A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems

Autor: Ismaguil Hanadé Houmma, Sébastien Gadal, Loubna El Mansouri, Maman Garba, Paul Gérard Gbetkom, Mansour Badamassi Mamane Barkawi, Rachid Hadria

Publikováno v: Geomatics, Natural Hazards & Risk, Vol 14, Iss 1 (2023)

AbstractThis manuscript aims to develop a new multivariate composite index for monitoring agricultural drought. To achieve this, the AVHRR, VIIRS, CHIRPS data series over a period of 40 years, rainfall and crop yield data as references were used. Var

Externí odkaz: https://doaj.org/article/7fdc9d851f6f43f0884d6df21206021e

Characterization of Soil Degradation from the Cameroonians Shores of Lake Chad Combining Spectral Indexes and Statistics Analysis

Autor: Sébastien Gadal, Paul Gérard Gbetkom, Alfred Homère Ngandam Mfondoum

Publikováno v: SN Computer Science
SN Computer Science, 2023, 4 (3), pp.237. ⟨10.1007/s42979-022-01651-7⟩

International audience; This article aims to propose a model on the soil degradation risk along the Cameroonian shores of Lake Chad based on the statistical analysis of spectral indexes of Sentinel 2A satellite images. A total of four vegetation inde

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4964dc56bb0479a406a7a1b561e7ed5b
https://hal.science/hal-04019713/file/Gadal_Gbetkom_Mfondoum.pdf

Lake Chad vegetation cover and surface water variations in response to rainfall fluctuations under recent climate conditions (2000-2020)

Autor: Paul Gérard Gbetkom, Jean-François Crétaux, Michel Tchilibou, Alice Carret, Manon Delhoume, Muriel Bergé-Nguyen, Florence Sylvestre

Publikováno v: The Science of the total environment. 857(Pt 2)

Monitoring the evolution of the Sahelian environment is a major challenge because the great Sahelian droughts, marked by significant environmental consequences and social impacts, contributed, for example, to the drying up of Lake Chad. We combined r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ab5267aabb916503381731a9d09eaf4
https://pubmed.ncbi.nlm.nih.gov/36216071

Adapting the Sudden Landslide Identification Product (SLIP) and Detecting Real-Time Increased Precipitation (DRIP) algorithms to map rainfall-triggered landslides in the West-Cameroon highlands (Central-Africa)

Autor: ALFRED HOMERE NGANDAM MFONDOUM, Pauline Wokwenmendam Nguet, Jean Valery Mefire Mfondoum, Mesmin Tchindjang, Sofia Hakdaoui, Ryan Cooper, Paul Gérard Gbetkom, Joseph Penaye, Ateba Bekoa, Cyriel Moudioh

Background – NASA’s developers recently proposed the Sudden Landslide Identification Product (SLIP) and Detecting Real-Time Increased Precipitation (DRIP) algorithms. This method uses the Landsat 8 satellite images and daily rainfall recordings f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c9b34f5cc0dde5e089c9a29d93880c4
https://doi.org/10.21203/rs.3.rs-19292/v4

A New Index to Better Detect and Monitor Agricultural Drought in Niger Using Multisensor Remote Sensing Data

Autor: Ahmed El-Aboudi, Paul Gérard Gbetkom, Mamane Barkawi Mansour Badamassi

Publikováno v: Professional Geographer
Professional Geographer, 2020, 72 (3), pp.421-432. ⟨10.1080/00330124.2020.1730197⟩
Professional Geographer, Taylor & Francis (Routledge), 2020, 72 (3), pp.421-432. ⟨10.1080/00330124.2020.1730197⟩

In this study, we propose a new remote sensing–based drought index, the agricultural drought condition index (ADCI), for agricultural drought monitoring in the agricultural area of Niger. It is def...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a49d720c0f865de914b1bb0ec2543466
https://hal.science/hal-03130785