Diego García Díaz
GIS & Remote Sensing. Python & Statistics. Surf & MTB :)
Protocolo automático para el tratamiento de imágenes Landsat y la generación de productos derivados
I meeting proyecto GOYAS (2/12/2024)
Máquina Virtual
Características
Software
download.py
protocolov2.py
productos.py
hidroperiodo.py
utils.py
run_download.sh
run_hydroperiod.sh
GitHub Repository
Código
Carpetas
/ori
/geo
/rad
/nor
/pro
/hyd
/data
/mongo
Busqueda y descarga
Hillshade
MDT
Geo & Rad
Productos
Normalización
Escena
Landsat
Pias
PIAs Ref
FMASK
Data
No
GeoServer
ICTS
LAST
{"_id": "20240815l9oli202_34",
"usgs_id": "LC92020342024228LGN01",
"tier_id": "LC09_L1TP_202034_20240815_20240815_02_T1",
"lpgs": "LPGS_16.4.0",
"category": "T1",
"Clouds": {"cloud_scene": 0.06,
"land cloud cover": 0.06,
"cloud_PN": 0 },
"Info": {
"Tecnico": "LAST-EBD Auto",
"Iniciada": {"$date": {"$numberLong": "1724690285816"}},
"Pasos": {"rad": "",
"nor": {"Normalize": "True",
"Nor-Values": {
"blue":
{"Parametros":
{"slope": 1.020172035444719,
"intercept": -0.00711237939135306,
"std": 0.016095327213406563,
"r": 0.98906989518987,
"N": 54886,
"iter": 1},
"Tipo_Area":
{"Mar": 49347,
"Embalses": 793,
"Pinar": 1564,
"Urbano-1": 575,
"Urbano-2": 944,
"Aeropuertos": 547,
"Arena": 664,
"Pastizales": 266,
"Mineria": 186}},
"Productos":
["NDVI", "NDWI", "MNDWI",
{"Flood": {
"El Rincon del Pescador": 72.72,
"Marismillas": 0.99,
"Caracoles": 0,
"FAO": 14.94,
"Marisma Occidental": 1.26,
"Marisma Oriental": 6.57,
"Entremuros": 115.29} },
"Turbidity",
"Depth" ]}
{"_id": "hidroperiodo_2023-2024",
"escenas": [
{"escena_id": "20240409l9oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 19896.300000000003},
{"escena_id": "20240503l8oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 11161.53},
{"escena_id": "20240511l9oli202_34",
"nubes_marismas": 8.31,
"ha_inundacion": 8354.789999999999},
{"escena_id": "20240527l9oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 3754.53},
{"escena_id": "20240604l8oli202_34",
"nubes_marismas": 0.06,
"ha_inundacion": 2661.84},
{"escena_id": "20240714l9oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 249.93},
{"escena_id": "20240722l8oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 215.1},
{"escena_id": "20240807l8oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 209.43},
{"escena_id": "20240815l9oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 211.76999999999998},
{"escena_id": "20231008l8oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 305.91},
{"escena_id": "20231024l8oli202_34",
"nubes_marismas": 7.69,
"ha_inundacion": 1131.8400000000001},
{"escena_id": "20231117l9oli202_34",
"nubes_marismas": 0,
"ha_inundacion": 408.51},
{"escena_id": "20231125l8oli202_34",
"nubes_marismas": 0.03,
"ha_inundacion": 421.83},
{"escena_id": "20231219l9oli202_34",
"nubes_marismas": 4.76,
"ha_inundacion": 589.5899999999999},
{"escena_id": "20231227l8oli202_34",
"nubes_marismas": 0.63,
"ha_inundacion": 512.8199999999999},
{"escena_id": "20240112l8oli202_34",
"nubes_marismas": 0.09,
"ha_inundacion": 696.69},
{"escena_id": "20240120l9oli202_34",
"nubes_marismas": 0.01,
"ha_inundacion": 1138.59},
{"escena_id": "20240221l9oli202_34",
"nubes_marismas": 7.73,
"ha_inundacion": 4288.32},
{"escena_id": "20240229l8oli202_34",
"nubes_marismas": 0.01,
"ha_inundacion": 3901.3200000000006},
{"escena_id": "20240316l8oli202_34",
"nubes_marismas": 6.05,
"ha_inundacion": 4150.98}]}
Landsat
Hidroperiodo
dtm
fmask_escena
hillshade_escena
ndvi_escena
ndwi_escena
mndwi_escena
cob_veg
ndvi_p10
ndvi_mean
fmask
mndwi
ndwi
swir1
Criterios:
Swir1 <= 0.12
slope > 8 (**embalses NDWI_scene & MNDWI_scene**)
hillshade < p30
ndvip10 > 0.3 & ndvimean > 0.5
cobveg > 75
ndvi_scene > 0.6 & dtm > 2.5
fmask_scene clouds & shadows
sum(reclass((fmask_scene, ndwi_scene, mndwi_scene)) >= 2
Valid days
Hydroperiod
nº días inundado / nº días válidos * 365
ciclo / media(84-24)
Gracias por su atención
Aquí va la imagen sorpresa
By Diego García Díaz
GIS & Remote Sensing. Python & Statistics. Surf & MTB :)