Linking Spatial–Temporal Changes of Vegetation Cover with Hydroclimatological Variables in Terrestrial Environments with a Focus on the Lake Urmia Basin

Investigation of vegetation cover is crucial to the study of terrestrial ecological environments as it has a close relationship with hydroclimatological variables and plays a dominant role in preserving the characteristics of a region. In Iran, the current study selected the watersheds of two rivers, Nazloo-Chay and Aji-Chay, to systematically investigate the implications and causes of vegetation cover variations under changing environments. These two rivers are among the essential inflows to Lake Urmia, the second largest saline lake on Earth, and are located on the west and east sides of the lake, respectively. There has been a debate between the people living in the rivers’ watersheds about who is responsible for the decline in the level of Lake Urmia—does responsibility fall with those on the east side or with those on the west side? In this study, the normalized difference vegetation index (NDVI) was used as a remotely sensed index to study spatial–temporal pattern changes in vegetation. Moreover, the temperature, precipitation, and streamflow time series were gathered using ground measurements to explore the causes and implications of changing vegetation cover. Discrete wavelet transform was applied to separate the different components of the time series. The Mann–Kendall (MK) test was applied to the time series on monthly, seasonal, and annual time scales. The connections and relationship between the NDVI time series and temperature, precipitation, and streamflow time series and any underlying causes were investigated using wavelet transform coherence (WTC). Land use maps were generated for different years using a support vector machine (SVM) in the final stage. The results indicated that the most dominant monthly, seasonal, and annual hydrological periodicities across the watersheds are 8 months, 6 months, and 2 years, respectively. The increasing vegetation cover during stable hydro-environmental periods revealed unusual conditions in the Aji-Chay watershed and reflected agricultural expansion. The WTC graphs indicated sudden changes in mutual periodicities and time-lags with different patterns between variables, which indicates the increasing anthropogenic activities in both watersheds. However, this was more dominant in the Aji-Chay watershed. The land use maps and investigation of the averaged NDVI maps also denoted that the areas of cultivated land have increased by 30% in the Aji-Chay watershed, and crop types have been changed to the crops with a higher demand for water in both watersheds.

Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China

Wetlands, as the most essential ecosystem, are degraded throughout the world. Wetlands in Zhenlai county, with the Momoge National Nature Reserve, which was included on the Ramsar list, have degraded by nearly 30%. Wetland degradation is a long-term continuous process with annual or interannual changes in water area, water level, or vegetation presence and growth. Therefore, it requires sufficiently frequent and high-spatial-resolution data to represent its dynamics. This study mapped yearly land-use maps with 30-m resolution from 1985 to 2018 using Landsat data in Google Earth Engine (GEE) to explore the wetland degradation process and mapped 12-day interval land-use maps with 15-m resolution using the Sentinel-1B and Sentinel-2 data in GEE and other assistant platforms to study the characteristics of wetland dynamics in 2018. Four sets of maps were generated using Sentinel-1B (S1), Sentinel-2 (S2), the combination of Sentinel-1B and Sentinel-2 (S12), and S12 with multitemporal remote sensing (S12’). All of the classifications were performed in the Random Forest Classification (RFC) method using remote sensing indicators. The results indicate that S12’ was the most accurate. Then, the impact of the historic land-use degradation process on current wetland change dynamics was discussed. Stable, degradation, and restoration periods were identified according to the annual changes in wetlands. The degraded, stable, restored, and vulnerable zones were assessed based on the transformation characteristics among wetlands and other land-use types. The impact of historical land-use trajectories on wetland change characteristics nowadays is diverse in land-use types and distributions, and the ecological environment quality is the comprehensive result of the effect of historical land-use trajectories and the amount of rainfall and receding water from paddy fields. This study offers a new method to map high-spatiotemporal-resolution land-use (S12’) and addresses the relationship between historic wetland change characteristics and its status quo. The findings are also applicable to wetland research in other regions. This study could provide more detailed scientific guidance for wetland managers by quickly detecting wetland changes at a finer spatiotemporal resolution.

A machine-learning model for the prediction of aggregated building heating demand from pan-European land-use maps

Aggregated building energy demand is a useful indicator for urban energy planning. It can be used by planners and decision-makers to identify clusters of high energy demand in a given urban area and efficiently plan, for example, district heating networks. Various data sources exist at the pan-European level describing land use and built areas. Combined with statistical data, such maps have been used in previous research for estimating building energy performance aggregated at the hectare level, using engineering assumptions. In this paper, we show that large-scale land-use maps alone can be used for predicting annual building energy demand with an accuracy comparable to the one of previous engineering models. We hence present a preliminary method based on Convolutional Neural Networks at different spatial resolutions. The resulting model was trained and tested in an area of about 170 km1 in Geneva (Switzerland) using a local annual heating demand dataset comprising 16239 buildings. On a 300-m aggregation tile, the obtained mean error (14.3%) is significantly reduced compared to the one of a simple linear model (37.2%). Using solely land-use data, we also achieve similar results for a 100-m tile as those of an engineering model from the literature.

Exploring and Predicting the Individual, Combined, and Synergistic Impact of Land-Use Change and Climate Change on Streamflow, Sediment, and Total Phosphorus Loads

The present study predicts and assesses the individual, combined, and synergistic effect of land-use change and climate change on streamflow, sediment, and total phosphorus (TP) loads under the present and future scenarios by using the Soil and Water Assessment Tool (SWAT). To predict the impacts of climate and land-use change on streamflow, sediment, and TP loads, there are 46 scenarios composed of historical climate, baseline period climate, eight climate models of Coupled Model Intercomparison Project phase 5 (CMIP5) of two representative emission pathways (RCP4.5 and RCP8.5), after downscaled and bias-corrected, two observed land-use maps (LULC 1995, LULC 2015) and the projected two future land-use maps (LU2055 and LU 2075) with the help of CA-Markov model to be fed into SWAT. The central tendency of streamflow, sediment, and TP loads under future scenarios is represented using the annual average. The intra-/inter-annual variation of streamflow, sediment, and TP loads simulated by SWAT is also analyzed using the coefficient of variation. The results show that future land-use change has a negligible impact on annual streamflow, sediment, TP loads, and intra-annual and inter-annual variation. Climate change is likely to amplify the annual streamflow and sediment and reduce the annual TP loads, which is also expected to reduce its inter-/intra-annual variation of TP loads compared with the baseline period (2000–2019). The combined impact of land-use and climate change on streamflow, sediment, and TP loads is greater than the sum of individual impacts for climate change and land-use change, especially for TP loads. Moreover, the synergistic impact caused by the interaction of climate and land use varies with variables and is more significant for TP loads. Thus, it is necessary to consider the combined climate and land-use change scenarios in future climate change studies due to the non-negligible synergistic impact, especially for TP loads. This research rare integrates the individual/combined/synergistic impact of land-use and climate change on streamflow, sediment, and TP loads and will help to understand the interaction between climate and land-use and take effective climate change mitigation policy and land-use management policy to mitigate the non-point source pollution in the future.

A Fractal Approach to Urban Boundary Delineation Based on Raster Land Use Maps: A Case of Shanghai, China

Given the diverse socioecological consequences of rapid urban sprawl worldwide, the delineation and monitoring of urban boundaries have been widely used by local governments as a planning instrument for promoting sustainable development. This study demonstrates a fractal method to delineate urban boundaries based on raster land use maps. The basic logic is that the number of built-up land clusters and their size at each dilation step follows a power-law function. It is assumed that two spatial subsets with distinct fractal characteristics would be obtained when the deviation between the dilation curve and a straight line reaches the top point. The top point is regarded to be the optimum threshold for classifying the built-up land patches, because the fractality of built-up land would no longer exist beyond the threshold. After that, all the built-up land patches are buffered with the optimum threshold and the rank-size distribution of new clusters can be re-plotted. Instead of artificial judgement, hierarchical agglomerative clustering is utilized to automatically classify the urban and rural clusters. The approach was applied to the case of Shanghai, the most rapidly urbanizing megacity in China, and the dynamic changes of the urban boundaries from 1994 to 2016 were analyzed. On this basis, urban–rural differences were further explored through several fractal or nonfractal indices. The results show that the proposed fractal approach can accurately distinguish the urban boundary without subjective choice of thresholds. Extraordinarily different fractal dimensions, aggregation and density and similar average compactness were further identified between built-up land in urban and rural areas. The dynamic changes in the urban boundary indicated rapid urban sprawl within Shanghai during the study period. In view of the popularization and global availability of raster land use maps, this paper adds fuels to the cutting-edge topic of distinguishing the morphological criteria to universally describe urban boundaries.

The Effects of Map Reading Expertise and Map Type on Eye Movements in Map Comparison Tasks

Comparing maps of different geographical phenomena, or maps of the same geographical phenomenon at different points in time, is a frequent task in many disciplines. The process of map comparison has been studied occasionally by cartographers since the 1970s, but recent improvements in neuropsychological testing equipment and in geographical information system (GIS) technology had us review this topic in a new light. We propose a cognitive approach using eye movement recording to understand the process of comparing two static maps displayed simultaneously on a screen. Two groups of subjects with different levels of expertise with map reading were shown pairs of maps and asked to judge their similarity or difference. We used three types of maps that differed in their spatial granularity: (A) randomly generated, 64-by-64 pixel, black-and-white images, (B) grayscale choropleth maps representing socio-economic variables for counties in lower Michigan, and (C) land-use maps of the surroundings of selected Canadian cities in different years resulting from classified satellite imagery. Subjects were asked whether two maps presented on the screen were similar (tests A and B) or different (test C). Response times, fixation durations and fixation counts differed significantly for the three map types. Land-use maps required the longest response times indicating that they were most difficult to compare. At the same time, land-use maps required more fixations than the other two types of maps, while the duration of these fixations was not different from the other map types. When comparing two maps of the same type, saccades between the two maps provide information on the subject’s decision-making process. We found that for the land-use maps, the number of these cross-saccades was significantly smaller than for the two other map types. Pairs of land-use maps were characterized by a fine raster grid and fewer pixel-by-pixel differences between the two maps, while both, random grids in test A and county maps in test B consist of clear-cut spatial units. We conclude that whenever spatial units can be distinguished on a map and corresponding units on a second map can be found easily, subjects will tend to compare the two maps in a unit-by-unit approach. In contrast, if maps consist of smoother spatial patterns, subjects will try to memorize patterns on one map (usually the one on the right-hand side), and make fewer saccades to compare these patterns with those on the other map. The results from this experiment could be used to provide context-adaptive tools for map comparison in GIS. The behavioral differences between groups (experts vs. novices) in this experiment were mostly not significant. This supports the notion of developing standard GIS tools that are offered to users with a wide range of expertise.

The Effects of Map Reading Expertise and Map Type on Eye Movements in Map Comparison Tasks

Comparing maps of different geographical phenomena, or maps of the same geographical phenomenon at different points in time, is a frequent task in many disciplines. The process of map comparison has been studied occasionally by cartographers since the 1970s, but recent improvements in neuropsychological testing equipment and in geographical information system (GIS) technology had us review this topic in a new light. We propose a cognitive approach using eye movement recording to understand the process of comparing two static maps displayed simultaneously on a screen. Two groups of subjects with different levels of expertise with map reading were shown pairs of maps and asked to judge their similarity or difference. We used three types of maps that differed in their spatial granularity: (A) randomly generated, 64-by-64 pixel, black-and-white images, (B) grayscale choropleth maps representing socio-economic variables for counties in lower Michigan, and (C) land-use maps of the surroundings of selected Canadian cities in different years resulting from classified satellite imagery. Subjects were asked whether two maps presented on the screen were similar (tests A and B) or different (test C). Response times, fixation durations and fixation counts differed significantly for the three map types. Land-use maps required the longest response times indicating that they were most difficult to compare. At the same time, land-use maps required more fixations than the other two types of maps, while the duration of these fixations was not different from the other map types. When comparing two maps of the same type, saccades between the two maps provide information on the subject’s decision-making process. We found that for the land-use maps, the number of these cross-saccades was significantly smaller than for the two other map types. Pairs of land-use maps were characterized by a fine raster grid and fewer pixel-by-pixel differences between the two maps, while both, random grids in test A and county maps in test B consist of clear-cut spatial units. We conclude that whenever spatial units can be distinguished on a map and corresponding units on a second map can be found easily, subjects will tend to compare the two maps in a unit-by-unit approach. In contrast, if maps consist of smoother spatial patterns, subjects will try to memorize patterns on one map (usually the one on the right-hand side), and make fewer saccades to compare these patterns with those on the other map. The results from this experiment could be used to provide context-adaptive tools for map comparison in GIS. The behavioral differences between groups (experts vs. novices) in this experiment were mostly not significant. This supports the notion of developing standard GIS tools that are offered to users with a wide range of expertise.

Arahan Kebijakan Untuk Mengurangi Dinamika Penggunaan Lahan pada DAS Antokan, Provinsi Sumatera Barat

The need for land has increased every year, and this increase is caused by the rate of population growth, resulting in changes in land use. Uncontrolled land use conversion has led to catastrophic flooding in the Antokan watershed. The purpose of this study was to determine the direction of land use change policies in the Antokan Watershed, West Sumatra Province. To determine land use change using the GIS method with the overlay technique of land use maps for the period 2000-2020. Furthermore, to determine the policy direction using the ISM method involving 20 experts. Research results in the Antokan watershed have shown changes in land use of 4,178 hectares during the 2000-2020 period. Changes occur in forest areas, mixed gardens, shrubs, and rice fields which have decreased, on the other hand, settlements, plantations and open land have expanded. Furthermore, there are two sub-elements that are the priority for policy direction to reduce the rate of land use change, namely making regulations and firm sanctions on land use errors (E3) and consistency in enforcing land use laws (E4).

Vegetation Dynamics in the Northern Zones of Niger: Case of the Rural Commune of Tanout (Zinder) and Aderbissinat (Agadez)

The present study conducted in the northern zone of Niger aims to show the impact of land use dynamics on woody vegetation. The methodological approach consisted in making in addition to the floristic surveys, the analysis of land use maps (LANDSAT images of the years 1975 and 2018). The floristic inventory allowed the identification of twenty-seven (27) woody species of which eleven (11) in Tanout and sixteen (16) in Aderbissinat. The most important families remain the Fabaceae-Mimosoideae which represent 37.5% at Aderbissinat and 45.45% at Tanout. The biological types remain dominated by microphanerophytes which dominate (86.67%), while for the phytogeographic types it is the Sudano-Zambezian and Sudanian species that dominate, with proportions respectively equal to 31.25%. There is a regression of woody vegetation at the level of these communes with a slight loss in Aderbissinat (60588,034 ha) and an accentuated degradation of vegetation in Tanout (781797,738 ha).