和2010年水稻种植范围,并根据NDVI的年内动态变化,从水稻种植范围、水稻生长季起始时间、水稻复种指数和NDVI最大振幅等分析了江西省水稻种植和生长情况,探讨2000~2010年江西省水稻生产的变化。