Analysis of urban landuse change using sequential aerial photographs and spot data: An example of north Bhubaneswar,Orissa

As urban area undergoes a rapid change it will be necessary to review development and the urban plans once in five years in relation to important public and other decisions taken from time to time. In order to know the trend of development and landuse patterns, analysis of sequential aerial photographs and satellite imagery of different years can be a useful tool for interpretation of various landuses and their comparison, In the present study an attempt has been made to understand the change detection using sequential aerial photographs of 1974 and 1989, and comparison with SPOT data of I988 with the help of ‘USEMAP’ GIS software package.     

联合像元-深度-对象特征的遥感图像城市变化检测

特征空间的构建和优化对遥感图像识别能力的提高具有重要作用。针对面向对象方法对波段光谱信息利用不足,以及像元识别法无法充分利用图像空间几何等信息的问题,本文建立了新颖的联合像素级和对象级特征的航摄遥感图像城市变化检测方法。首先,充分利用像素级和对象级特征的优势,建立考虑光谱、指数、纹理、几何、表面高度及神经网络深度特征的特征空间;然后,引入LightGBM(light gradient boosting machine)算法对大量特征进行选择研究;最后,采用随机森林识别器对宜兴市2012年和2015年两期遥感图像进行识别,利用变化矩阵进行城市的变化检测。结果表明:联合像元、深度、对象特征和LightGBM特征选择算法的识别效果最好,平均的总体识别精度达到了88.50%,Kappa系数达到0.86,比基于像元、深度或对象特征的识别方法分别提高了10.50%、15.00%和4.00%;城市变化检测精度达到了87.50%。因此,本文方法是利用甚高分辨率航摄遥感图像进行城市变化的检测的有效方法。     

Study of landforms,land use and land units of a part of Krishna district,Andhra Pradesh,from aerial photographs

Utilising aerial photographs as the chief source of information an attempt has been made to study the land units, land use, land capability and limitations in relation to geomorphology of an area of about 350 sq. kms. in Krishna district of Andhra Pradesh. Besides identifying major individual landforms, the area is divided into four geomorphic environments each characterised by dominant landform pattern and relief. Each form and unit is described. Nine types of land units based on amount of slope and six land use classes were chosen after preliminary interpretation and a reconnaissance field check. The estimated range in slope is given for each land unit. The land’s capability and limitations are brought out from consideration of landforms, land units (slopes), nature of soil and water resources. Soil samples were collected from each geomorphic unit and analysed. The results are presented in the form of 3 maps and 2 tables, which may be of use for planning and development of the area.     

Study of drainage profiles in Jharia Coalfield,eastern India from aerial photographs: Implication for land use planning

Drainage analysis of an area through aerial photographs helps a lot in knowing its soil textrue, mainly its porosity, permeability, grainsize and compactness. These observations may be used as a guide for land use planning over the area. Studies have been conducted in Jharia Coalfield through scanning of acrial photographs to know the textural characters of soil/rock cover over the area. Nature of valley profiles have been studied in detail. The overall drainage pattern and drainage texture have also been studied. The observation have been used to infer about the textue of the materials (rock/soil) traversed by the drainage lines in the region. The observations suggest that the major part of the field is covered by materials of moderate cohesiveness with good porosity, permeability and recharge capacity. These informations have been used as critical inputs for future land use planning in the area.     

Urban land use mapping: A case study of ahmedabad city and its environs

Proper urban planning and effective implementation requires reliable urban land use statistics. In this context, satellite remote sensing data has been studied using both visual and digital techniques. A portable eight-band radiometer has been used to collect spectral signatures of surface features present in Ahmedabad city and its environs. Using these signatures a suitable approach employing visual and digital techniques has been developed for urban land use/sprawl mapping. Urban land-use maps of Ahmedabad city and its environs were prepared on 1:25,000 scale and for Ahmedabad Urban Development Authority Area on 1:50,000 scale using this methodology. It has been found that edge-enhancement techniques are useful to enhance the contrast among different urban land uses. Classification techniques such as MXL and Bayes classifiers are not successful in discriminating urban land uses. Tonal characteristics alongwith other elements of interpretation are required to classify urban land uses such as residential, industrial etc. Spatial distribution of various urban and uses and the space devoted to each urban land use has been brought out.     

Morphometric analysis of a drainage basin using aerial photographs: A case study of Khairkuli basin,district Dehradun,U.P.

Remote sensing techniques using satellite images and aerial photographs are convenient tools in morphometric analysis of a drainage basin. In the present study morphometric parameters of Khairkuli drainage basin, district Dehradun, are worked out using aerial photographs. The parameters worked out include bifurcation ratio, stream length, form factor, circulatory ratio, elongation ratio, drainage density, constant of channel maintenance and stream frequency. Hypsometric relations of drainage basin are also presented. Relation between cumulative stream length and the stream order establishes that the ratio between cumulative stream length Σ ₁ ^u Σ ₁ ^nu Lu and the stream order u is constant throughout the. successive orders of a drainage basin suggesting that geometrical similarity is preserved in the basins of increasing order. The morphometric parameters computed suggest that the area is covered by resistant permeable rocks (with fracture and karstic porosities) and vegetative cover, the drainage network is affected by tectonic disturbances. The peak flows generated from the basin are likely to be moderately high and of short duration.     

Wavelet-based detection of bush encroachment in a savanna using multi-temporal aerial photographs and satellite imagery

Although increased woody plant abundance has been reported in tropical savannas worldwide, techniques for detecting the direction and magnitude of change are mostly based on visual interpretation of historical aerial photography or textural analysis of multi-temporal satellite images. These techniques are prone to human error and do not permit integration of remotely sensed data from diverse sources. Here, we integrate aerial photographs with high spatial resolution satellite imagery and use a discrete wavelet transform to objectively detect the dynamics in bush encroachment at two protected Zimbabwean savanna sites. Based on the recently introduced intensity-dominant scale approach, we test the hypotheses that: (1) the encroachment of woody patches into the surrounding grassland matrix causes a shift in the dominant scale. This shift in the dominant scale can be detected using a discrete wavelet transform regardless of whether aerial photography and satellite data are used; and (2) as the woody patch size stabilises, woody cover tends to increase thereby triggering changes in intensity. The results show that at the first site where tree patches were already established (Lake Chivero Game Reserve), between 1972 and 1984 the dominant scale of woody patches initially increased from 8 m before stabilising at 16 m and 32 m between 1984 and 2012 while the intensity fluctuated during the same period. In contrast, at the second site, which was formely grass-dominated site (Kyle Game Reserve), we observed an unclear dominant scale (1972) which later becomes distinct in 1985, 1996 and 2012. Over the same period, the intensity increased. Our results imply that using our approach we can detect and quantify woody/bush patch dynamics in savanna landscapes.     

Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California

Observing dynamic change patterns and higher-order complexities from remotely sensed images is warranted, but the main challenges include image inconsistency, plant phenological differences, weather variations, and difficulties of incorporating natural conditions into automatic image processing. In this study, we proposed a new algorithm and demonstrated it by producing 2002–2008 and 2010 land-cover maps in heterogeneous Southern California based on an existing 2009 land-cover map. The new algorithm improves the baseline land-cover map quality by discarding potential bad land-cover pixels and dividing each land-cover type into several subclasses. Time series Landsat images were used to detect changed and unchanged areas between baseline year and target year t. Subsequently, for each individual year t, each pixel that was identified as unchanged inherited the baseline classification. Otherwise, each pixel in the changed areas was classified by a similar surrogate majority classifier. The demonstration results in Southern California showed that the land-cover temporal pattern captured the observed successional stages of the ecosystem very well. The accuracy assessment had an overall classification accuracies ranging from 81% to 86% and overall kappa coefficients ranging from 0.79 to 0.83.     

Soil mapping and land use plan in tehri-garhwal district,uttar pradesh,using aerial photo-interpretation technique,highlighting soil-landscape relationship and land utilization

Soil mapping on the scale 1:50,000 was conducted in Tehri-Garhwal district of Uttar Pradesh using Survey of India Topographic maps and utilising aerial photographs of the area which were interpreted for demarcation of physiographic units, vegetation, drainage and other features relevant to soil development. Resulting soil map and soils and land use information have been helpful in presenting an optimum land use and management plan in the area keeping in view of the soils characteristics, terrain features and existing land use, Soils and physiographic interpretation in the area have highlighted significant soil-landscape relationships relevant to land utilization. The other factors responsible for soil formation which could be significant in the area i.e. climate and parent material were also taken into consideration apart from topography. Of all these factors topography was revealed to be the predominant factor governing soil formation in the area. Soil units mapped coincided with the physiographic units demarcated through aerial photo-interpretation. The area of the district could be divided into three climatic zones viz. (i) Cool temperate, (ii) Sub-tropical warm temperate and (iii) tropical following Kaushic (1962). It was noticed that in each climatic zone with the climate being almost uniform within the zone, irrespe tlve of variations in the parent material, soil development was markedly affected by topographly, variations which led to differences in soil characteristics particulary soil texture and amount of coarse fragments. In about 70 percent of the area of the district where slopes are steep to very steep, topography was revealed to be the dominant factor determining characteristic soil development. In the remaining part where slopes are moderate to gentle, parent material is the dominant factor followed by topography.     

Identification and delineation of saline soils using aerial photographs in Yamuna Alluvial plain,Haryana

Salinity is creating great problems in the Yamuna Alluvial Plain. State Government is taking steps for reclaiming these lands to increase agricultural production. Impeded drainage, excess canal irrigation, topography parent material, shallow depth and bad quality of ground water are the main factors which are responsible for the genesis of saline soils in the alluvial plains of Haryana. On the arial photographs tonal differences on account of salt concentration in the soil are clearly seen. These differences are aslo associated with physiography and soil conditions which can be easily delineated. The information thus; collected can be used for reclamation of saline soils.     

通过软硬变化检测识别冬小麦

提出一种软硬变化检测的作物识别方法 SHLUCD(Soft and Hard Land Use/Cover Change Detection Method)。该方法利用多期遥感影像能够有效表达作物的生长物候特征,以达到在离散变化区(即纯净像元区,包括完全转换成作物的突变区域和非作物区域)和连续变化区(即渐变区,混合像元区,是部分转化为作物的区域)准确进行作物的识别。在北京市选择一个研究区,以冬小麦为研究对象,选用2011年10月6日(播种期)和2012年4月16日(拔节期)两期环境减灾1号卫星影像,分别采用硬变化检测方法 HLUCD(Hard Land Use/Cover Change Detection Method)、软变化检测方法 SLUCD(Soft Land Use/Cover Change Detection Method)和SHLUCD进行冬小麦的识别。实验结果表明:在不同尺度窗口下,SHLUCD较传统方法表现出较明显的优势,具有更低的均方根误差RMSE(SHLUCD为[0.14,0.07],HLUCD为[0.15,0.07],SLUCD为[0.16,0.08])和偏差bias(SHLUCD为-0.0008,HLUCD为-0.007,SLUCD为0.014)和更高的决定系数R2(SHLUCD为[0.68,0.86],HLUCD为[0.62,0.86],SLUCD为[0.60,0.86])。针对冬小麦突变区域、冬小麦渐变区域和非冬小麦区域分别进行评价,表明SHLUCD识别精度接近各区最佳的识别方法,进一步验证了SHLUCD的灵活性和适用性。SHLUCD方法在离散变化区能够通过土地覆盖类型状态变化来有效地识别出冬小麦,在连续变化区可识别出土地覆盖的状态变化程度定量表达冬小麦的丰度,是其他作物多时相遥感变化检测的前期实验基础。     

Evaluation of image fusion methods using PALSAR,RADARSAT-1 and SPOT images for land use/ land cover classification

This research aimed to explore the fusion of multispectral optical SPOT data with microwave L-band ALOS PALSAR and C-band RADARSAT-1 data for a detailed land use/cover mapping to find out the individual contributions of different wavelengths. Many fusion approaches have been implemented and analyzed for various applications using different remote sensing images. However, the fusion methods have conflict in the context of land use/cover (LULC) mapping using optical and synthetic aperture radar (SAR) images together. In this research two SAR images ALOS PALSAR and RADARSAT-1 were fused with SPOT data. Although, both SAR data were gathered in same polarization, and had same ground resolution, they differ in wavelengths. As different data fusion methods, intensity hue saturation (IHS), principal component analysis, discrete wavelet transformation, high pass frequency (HPF), and Ehlers, were performed and compared. For the quality analyses, visual interpretation was applied as a qualitative analysis, and spectral quality metrics of the fused images, such as correlation coefficient (CC) and universal image quality index (UIQI) were applied as a quantitative analysis. Furthermore, multispectral SPOT image and SAR fused images were classified with Maximum Likelihood Classification (MLC) method for the evaluation of their efficiencies. Ehlers gave the best score in the quality analysis and for the accuracy of LULC on LULC mapping of PALSAR and RADARSAT images. The results showed that the HPF method is in the second place with an increased thematic mapping accuracy. IHS had the worse results in all analyses. Overall, it is indicated that Ehlers method is a powerful technique to improve the LULC classification.     

Modelling of land use land cover change using earth observation data-sets of Tons River Basin,Madhya Pradesh,India

Abstract

An integrated Markov Chain and Cellular Automata modelling (CA MARKOV), multicriteria evaluation techniques have been applied to produce transition probability. The unsupervised method was employed to classify the satellite images of year 1985, 1995, 2005 and 2015 to meet the magnitude of LULC change. Results showing the spatial pattern of the sub-basin is largely influenced by the biophysical and socio-economic drivers leading to growth of agricultural lands and built-up area in the basin. Simulated plausible future LULC changes for 2025 which is based on a CA MARKOV that integrates Markovian transition probabilities computed from satellite-derived LULC maps and a CA contiguity spatial filter (5 × 5). Further, the fragmentation analysis was performed to check the fragmentation scenario in the year 2025. The result for year 2025 with reasonably good accuracy will be useful to the planners, policy- and decision-makers.     

城市用地空间信息分类与数字重建——以长春百年城市内部用地变化为例

针对单一应用遥感影像难以进行城市内部用地结构分类以及高精度城市内部用地多期空间数据叠置分析中位置误差问题建立了基于"分层分类"与"对象分割"的城市内部用地空间信息数字重建方法。实现对特大城市产业用地(住宅、商业、工业等)以及交通、水系、生态绿地等不同功能结构用地的高精度监测以及历史演变过程的重建。综合集成SPOT5,1︰1万地形图、历史地图及城市规划图等辅助信息对长春城市1905年以来城市用地信息进行分类。研究表明,在专家知识参与下人—机交互解译,集成多源空间信息对实现高精度城市用地空间信息重建具有较高的应用价值,该方法不仅能提高城市用地分类精度而且能提高城市用地空间信息提取效率以及多期空间数据叠置分析的定位精度。     

Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng,China

Simulations of intra-urban land use changes have gradually attracted more attention as these approaches are extremely helpful in regard to decision making and policy formulation. While prior studies mostly focused on methods of developing intra-urban level simulations, very little research has been conducted explain the factors driving intra-urban land use change. Urban planners are highly concerned with how inner-city structures are formed and how they function. Here, to simulate multiple intra-urban land use changes and to identify the contribution of different driving factors, we developed a random forests (RF) algorithm-based cellular automata (CA) simulation model. In this study, the model applied diverse categories of spatial variables, including traffic location factors, environmental factors, public services, and population density, as the driving factors to enhance our understanding of the dynamics of internal urban land use. The CA model was tested using data from the Huicheng district of Huizhou city in the Guangdong province of China. The Model was validated using actual historical land use data from 2000 to 2010. By applying the validated model, multiple intra-urban land use maps were simulated for 2015. Simultaneously, spatial variable importance measures (VIMs) were calculated by using the out-of-bag (OOB) error estimation approach of the RF algorithm. Based on the calculation results, we assessed and analysed the significance of each intra-urban land use driver for this region. This study provides urban planners and relevant scholars with detailed and targeted information that can aid in the formulation of specific planning strategies for different intra-urban land uses and support the future evolution of this area.     

Glacier and glacial lake classification for change detection studies using satellite data: a case study from Baspa basin,western Himalaya

Using high-resolution Google Earth^TM images in conjunction with Landsat images, the glaciers and lakes in the Baspa basin are classified to explore the recent changes. A total number of 109 glaciers (187 ± 3.7 km²) are mapped and subsequently classified as compound valley glaciers, simple valley glaciers, cirques, niches, glacieretes and ice aprons. The compound and simple valley glaciers contribute 67.1 ± 1.3% and 19.8 ± 0.3% to the total glacier cover of the basin. Similarly, a total number of 129 glacial lakes (0.360 ± 0.007 km²) are identified. From 1976 to 2011, the compound valley glaciers have lost a small area of 10.3 ± 0.03% at a rate of 0.41 ± 0.002 km² a^-1, whereas the niche glaciers have lost higher area of 40.1 ± 0.001% at a rate of 0.04 ± 0.0001 km² a^-1. Change detection of two benchmark glacial lakes revealed a progressive expansion during recent decades. The Baspa Bamak proglacial lake has expanded from 0.020 ± 0.0004 km² (2000) to 0.069 ± 0.001 km² (2011). Due to the complete loss of source ice, another glacial lake has expanded from 0.09 ± 0.001 km² (1994) to 0.10 ± 0.002 km² (2011). During the study period, the mean annual temperature that is T_avg, T_min and T_max have increased significantly at the 95% confidence level by 1.5 ^oC (0.070 °C a^-1), 1.8 ^oC (0.076 °C a^-1) and 1.6 ^oC (0.0071 °C a^-1) from 1985 to 2008. However, the precipitation has decreased significantly from 1976 and 1985 to 2008.     

Landsat mss data for land use and land cover inventory and mapping: A case study of Andhra Pradesh

This study deals with the technique of remote sensing and how far it helps in the rapid study of geographical phenomena especially land use within a very short time and accurate manner. It evaluates how well data from the Landsat - Multispectral Scanner (MSS) could be used to detect, identify and delineate land use features within the Andhra Pradesh State. The main objective was to prepare a small scale land use map from satellite imagery showing the broad distribution of land use patterns to serve as a base for monitoring land use change.     

Illegal land use change assessment using GIS and remote sensing to support sustainable land management strategies in Taiwan

Land use is changing at accelerated rates in Taiwan, and illegal land use change practices (ILP) are regularly observed within conservation areas. For this reason, we map high-potential areas of ILP within the Soil and water conservation zone (SWCZ) as an aid for effective land management and conducted an exploratory analysis of explanatory variables to evaluate their variability within ILP hot spots. We used variables relevant to hot spots to develop a logistic regression model and identified seven statistically significant variables. We re-applied the logistic regression approach to produce spatially explicit predictions of ILP. High probability areas are distributed along the coastal regions, covering 26% of the SWCZ, and their major drivers are related to accessibility and topography. The results from this research provide relevant information on the major drivers of ILP and high-potential areas, which can support officials in monitoring efforts for better planning and governance within the SWCZ.     

Land use/land cover mapping and change detection in part of eastern ghats of tamil nadu using remote sensing and GIS

In the present study an attempt has been made to map land use/land cover and change detection analysis in Kolli hill, part of Eastern Ghats of Tamil Nadu, using remote sensing and GIS. About 467 ha increase has been observed in single crop category and about 434 ha decrease has been observed in land with or without scrub category. Majority of the area (13639 ha) is under scrubland. Lesser changes could be noticed in double crop, plantation and barren/rocky categories. Necessary measures should be taken to utilize the scrubland and to prevent the conversion of cropland into scrubland. The identified wastelands, which are suitable for agriculture, have to be utilized optimally to improve the economy of the people.