Understanding land-use/cover change process for land and environmental resources use management policy in Ghana

Accurate information on land-use/cover change is a critical input for natural resource use management policy decisions. In Ghana, however, land-use/cover change is premised on the assumption that there has been a historically simple, linear, and uniform degradation of vegetation across all landscapes. The Kintampo and neighboring districts have become a subject of intense debate as to the real nature of prevailing land cover changes .It is commonly assumed that there is ubiquitously progressive irreversible woody vegetation loss across the area. The paper reports on the process and amount of land-use/cover changes that have prevailed in specific localities across the area within a 10-year period. It is hoped this will improve understanding and management of land-use/cover change in Ghana. Remote sensing and Geographic information systems technologies were used for the investigation. A multi-site satellite imagery approach was adopted to ensure that inductive inferences could be made. The outcome of the study indicated that, in space and time, there have been significant land-use/cover changes. Variability in change was a constant, rather than occasional feature across these human dominated landscapes. The conversion and transformation processes indicated that the traditional land-use strategies are self-sustaining. Any effective land-use/cover management strategy should be built upon the existing traditional farming system knowledge and practices.     

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

吉林西部多时相遥感数据分类方案的构建及应用

为了深化遥感监测方法在生态环境调查中的应用,本文以吉林西部为试验区,设计了一种多时相遥感数据分类方案。该方案以物候信息为主,结合地物特征变量(植被、水体和土地信息)构建的多维特征空间数据集用于土地覆被分类。该遥感分类方案提取了9种地表覆被类型,结果表明:地表植被季节变化信息和土地利用信息的引入能明显改善土地覆被的分类精度;与基于原始波段的分类方案相比,多时相遥感数据分类方案的分类精度最好,总体分类精度为95.50%,Kappa系数为95.04%。     

Geospatial tools for assessing land degradation in Budgam district,Kashmir Himalaya,India

Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS ‘Spatial Analyst Module’. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.     

晋陕蒙接壤地区土地利用/覆盖变化及其驱动力研究——以神华集团大柳塔矿区为例

选择地处生态环境脆弱地区的晋陕蒙接壤地区能源化工基地的大柳塔矿区为研究区,利用1986年8月2日和2007年9月7日的TM卫星图像数据为信息源,应用遥感技术对其土地利用/覆盖变化进行研究。通过图像处理,划分出7种土地利用和地表覆盖景观类型,根据获取的景观类型变化参数对其结构与变化特征进行分析,得出研究区的生态变化趋势与驱动力。结果表明,煤矿大规模开采以来,研究区景观结构稳定性减弱,破碎度增强,人类活动在研究区生态环境变化过程中起主导作用。在矿区生态环境恢复中,应提高自然植被景观类型的有效规模,有利于增强生态系统的稳定性。     

Spectral wheat yield prediction modeling using SPOT satellite imagery and leaf area index

As wheat represents the main staple food and strategic crop in Egypt and worldwide and since remote sensing satellite imagery is the tool to obtain synoptic, multi-temporal, dynamic, and time-efficient information about any target on the Earth, the main objective of the current study is to use remote sensing satellite imagery to generate remotely sensed empirical preharvest wheat yield prediction models. The main input parameters of these models are spectral data either in the form of spectral reflectance data released from Satellite Pour l’Observation de la Terre (SPOT) 4 satellite imagery or in the form of spectral vegetation indices. The other input factor is leaf area index (LAI) that was measured by LAI Plant Canopy Analyzer. The four spectral bands of SPOT4 imagery are green, red, near-infrared, and middle infrared; the five vegetation indices that are forms of ratios between red and near-infrared bands are normalized difference vegetation index, ratio vegetation index, soil-adjusted vegetation index, difference vegetation index, and infrared percentage vegetation index. Another vegetation index is green vegetation index that is calculated through a ratio between green band and near-infrared band. Each of the above-mentioned factors was used as an input factor against wheat yield to generate wheat yield prediction models. All generated models are site-specific limited to the area and the environment and could be applicable under similar conditions in Egypt. The study was carried out in Sakha experimental station by using the dataset from two wheat season 2007/2008 and 2009/2010. The total wheat area was 1.3 ha cultivated by Sakha 93 cultivar. Modeling and validation process were carried out for each season independently. Modeled yield was tested against reported yield through two common statistical tests; the standard error of estimate between modeled yield and reported yield, and the correlation coefficient for a direct regression analysis between modeled and reported yield with each generated model. Generally, as shown from the correlation coefficient of the generated models, green and middle infrared bands did not show good accuracy to predict wheat yield, while the other spectral bands (red and near-infrared) bands showed high accuracy and sufficiency to predict yield. This was proven through the correlation coefficient of the generated models and through the generated models with the wheat crops for the two seasons. Accordingly, the green vegetation index that is generally calculated from green and near-infrared bands showed relatively lower accuracy than the rest of the vegetation index models that are calculated from red and near-infrared bands. LAI showed high accuracy to predict yield as shown from the statistical analysis. The models are applicable after 90 days from sowing stage and applicable in similar regions with the same conditions.     

Assessment of Land-use and Land-cover Change and its Impact on Groundwater Quality Using Remote Sensing and GIS Techniques in Raipur City,Chhattisgarh, India

Monitoring of land use and land cover change (LULC) is essential for water conservation and management. In this study, an attempt has been made to understand the impact of LULC change on groundwater quality. In the present study LULC map of the study area prepared using satellite image of year 1999 and 2016 which are visually interpreted with help of ERDAS IMAGINE and ArcGIS software. In this study different image interpretation elements like tone, texture, size, pattern and association were used and verified with field check and total eight LULC classes were recognized such as settlement, road, cultivation, industry, drainage, lake, open land and vegetation. Comparison of LULC of year 1999 and year 2016 indicates that the settlement (net increases 16.2%), road (net increases 0.8%), open land (net increases 14.8%) and industry (net increases 3.1%) area has expanded. In the study area groundwater pollution is mainly associated with LULC change and as well as poor waste management practices. Obtained result has been validated with nitrate concentration and found 73.33% accuracy reflecting that, applied techniques has produced significantly reliable results.     

Assessing land use and land cover change in the Wassa West District of Ghana using remote sensing

Vast tracts of forests are lost globally every year especially in the developing countries of the tropics due to various human activities such as lumbering, farming, bush fires, surface mining and urbanization. The rainforest in Ghana has experienced rapid depletion since the 1980s. The impact of deforestation is widespread, affecting the livelihoods of local people and disrupting the tropical ecosystem. There is a serious concern in the study area about climatic change, soil erosion, siltation of rivers and loss in biodiversity which have an adverse impact on traditional medicinal plants of the local people. The study examined the extent of land cover change through image differencing of Landsat TM 1986 and 2002. The image classification indicated that, vegetative cover from 1986 to 2002 has been reducing whiles land use activities have been increasing. Closed canopy, open canopy and plantation have significantly diminished and land use activities especially built ups, farms, mining and openfields are more than doubled. The driving forces for the change in land cover are population growth, lumbering, socio-economic and cultural practices of the people. Lumbering and mining have been some of the major causes of the changing landscape in primary forest. Also the reliance on wood for domestic energy and the need to increase food productivity to feed growing population have also contributed greatly to the rapid depletion of the vegetative cover.     

Monitoring land use/land cover change using multi-temporal Landsat satellite images in an arid environment: a case study of El-Arish,Egypt

Environment in arid conditions is dynamic and needs more investigation to understand the complexity of change. This spatiotemporal study will help to assess and monitor the land use and land cover change in the arid region of El-Arish area, where the climate and human activities are the major threats to rural development. In the past 11 years, dramatic changes of environment have been recorded in case studies. The post-classification comparison method was used to observe the changes using multi-temporal satellite images which were captured in the years 1999, 2001, 2005, and 2010. The overall accuracy of the produced thematic images was assessed regarding to the quantity and allocation disagreements. Five classes were defined in this investigation: bare soil, vegetation, urban, sand dunes, and fertile soil. From the year 1999 to 2010, fertile soil was increased by 13 %. Bare soil class occupied more than 50 % of land in the case study during for over a decade. From year 1999 to 2010, vegetation cover witnessed a dramatic increase. Soil and water management are the keys of land development and positive land use and land cover dynamics. Changing agricultural policies of using the available water resources are needed in the case study to prevent severe food shortage in the future.     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

基于遥感和景观分类的北京市裸露农田分析和治理对策

基于遥感影像的决策树分类,结合土地利用图,将北京市农业地表覆盖划分为春玉米、冬小麦、果园、林木苗圃、牧草地、设施农业和畜禽饲养地。考虑海拔、坡度和土壤质地三个因子将北京市分成10个景观区,在景观分区和不同农业用地基础上划分出39类农业景观单元。利用基于遥感影像计算的归一化差异植被指数,结合实地调查验证,分类出北京市冬春季裸露农田。结合景观分类,分析了不同景观单元冬春季地表裸露情况。结果表明：2007—2008年冬春季裸露农田共8.05×104 hm2,主要分布在延庆盆地、密云水库北岸和城区边缘的近郊农业区;海拔和土地利用方式对裸露情况影响较大,其中山区春玉米和平原果园裸露情况绝对面积较大,分别占到总裸露农田面积的40%和17%,牧草地、林木苗圃与设施农业地裸露程度较高。基于不同景观单元裸露程度,结合绿肥种植、保护性耕作、生草覆盖等裸露农田治理方法,探讨了北京市农业产业和景观一体化建设策略。     

The relationship between drought activity and vegetation cover in Northwest China from 1982 to 2013

We investigated drought activity and the relationship between drought and vegetation in Northwest China over the period 1982–2013 using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI). The indexes were, respectively, calculated from ground-based meteorological data and from remotely sensed satellite data. The spatial and temporal distributions of drought (SPEI) and of vegetation cover (NDVI) were compared using annual trends, and the relationships between these trends were analyzed. The results are: (1) Overall, Northwest China had a drought trend during the study period, although some a few regions show a significant wetness trend; (2) the mean annual NDVI fluctuates, but overall shows an increasing trend, particularly in some mountainous areas that have at least adequate water and vegetation cover, while unused land becomes degraded; (3) most regions show a positive correlation between SPEI and NDVI, although the western parts of the Tarim basin, Qaidam basin, and some regions in the southeastern part of study area show a negative correlation; and (4) the various regions respond differently to global climate change, but in general regions with more vegetation cover show increased vegetation growth, while regions with less vegetation cover are becoming degraded and thus more vulnerable to the adverse effects of climate change.     

Spatio-temporal land cover changes in a semi-arid watershed: Central India

Land use/land cover change is a global phenomenon which reflects natural resources degradation and/or utilization. Remote sensing and GIS have been widely used to monitor such changes at watershed level. The present study evaluates the LU/LC change during 1989 - 2001 in a semi-arid watershed of central India. Geocoded satellite data of 1989 and 2001 on 1:50,000 scale, were visually interpreted to prepare thematic maps which were later digitized using ArcGIS softwares. The analysis shows that vast tracts of cultivated land have become uncultivated and at some places even converted to wasteland. However, the land under dense forest and open forest has decreased due to expansion of built-up land and other anthropogenic activities. Increase in area of uncultivated land, wasteland and decrease in cultivated land and open scrub is also supported by rainfall analysis, which shows a declining trend and a fall of 186.93 mm in average annual rainfall for 1986-2003 period. The change detection map prepared using land use/land cover of 1989 and 2001 as inputs shows that out of the total geographical area of the watershed, 25.78% of the watershed area has seen a change from one land use category to another, however rest 74.22% has remained unchanged.     

Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok,India

In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.     

Multi-temporal landsat images based on eco-environmental change analysis in and around Chah Nimeh reservoir,Balochestan (Iran)

Chah Nimeh reservoirs have served as a water storage facility, especially during droughts over the last three decades. It is also an important wintering site for migratory birds. In this study, thematic mapper time-series data were derived from Landsat images for prolonged droughts that occurred in two satellite images (2002 and 2011). The data derived from these images were used for the detection of changes in land cover and water storage in the reservoirs. First, a vegetation cover map was produced using soil-adjusted vegetation index and field sampling. Subsequently, land use/cover maps were generated using supervised and hybrid image classification method. Using the spatial change detector (SCD v1.0) software extension, the layers were combined and the change map was generated. The overall accuracy of the produced thematic images was assessed in regards to quantity and allocation disagreements. A total of five classes were defined in this investigation: deep water, shallow water, vegetation, salt land and bare land. The results showed that during the period of study, water volume reduced and vegetation cover increased, especially around the reservoirs that are important as shelter for wintering migratory birds. Comparison of land use/cover maps showed the increase in total available surface of shallow water, which indicated an increase in the habitats for surface feeding and diving birds.     

陆面过程中植被的描述及其卫星遥感反演——从定性描述向定量描述的发展

植被在陆面参数化方案（Land Surface Parameterizations, LSPs）中的描述经历着从定性描述向定量描述发展的过程。这一方面是由于陆面过程研究的深入,另一方面则得益于地表植被信息获取方式的进步,尤其是卫星遥感技术的发展。对三代LSPs中的植被描述做了简要概述,并介绍了卫星遥感在植被参数反演上的发展和应用情况。其中包括：①定性描述,主要指地表覆盖类型的描述方式;②部分参数定量描述,指SiB2等模式中对LAI等时空变化较大的少数参数由卫星资料直接反演的赋值方式;③植被特征连续分布（VCF）定量描述,一种完全定量的描述方式。     

Risk assessment of water soil erosion in upper basin of Miyun Reservoir,Beijing, China

This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion, ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data. Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction. All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively.     

Vegetation recovery and landscape change assessment at Chiufenershan landslide area caused by Chichi earthquake in central Taiwan

This study discusses vegetation recovery and land cover change with reference to the Chiufenershan landslide, a major disaster caused by the Chichi earthquake, 21 September 1999. Image classification technology, landscape indicators from multi-temporal remotely sensed data and a field survey provide the data. Image differencing methods and threshold values coupled with pre- and post-quake satellite images were used. Multi-temporal images in combination with various vegetation indices were drawn on to classify land cover patterns and discuss differences and suitability of indices. Landscape indicators and field investigations fed into an investigation of vegetation recovery and landscape change. The study results show that the best image classification system is original wavebands coupled with a cropping management factor index (CMFI). The land cover analysis shows that areas of forest and grass are increasing and areas of landslide are decreasing. From the field investigation, because the left and right sides of the landslide area were not disturbed by the earthquake, their calculated similarity index is the highest (30.08%). Miscanthus floridulus is the most dominant pioneer plant at the landslide collapse area with an importance value index (IVI) of 63.6%.     

Remote sensing and GIS for artificial recharge study, runoff estimation and planning in Ayyar basin, Tamil Nadu, India

This paper focuses on artificial groundwater recharge study in Ayyar basin, Tamil Nadu, India. The basin is covered by hard crystalline rock and overall has poor groundwater conditions. Hence, an artificial recharge study was carried out in this region through a project sponsored by Tamil Nadu State Council for Science and Technology. The Indian Remote Sensing satellite 1A Linear Imaging Self Scanning Sensor II (IRS 1A LISS II) satellite imagery, aerial photographs and geophysical resistivity data were used to prioritize suitable sites for artificial recharge and to estimate the volume of aquifer dimension available to recharge. The runoff water available for artificial recharge in the basin is estimated through Soil Conservation Service curve number method. The land use/land cover, hydrological soil group and storm rainfall data in different watershed areas were used to calculate the runoff in the watersheds. The weighted curve number for each watershed is obtained through spatial intersection of land use/land cover and hydrological soil group through GeoMedia 3.0 Professional GIS software. Artificial recharge planning was derived on the basis of availability of runoff, aquifer dimension, priority areas and water table conditions in different watersheds in the basin.     

Relationship in metastasis of coal fire and land use/cover using thermal imagery and support vector machine classifier

The objective of the present study was to delineate temporal and spatial changes in the coal fire and land use/cover within Bastacolla area of Jharia coal field. Studying this variation helped to decipher interconnection among the dynamics of the coal fire and concomitant changes in land use/cover. The detection of coal fires during a span of 14 years along with transitioning land use/cover was cost-effective and enabled planning for management of coal resources and environment. Landsat series of satellite data of 2002, 2009, 2013, and 2016 were processed for generating land surface temperature profiles vis-a-vis classified land use/cover of the study area. A single cut-off temperature was derived for mapping of coal fires using land surface temperature profile from 2002 to 2016. The satellite images were classified using support vector machines, and for depicting land use/cover change, post-classification change detection was done. Classification accuracy obtained was excellent with kappa coefficient ranging from 0.897 for classified image of 2002 to 0.799 for classified image of 2016. Results revealed that coal fires had shifted to the central west part of the area. Furthermore, pockets of coal fire from northern and eastern part of the study area have diminished. OB dumps and coal quarry/coal dump may be attributed towards the spatial change in coal fire while; OB dumps showed connotation with the highest temperature zones. Ground verifications for temperature profiles and coal fires were carried out using thermal camera which enunciated good agreement with results.