Characterization of the Sahelian and Guinea Savannah ecosystem of Nigeria based on land surface temperature and normalized difference vegetation index DOI Creative Commons
Ping An,

E.E. Aki,

Victoria Otie

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Abstract Drought and desertification are expected to increase in Sahelian Africa, where there significant rainfall deficits extreme temperatures. This study examined the trends vegetation climate variables during period 1986–2023 Kano, Katsina Jigawa states, Nigeria. We used Landsat 5 TM, 7 ETM+ 8 OLI/TIRS processed spectral indices with Google earth engine platform. For pilot site year 2015 had highest minimum (40.19°C), maximum (43.04 °C) mean (42.63 land surface temperatures (LST), while 2005 lowest of these values. The LST for three states showed a long-term over years but normalized difference index 1986 was generally low, being 0.19 0.15 0.17 becoming lower still 2010. Low condition close 0 dominant sites, suggesting typically poor growth coverage. Mild severe drought noticed state, Kano experienced mild drought. Continuous monitoring would be necessary assess overall health vegetation, providing insights into environmental changes their potential impacts on ecosystem.

Language: Английский

Analysis and Prediction of Land Use/Land Cover Changes in Korgalzhyn District, Kazakhstan DOI Creative Commons
Onggarbek Alipbeki,

Chaimgul Alipbekova,

Gauhar Mussaif

et al.

Agronomy, Journal Year: 2024, Volume and Issue: 14(2), P. 268 - 268

Published: Jan. 25, 2024

Changes occurring because of human activity in protected natural places require constant monitoring land use (LU) structures. Therefore, Korgalzhyn District, which occupies part the State Natural Reserve territory, is considerable interest. The aim these studies was to analyze changes composition use/land cover (LULC) District from 2010 2021 and predict LU transformation by 2030 2050. Landsat image classification performed using Random Forest on Google Earth Engine. combined CA-ANN model used LULC 2050, were carried out MOLUSCE plugin. results showed that 2021, there a steady increase share ploughable an adequate reduction grassland. It established that, this trend will continue. At same time, be no drastic other classes. obtained can helpful for development management plans policies District.

Language: Английский

Citations

8
Unleashing the power of innovation and sustainability: Transforming cereal production in the BRICS countries DOI Creative Commons
Cosimo Magazzino,

Tulia Gattone,

Muhammad Usman

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 167, P. 112618 - 112618

Published: Sept. 16, 2024

Language: Английский

Citations

8
Increased atmospheric water stress on gross primary productivity during flash droughts over China from 1961 to 2022 DOI Creative Commons
Xiazhen Xi,

Miaoling Liang,

Xing Yuan

et al.

Weather and Climate Extremes, Journal Year: 2024, Volume and Issue: 44, P. 100667 - 100667

Published: March 28, 2024

Flash droughts threaten ecosystems substantially because of the fast onset and low predictability. Soil atmospheric water stress are two main factors reducing ecosystem productivity during flash droughts. However, long-term trends in soil on vegetation unclear. By conducting land surface model simulations, this study investigated impact gross primary (GPP) hot periods droughts, as well changes from 1961 to 2022 over China. The areas dominated by were 65.2% 19.9% respectively. During raised 39.4%, reduced 48.7%. 1961–2022, frequency, intensity, duration all showed significant upward (p < 0.05) Meanwhile, GPP decreased significantly 0.05), but increased 0.05). Correspondingly, at 0.8%/decade, while rose 1.6%/decade With sensitivity we found that was weakened North China plain under irrigated conditions, trend consistent with non-irrigated conditions Our indicated importance moisture climate warming.

Language: Английский

Citations

7
Tripartite relationship of urban planning, city growth, and health for sustainable development in Akure, Nigeria DOI Creative Commons
Taye Bayode, Alexander Siegmund

Frontiers in Sustainable Cities, Journal Year: 2024, Volume and Issue: 5

Published: Jan. 11, 2024

We live in an urban planet. As the world continues to urbanize, development that support health and wellbeing of city dwellers is far more important than ever before achieve sustainable targets. This study explores complex relationship among planning, growth, as critical drivers rapidly growing nodal Akure, Nigeria. The provides a four-decade spatio-temporal model Land Use Cover (LULC) changes Akure between years 1984 2023 from acquired Landsat satellite imageries. result shows 20% net change increase developed LULC classes years. A strong positive correlation exists covered analyses ( r = 0.93, p 0.002), negative with forest land use −0.94, 0.002) potential debilitating impacts on residents’ health, green infrastructures city’s sustainability future. Furthermore, results key informant interviews (KIIs) officials Ministry Physical Planning Urban Development (MPPUD) Ondo State, unveil various views “place health” planning practices Akure. lack synergy planners public practitioners limiting scope functions impact were observed. Thus, we recommend integration approach guide manage city.

Language: Английский

Citations

6
Land Use Change Modelling Using Logistic Regression, Random Forest and Additive Logistic Regression in Kubu Raya Regency, West Kalimantan DOI Creative Commons

Alfa Nugraha Pradana,

Anik Djuraidah, Agus Mohamad Soleh

et al.

Forum Geografi, Journal Year: 2023, Volume and Issue: 37(2)

Published: Dec. 29, 2023

Kubu Raya Regency is a regency in the province of West Kalimantan which has wetland ecosystem including high-density swamp or peatland along with an extensive area mangroves. The function ecosystems essential for fauna, as source livelihood surrounding community and storage reservoir carbon stocks. Most land peatland. As consequence, peat long been used agriculture community. Along vast peat, also potential high risk fires. This study aims to predict use changes using three statistical machine learning models, specifically Logistic Regression (LR), Random Forest (RF) Additive (ALR). Land cover map data were acquired from Ministry Environment Forestry subsequently reclassified into six types at resolution 100 m. employed classify class regency, years 2009, 2015 2020. Based on model performance, RF provides greater accuracy F1 score opposed LR ALR. outcome this expected provide knowledge recommendations that may aid developing future sustainable development planning management Regency.

Language: Английский

Citations

15
Investigating the impact of climate change on trend shifts of vegetation growth in Gilgit Baltistan DOI

Zulqarnain Satti,

Muhammad Naveed, Muhammad Shafeeque

et al.

Global and Planetary Change, Journal Year: 2023, Volume and Issue: 232, P. 104341 - 104341

Published: Dec. 22, 2023

Language: Английский

Citations

14
Ten deep learning techniques to address small data problems with remote sensing DOI Creative Commons
Anastasiia Safonova, Gohar Ghazaryan, Stefan Stiller

et al.

EarthArXiv (California Digital Library), Journal Year: 2023, Volume and Issue: unknown

Published: June 9, 2023

Researchers and engineers have increasingly used Deep Learning (DL) for a variety of Remote Sensing (RS) tasks. However, data from local observations or via ground truth is often quite limited training DL models, especially when these models represent key socio-environmental problems, such as the monitoring extreme, destructive climate events, biodiversity, sudden changes in ecosystem states. Such cases, also known small pose significant methodological challenges. This review summarises challenges RS domain possibility using emerging techniques to overcome them. We show that problem common challenge across disciplines scales results poor model generalisability transferability. then introduce an overview ten promising techniques: transfer learning, self-supervised semi-supervised few-shot zero-shot active weakly supervised multitask process-aware ensemble learning; we include validation technique spatial k-fold cross validation. Our particular contribution was develop flowchart helps users select which use given by answering few questions. hope our article facilitate applications tackle societally important environmental problems with reference data.

Language: Английский

Citations

11
Projections of future spatiotemporal urban 3D expansion in China under shared socioeconomic pathways DOI
Kechao Wang, Tingting He, Wu Xiao

et al.

Landscape and Urban Planning, Journal Year: 2024, Volume and Issue: 247, P. 105043 - 105043

Published: March 11, 2024

Language: Английский

Citations

4
Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models DOI Creative Commons
Eden T. Wasehun, Leila Hashemi-Beni, Courtney A. Di Vittorio

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102988 - 102988

Published: Dec. 1, 2024

Language: Английский

Citations

4
Monitoring land changes at an open mine site using remote sensing and multi-spectral indices DOI Creative Commons

Ikram Loukili,

Ahmed Laamrani, Mustapha El Ghorfi

et al.

Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41845 - e41845

Published: Jan. 1, 2025

Language: Английский

Citations

0