Land Cover Conditions Research Articles

ANALISIS SPASIAL POTENSI RESAPAN AIR UNTUK MENDUKUNG PENGELOLAAN DAERAH ALIRAN SUNGAI (DAS) UNDA PROVINSI BALI (Spatial Analysis of Water Infiltration Potential to Support The Management of Unda Watershed at Bali Province)

The Unda Watershed is categorized as the priority watershed, which part of its area is degraded land. The condition of land cover with the dominance of low-density vegetation has implications for low infiltration and water absorption capacity, so that it has the potential to increase surface runoff. This study aims to identify the potential for water absorption as the basis for watershed management planning. The method used in this study is scoring with four parameters, namely soil type, land use, slope, and rainfall. Spatial data analysis uses Geographic Information System (GIS). The formulation of recommendations for watershed management activities is carried out descriptively, based on the findings of the analysis of water absorption potential. The results showed that the water recharge conditions in the study area were classified as good (22.54%), very critical (18.20%), normal (17.92%), and less critical (7.99%). The recommended watershed management is periodic reforestation, construction of bench/traditional terraces, construction of infiltration wells/biopori holes in the residential areas, and synergistic integration of the roles of watershed institutions from upstream to downstream.

Pendekatan Special Perkebunan Kelapa Sawit terhadap Daya Dukung Lingkungan di Kecamatan Anggaberi Kabupaten Konawe

The objectives of this study were (1) to identify the existing conditions of oil palm plantations in Anggaberi District, Konawe Regency (2) to analyze the condition of the carrying capacity of the environment in Anggaberi District, Konawe Regency (3) to formulate the concept of controlling environmental carrying capacity in Anggaberi District, Konawe Regency . This research was carried out through the stages of research methods including conducting studies on primary data and secondary data, namely the availability of geospatial information on the research area, D3TLH information, in the formulation of the concept of carrying capacity control. Based on the results of spatial identification, it shows that there are 2 villages and 1 sub-district that are the location for developing oil palm plantations in Anggaberi District, namely Andabia Village, Lerehoma Village, Wunduongohi Village, with a total area of 2500 Ha. The results of the analysis of environmental service index performance in Anggaberi District are divided into 5 (five) index classes, namely very low class, low, medium, high and very high class. The average carrying capacity index value of the provision, regulation and support ecosystem services in Konawe Regency, where the provision of environmental services ranges from 2.38 to 3.44 (low - high class), the regulatory environmental service index is in the range of 2.12 to 3.18 (low to medium class) and supporting environmental services index values ranging from 2.55 to 2.95 (low to medium class). In detail, the distribution of the index of carrying capacity for environmental services provision, regulation and support in Anggaberi District. The carrying capacity and carrying capacity of the region are highly dependent on the ability of the ecosystem to produce provision, maintenance and protection services. The ability of ecosystems to produce the services mentioned above is very dependent on the condition/state of the landscape or ecoregion conditions, the condition of the distribution of natural vegetation and the condition of land cover throughout the mainland of Konawe Regency. The combination of these three variables greatly determines the ability of ecosystems to produce services, both provisioning services, regulatory services and protection services.

Rejuvenation of ancient palaeochannel through groundwater recharge in Thar Desert of Rajasthan, India: investigations through remote sensing and HERT survey

Groundwater investigation in Thar Desert is a challenging task due to low rainfall pattern and limited recharge. In search of an alternate source of drinking water, satellite remote sensing technique has been used in delineation of palaeochannel (PC) in parts of Rajasthan. Analysis of temporal satellite images (1995–2016) show the signature of PC with increasing vegetation anomaly in an elevated terrain. Validation of the PC and its groundwater potential were demonstrated using land use land cover statistics, High-resolution Electrical Resistivity Tomography (HERT) and drilling data. 2D resistivity tomograms show that the PC aquifer is a low resistivity zone (7.98–53.6 Ωm), characterized by thick alluvium at 26 m depth. Based on the integrated analysis of satellite data and geospatial maps it has been inferred that this ancient fluvial channel (PC) has been rejuvenated due to groundwater recharge from the canal water from the north, after commissioning of IGNP canal in 1992.

Analysis of Land Cover Change and Projection of Settlement Land in Sepaku District, North Penajam Paser Regency

The relocation of the capital city of Indonesia to Sepaku District, North Penajam Paser Regency, East Kalimantan will have an impact on all existing aspects. Land cover in Sepaku District has decreased from year to year. The area of vegetated land cover in Sepaku District is assumed to be decreasing due to the relocation of the New Capital City (NCC) to the area, which will have a negative impact on the environment. Therefore, this study aims to determine the level of land cover change in Sepaku District and discuss how the condition of land cover in Sepaku District after the construction of the New Capital City (NCC). The method in this study uses GIS (Geographical Information System) analysis and descriptive analysis. The data used are land cover data from 2009 to 2019 to find out changes in land cover and population data from BPS to project the population. Based on the results of the analysis of land cover data from 2009 to 2019 there was a change from scrubland to industrial forest plantations of around 26000 ha. In addition, there was no significant change in the area of built-up land. However, the results of population projections show that Sepaku Sub-district will experience a significant increase in built-up land cover after the construction of the New Capital City (NCC).

Global Evaluation of SMAP/Sentinel-1 Soil Moisture Products

SMAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water bodies, urban areas, soil characteristics, and seasonal climatic conditions on the performance of active–passive SMAP/Sentinel-1 in estimating the SM. We also compared the performance metrics of enhanced SMAP (9 km) and SMAP/Sentinel-1 products (3 km) to analyze the effects of the active–passive disaggregation algorithm on various features of the SMAP SM maps. Results showed satisfactory agreement between SMAP/Sentinel-1 and in situ SM measurements for most sites (r values between 0.19 and 0.95 and ub-RMSE between 0.03 and 0.17), especially for dense sites without representativeness errors. Thanks to the vegetation effect correction applied in the active–passive algorithm, the SMAP/Sentinel-1 product had the highest correlation with the reference data in grasslands and croplands. Results also showed that the accuracy of the SMAP/Sentinel-1 SM product in different networks is independent of the presence of water bodies, urban areas, and soil types.

An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India

Anthropogenic activities are leads to changing a natural land cover, and consequences are severe to human and environments etc. The present study has examined the Muthupet mangrove forest and its surrounding land-use changes from 1975 to 2015 using the geospatial technology. An assessment of land use and land cover was done at Muthupet mangrove forest which is an occupied the three coastal district of Tamilnadu i.e. Thanjavur, Thiruvarur, and Nagappattinam. The remote sensing (MSS, TM, and OLI) data was adopted to explore the land use and land cover with help of visual image interpretation. The study had justified the results based upon the ground truth verification, and 203 sites were selected for explore the 10 land use categories. An Accuracy Assessment has done based on the KAPPA index for the year 2015 classified image and appraisal of land use change detection from 1975 to 2015 for all the categories. The study revealed that the land use and land cover condition from the 1975 to 2015, for example 1975 water bodies covered an area of about 156.1 km2, and 2015 it has comprised 89.8 km2. An appraisal of land use and land cover clearly is evidence in 2005 entire land use and land cover changed, and reasons for that an influence of the Tsunami. Consequently, Muthupet mangrove forest is one of the important to human and environments, and the present study has exposed that the changes of the mangrove forest, and its impact on to the coastal community.
 Keywords : Mangrove Fores; Remote sensing; LULC; Classification; Change detection
 
 Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Multi-scale evaluation of global evapotranspiration products derived from remote sensing images: Accuracy and uncertainty

• Five global remote sensing-based evapotranspiration (ET) products are compared. • Their accuracy at point scale is evaluated based on 94 worldwide flux stations. • Accuracy at basin scale is assessed by water balance analysis across 414 basins. • ET uncertainty at pixel scale is quantified with three-cornered hat method. • ET quantity and trend at the global scale is assessed through comparison analysis. Advances in satellite remote sensing (RS) techniques have greatly prompted the development of large-scale evapotranspiration (ET) models, yielding several freely available global ET products. A comprehensive evaluation on these products is necessary for selecting the most suitable ET products and developing large-scale ET models step forward. In this study, the accuracy and uncertainty of five RS-based global ET products (MOD16, SSEBop, GLEAM, AVHRR, and BESS) were evaluated at multi scales. At point scale their accuracy was evaluated through a direct comparison with in-situ observations from 94 worldwide flux towers. Results indicate that accuracy differences of these five products vary with statistical metrics and land cover types. The combination of all statistics illustrates that GLEAM and AVHRR outperform three other products, which is consistent with the findings of most previous continental-scale studies. The accuracy at basin scale was assessed through water balance analysis across 19 big river basins. BESS is found to be the product that is superior to four other ET products at both monthly and multi-annual scale, which may be related with its low random error at point scale. The uncertainty of these five products at pixel scale was assessed by the three-cornered hat (TCH) method and comparison analysis. The TCH outputs reveal that BESS and SSEBop are the two products with the lowest and largest relative uncertainty, respectively. That explains the good performance of BESS at basin scale from another perspective. As for the two MODIS-based ET products (MOD16 and SSEBop), their accuracy at FLUXNET site scale is comparable in monthly ET estimation. However, SSEBop has special advantage in the capture of multiyear ET patterns. The comparison analysis indicates that SSEBop is the product that agrees best with the ensemble mean not only on a global scale but also in four of the six continents. Our results imply that it is difficult or even impossible to figure out the best ET product in all respects. The selection of ET products for scientific research should consider their performance difference in spatial scale as well as the influence of land cover and climate conditions.

Operational Use of EO Data for National Land Cover Official Statistics in Lesotho

The Food and Agriculture Organization of the United Nations (FAO) is building a land cover monitoring system in Lesotho in support of ReNOKA (‘we are a river’), the national program for integrated catchment management led by the Government of Lesotho. The aim of the system is to deliver land cover products at a national level on an annual basis that can be used for global reporting of official land cover statistics and to inform appropriate land restoration policies. This paper presents an innovative methodology that has allowed the production of five standardized annual land cover maps (2017–2021) using only a single in situ dataset gathered in the field for the reference year, 2021. A total of 10 land cover classes are represented in the maps, including specific features, such as gullies, which are under close monitoring. The mapping approach developed includes the following: (i) the automatic generation of training and validation datasets for each reporting year from a single in situ dataset; (ii) the use of a Random Forest Classifier combined with postprocessing and harmonization steps to produce the five standardized annual land cover maps; (iii) the construction of confusion matrixes to assess the classification accuracy of the estimates and their stability over time to ensure estimates’ consistency. Results show that the error-adjusted overall accuracy of the five maps ranges from 87% (2021) to 83% (2017). The aim of this work is to demonstrate a suitable solution for operational land cover mapping that can cope with the scarcity of in situ data, which is a common challenge in almost every developing country.

Error and uncertainty characterization of soil moisture and VOD retrievals obtained from L-band SMAP radiometer

L-band passive microwave remote sensing has evolved over the past decade to estimate soil moisture (SM) and Vegetation Optical Depth (VOD). Novel Radiative Transfer Model (RTM) schemes and model parameterizations are proposed to achieve this goal. In this work, we attempt to characterize errors and uncertainties that propagate from RTMs and their parameters while retrieving SM and VOD from Soil Moisture Active Passive (SMAP) data. Three RTMs are considered, including a zeroth order model (τ-ω model) and two first order models (First order RTM and 2-Stream Emission model (2S-EM)). Surface roughness (h; characterizes undulations on soil surface) and single scattering albedo (ω; accounts for the scattering of emissions due to vegetation structure) are the two parameters (of RTMs) considered. SM and VOD are retrieved concurrently using a multi-temporal RTM inversion scheme. Errors and uncertainty contributions are determined using the Analysis of Variance (ANOVA) approach. To assess the role of land cover conditions on error and uncertainties in retrievals, ten reference sites are chosen to represent various biomes.Initially, brightness temperatures are simulated by varying RTMs and their parameters to determine their sensitivity. The SM and VOD retrievals are compared with reference datasets, and the performance is found to be acceptable. Error decomposition analysis indicates RTMs and their parameters (h and ω) induce noticeable and significant error in SM and VOD retrievals. Errors contributions due to the above factors are more prominent in VOD retrievals compared to SM. However, the uncertainty contributions indicate minimal influence of RTMs and their parameters on SM retrievals. The ω parameter followed by the choice of RTM have significant contributions to the uncertainty in the VOD retrievals. The h parameter resulted in significant uncertainties in VOD retrievals under sparsely vegetated regions. The results are used to comment on the suitability of each of the three RTMs and the model parameterization design that could alleviate the issue of errors and uncertainties in concurrent retrievals of SM and VOD. These inferences shall contribute towards developing robust multi-parameter retrieval algorithms.

IDENTIFKASI KERUSAKAN LAHAN HUTAN AKIBAT AKTIVITAS PERTAMBANGAN EMAS DESA BOWONE KECAMATAN TABUKAN SELATAN TENGAH

The problem of this research is changes in forest land use and the level of damage to forest land due to gold mining activities in Bowone Village, South Central Tabukan District, Sangihe Islands Regency. The research method is quantitative with GIS-based spatial analysis using Supervised Classification and NDVI. The study results show that the mining area expanded from 11.83 hectares in 2015 from 2.35 hectares to 14.18 hectares in 2020, with an average expansion of 2.37 hectares per year or 45.53% per year. Heavy damage in the forest area of ​​Bowone Village with an area of ​​131.2422 hectares (15%). Moderate damage with an area of ​​279,8941 hectares (35%), and light damage with an area of ​​435,7669 hectares (51.45). The condition of forest land cover in Bowone village is categorized as quite reasonable. However, it should be noted and anticipated that the current state of vegetation cover may decrease because 279.8941 hectares (33.05) have experienced a medium density category.

Spatio-Temporal Analysis of Land Use Land Cover, Dynamics in Built-up Area and Its Trend Predictions in Peshawar Vale, Pakistan

This study focused on the Spatio-temporal monitoring of land use land cover, built-up area, its trend, and its prediction in the valley of Peshawar, Pakistan. The collected data from 1990 to 2020 were spatiotemporally analyzed in GIS to get the required objective. Parallel to this, Terr-Set has been used for change analysis, whereas Cellular Automaton and Markov model have been applied for trend prediction of built-up area for 2050. The land use land cover analysis indicates that the study area's built-up area is rapidly increasing. The land use land cover statistics reveal that, the built-up area and vegetation cover showed a positive growth trend as the area under the built environment and vegetation cover consistently increased. However, the area under barren Land is decreasing with time, showing a negative trend. The analysis of the Markov model predicted that in 2050 the built-up area in Peshawar valley would be further increased at the cost of consuming bare soil and vegetation cover.

Pemetaan Tutupan Lahan Di Desa Bukit Raya Kecamatan Tenggarong Seberang Menggunakan Citra Sentinel 2A

The purpose of this study was to make a land cover map and determine the condition of land cover in Bukit Raya Village, Tenggarong Seberang District.The method used in this study is the use of remote sensing Sentinel 2A for land cover mapping with a guided method using sample digitization on the screen for sampling in the land cover classification process. After using the supervised classification data obtained in the form of vector data that must be combined first before being used as a layout map.Results Based on the research, information was obtained about the process of making land cover maps in Bukit Raya Village, Tenggarong Seberang District and Land Cover Maps in Bukit Raya Village, Tenggarong Seberang District. The result of the area of ​​each land cover class is Agricultural Land with an area of ​​426.9 Ha,Air with an area of ​​138.2 Ha, Urban with an area of ​​176.1 Ha, Forest Land with an area of ​​391.7 Ha, Barren land with an area of ​​2 Ha, Industry 49.7 Ha, Transportation 59 Ha.

Charcoal Whirlwinds and Post-Fire Observations in Serengeti National Park Savannahs

Whirlwinds and visible dust devils occur over semi-arid ecosystems and entrain particles from the ground surface. Fires produce abundant charcoal across savannahs and the resulting blackened surfaces create a large albedo contrast. Whirlwinds have been observed associated with active fires; yet, there are few published observations on post-fire landscapes. Spatiotemporal patterns of whirlwinds have been documented for a limited number of regions and have not been made for the ecosystems of eastern Africa. From field-based sightings in the Serengeti National Park, Tanzania, we report on whirlwinds over burned savannah patches that entrained large quantities of charcoal to produce black coloured charcoal devils that lofted charcoal into the atmosphere. Two occurrences of charcoal devils were sighted and photographed, one each in the Western Corridor (Bunda District) and Lamai (Serengeti District), Mara Region. The observations were compared with regional scale meteorological data and remote sensing satellite imagery and albedo estimates of the land cover conditions. Although direct meteorological or particulate matter measurements were not made, the observations show that both charcoal devils differed in colour, funnel shape, height, and savannah land cover types (different woody to grass fuel canopies), and thus different charcoal morphologies. Charcoal laden whirlwinds require further study and characterization to analyse the contribution to local-scale redistribution of matter and regional-to-global fluxes of terrestrially derived atmospheric particulates. Future research focusing on the spatiotemporal patterns of whirlwinds over burned patches of savannah, the formation, duration and dissipation mechanisms, and characterisation of the entrained material would contribute to our understanding of the phenomena. The redistribution of organic and clastic material would contribute to understanding of detrital fluxes to depositional environments, such as lakes, wetlands, and snow.
 Keywords: Atmospheric boundary layer; Convection; Detritus; Dust devils; Fires; Particulate matter.

Dynamic Displacement using DInSAR of Sentinel-1 in Sunda Strait

Sunda Strait’s geographical condition makes it experience many tectonic and seismic events. Deformation monitoring has been carried out with various methods ranging from terrestrial and non-terrestrial surveys. This study aimed to monitor the dynamics of deformation in the Sunda Strait region in 2019 using Differential Interferometric Synthetic Aperture Radar (DInSAR). DInSAR principle analyzes the paired SAR images that have been co-registered with different acquisition times to detect changes along the sensor observation line to the target or Line of Sight (LOS). The SAR data used are Sentinel-1 acquisition on June 1, and October 23, 2019. The results show that the coherence value of the image pair is low due to differences in the phase and intensity values. The maximum uplift value is 0.54 m located in the West Lampung Regency, and the subsidence is −0.3 m in the Pesisir Barat Regency. Uplift results are located in various geological conditions and do not affect by seismic phenomena, whereas subsidence shows its location in the potential area of land subsidence. The dynamics of uplift and subsidence in the Lampung regency are mostly affected by the geological and land use conditions of the locations.
 HIGHLIGHTS
 
 DInSAR provides deformation measurements with a high level of data precision over a large area
 The selection of image pairs is essential for analyzing ground deformation using DInSAR
 Lampung Province has experienced uplift and subsidence in several locations
 The dynamic of uplift and subsidence in the Lampung Province is mostly affected by the conditions of the geological and land-cover condition
 
 GRAPHICAL ABSTRACT

GLC-STATISTICS: A WEB-BASED SPATIAL STATISTICS SYSTEM FOR GLOBAL LAND COVER DATA

Abstract. Land cover data is one of the principle sources to understand changes of the earth, develop sustainable globe, conduct environment change studies, land source management, and many other societal benefit areas. Globeland30 is the first multi-temporal (for years 2000 and 2010) global land cover datasets at 30-meter resolution. Based on this dataset, an online geo-statistical system has been developed named “GlobeLand30 GSA”. It helps users from different technical expertise backgrounds to visually explore and quantitatively analyse global land cover data. Different from other Web geoprocessing services and applications or desktop GIS software, this system has developed algorithms to correct multi-type errors in computing global land cover statistics, and applied optimal strategies of pre-organizing geography and auxiliary datasets in order to provide rapid response to multiple co-occurrence user-requests. This paper presents the system architecture and the developed data processing strategies, and also the related accuracy and efficiency assessment of GlobeLand30 GSA. The result shows that the system can provide accurate and efficient land cover statistical analysis for various size and shape of user requested areas, and is capable of handling as much as 200 concurrent user-requests with reasonable response time using a low-end desktop computer system environment.

GIS-Based Modeling of Human Settlement Suitability for the Belt and Road Regions.

(1) Background: Human settlements are a basic requirement for human survival and development. The natural suitability of human settlements directly affects human health and their quality of life and, to some extent, also dictates the size of the regional population and economy, as well as the level of urbanization. (2) Methods: This study presents a kilometer grid-based comprehensive human settlement suitability (HSS) evaluation model (containing the relief degree of the land surface (RDLS), the temperature–humidity index (THI), the land surface water abundance index (LSWAI), and the land cover index (LCI)). (3) Results: Based on the correlations between the four factors (i.e., the normalized RDLS (NRDLS), normalized THI (NTHI), LSWAI, and LCI), the NRDLS and NTHI were determined to be the leading factors, and the LSWAI and LCI were considered to be the auxiliary factors. The auxiliary factors were used to enhance the comprehensive HSS model determined by the leading factors. Based on this logic, spatial and index models were established separately. The HSS index for the BRI regions ranged from 0.07 to 1.00. Six levels of HSS were determined—namely, unsuitable, critically unsuitable, critically suitable, generally suitable, moderately suitable, and highly suitable conditions. In particular, the human settlements suitability is dominated by critically suitable and suitable conditions that accounted for 63% of the BRI. (4) Conclusions: The evaluation results of human settlements showed that topographic and climatic conditions are important limiting factors for the suitability of human settlements. Due to the renewability and manmade adjustability of hydrological and land cover conditions, the comprehensive suitability of human settlements shows differences in different geographic spaces along the BRI. The results provide a decision-making basis for the research on the resource carrying capacity and reasonable distribution of populations in the BRI, so as to realize the sustainable development along the regions.

Grid-quantification study on the effect of rapid urbanization on hydrological processes

Abstract Hydrological processes such as evaporation, infiltration, and runoff are affected not only by natural climate change but also by land cover and soil conditions. The impact of urbanization on the key elements of the hydrological process is worth studying in the context of rapid urbanization. This paper combines the soil-land use index grid and the GSSHA model to quantitatively study the impact of land use on urban hydrological processes under the background of the changing urbanization stage. The results show that with the increase in land development and utilization activities, the hydrological process will transform. When grassland and woodland are converted to construction land, the changes in runoff, infiltration, and evaporation are the largest. The runoff depth increased by 0.94 × 10−1 ∼ 2.42 × 10−1 mm/km2, infiltration depth decreased by 0.80 × 10−1 ∼ 2.18 × 10−1 mm/km2, and evaporation decreased by 0.14 × 10−1 ∼ 0.28 × 10−1 mm/km2. In the transition from forest land to grassland, from cultivated land to forest land, and from cultivated land to grassland, the increase of infiltration contributed over 80% to the decrease of runoff process. This provides a scientific basis for future urban planning and sponge city construction.

Detection and characterization of coastal tidal wetland change in the northeastern US using Landsat time series

Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management. Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.

Green Urban Areas, a Landscape and Biological Characterization Applied to a Micro-basin of the Great Metropolitan Area of Costa Rica

Este artículo presenta una caracterización paisajística y biológica de las áreas verdes urbanas (AVU) de la microcuenca del río Bermúdez, provincia de Heredia, Costa Rica. Esta caracterización se basa en una clasificación según criterios de uso de estos espacios verdes, donde se describen atributos paisajísticos como cantidad, tamaño promedio, área total y condición de cobertura de la tierra; y atributos biológicos como riqueza de especies, géneros y familias, porcentajes de especies exóticas y nativas por categoría de AVU. Se utilizaron datos geoespaciales en el caso del componente paisajístico, provenientes de los municipios, así como fotointerpretación y generación de cartografía propia, y, para el componente biológico, muestreos de campo y consultas a expertos, fuentes secundarias mediante una revisión exhaustiva de literatura científica y de las bases de datos en línea. Los resultados muestran que existe 8.95% (664.68 ha) del área total de la microcuenca dedicada a las AVU de conservación de la biodiversidad, de protección del recurso hídrico y de recreación, mientras que la categoría AVU privadas dedicadas a cultivos y pasturas casi cuadriplica las primeras (31.33%; 2 325.81 ha). Se identificó 1 029 especies de árboles, arbustos, hierbas, trepadora, etc., siendo los jardines y calles los que aportan más especies. La fauna de vertebrados está dominada por las aves, seguida por reptiles, anfibios y por último los mamíferos. En conclusión, las AVU del área de estudio muestran diferencias paisajísticas y biológicas importantes en cuanto a cantidad, tamaño, distribución espacial, riqueza florística y faunística, y que en su conjunto forman una trama verde que aporta servicios ecosistémicos a la ciudad.

ASSESSMENT OF WETLAND DEGRADATION USING GEOSPATIAL TECHNIQUES IN LAKE BOYO, SOUTHERN ETHIOPIA

Although wetlands occupy less than 6% of the earth’s land area, they contribute a lot for ecosystem services than their small area implies. This study aims to model the wetland degradation of Boyo Lake using Geospatial techniques. This study uses Landsat 7 ETM for the year 2000 and 2010 while Landsat 8 OLI used for 2020. The imageries were extracted and geometrically corrected using boundary polygon data using Spatial Analyst Tool in ArcGIS 10.8. Supervised classification was performed using the Maximum Likelihood Classifier. A comparison of land cover statistics assisted in identifying the trend and rate of change at wetland over time. In 2000, water and wetland covered an area of 2743.9 ha (53.3%) and 1680.3 ha (32.7%) of the area, respectively. The analysis shows that water and wetland coverage declined to 1922.9 ha (37.4%) and 1309.4 ha (25.4%) while farmland have increased to 1765.23 ha (34.3%) in 2010. Subsequently, area coverage by water and wetland further declined to 1579.1 (30.7%) and 627.94 (12.21 %) respectively, in 2020. The area under wetland is threatened dramatically with increasing encroachment of farmland over the years. Protecting wetlands from degradation needs the multi-stakeholders involvement and policy enforcement.