feat(layers): update info (#488)

* feat(layrs): update description

* feat(aerosols):remove unit

data/layers-config.json

@@ -66,7 +66,7 @@
       "year": "numeric",
       "month": "long"
     },
-    "units": "testunit",
+    "units": "",
     "flyTo": {
       "position": {
         "height": 15000000.06,

storage/layers/layers-en.json

@@ -1,7 +1,7 @@
 [
   {
     "id": "fire.burned_area",
-    "name": "Fire",
+    "name": "Fire Burned Area",
     "shortName": "Fire",
     "description": "Throughout history, humans have used fire as an environmental management tool. Vegetation characteristics, mainly biomass loads and moisture, determine fire behaviour, but fire also modifies vegetation structure and evolution. Climate affects fire occurrence through the thermal and precipitation cycles, but it is also affected by fire, particularly by gaseous and PM emissions. This mutual influences among vegetation, climate and fire highlight the importance of having global long-term burned area (BA) information that serves as input for climate and vegetation modellers.\n\nCurrently, FireCCI51 BA product includes 19 years of global BA data. The product is offered at 250m resolution with date of detection, and at 0.25 degree cells with total BA and land cover. In both cases, uncertainty layers are also incorporated.\n\n**Variable Shown:** Total Burned Area in Square Meters  \n**Time Span:** 2001-01 – 2019-12  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Spatial Resolution:**  0.25 x 0.25 degree\n**Version:** 5.1\n\n[ESA CCI Fire ECV Project website](http://www.esa-fire-cci.org/)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/3628cb2fdba443588155e15dee8e5352)",
     "link": "http://..."
@@ -29,14 +29,14 @@
   },
   {
     "id": "aerosol.AOD550_mean",
-    "name": "Aerosol",
-    "shortName": "Aerosol",
-    "description": "Aerosol Optical Depth (AOD) quantifies the total aerosol extinction integrated over the entire vertical column of the atmosphere. Maps of AOD show the dominant global aerosol sources (e.g. Sahara desert, tropical biomass burning, Industrial emissions over for example China, the Po valley, North-Western Europe) as well as the large spatial and temporal variations due to the short particle lifetime in the atmosphere of a few days to a week.\n\nIn CCI a global record of AOD covering 1995 to 2012 has been processed together with further data records which contain additional aerosol parameters (e.g. Fine Mode AOD of small particles, Mineral Dust AOD, aerosol absorption, aerosol layer height). The animation in the App shows daily AOD maps from dual-view radiometers ATSR-2 / AATSR (Swansea algorithm, version 4.3).\n\n**Variable Shown:**  Aerosol Optical Thickness at 550 nm  \n**Time Span:** 2002-05 – 2012-04  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Version:** 4.21  \n\n[ESA CCI Aerosol ECV Project website](http://cci.esa.int/aerosol)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5dd3881e89c8419bbdba4ab06aa91112)",
+    "name": "Aerosol Optical Depth",
+    "shortName": "Aerosols",
+    "description": "Aerosol Optical Depth (AOD) quantifies the total aerosol extinction integrated over the entire vertical column of the atmosphere. Maps of AOD show the dominant global aerosol sources (e.g. Sahara desert, tropical biomass burning, Industrial emissions over for example China, the Po valley, North-Western Europe) as well as the large spatial and temporal variations due to the particle lifetime in the atmosphere of a few days to a week.\n\nIn CCI a global record of AOD covering 1995 to 2012 has been processed together with further data records which contain additional aerosol parameters (e.g. Fine Mode AOD of small particles, Mineral Dust AOD, aerosol absorption, aerosol layer height). The animation in the App shows monthly AOD maps from dual-view radiometers ATSR-2 / AATSR (Swansea algorithm, version 4.21).\n\n**Variable Shown:**  Aerosol Optical Depth at 550 nm  \n**Time Span:** May 2002 – April 2012  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Spatial Resolution:** 1 degree  \n**Version:** 4.21  \n\n[ESA CCI Aerosol ECV Project website](http://cci.esa.int/aerosol)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/5dd3881e89c8419bbdba4ab06aa91112)",
     "link": "http://..."
   },
   {
     "id": "cloud.cfc",
-    "name": "Clouds",
+    "name": "Cloud Fraction",
     "shortName": "Clouds",
     "description": "**Variable Shown:**  Cloud Fraction  \n**Time Span:** 1982-01 – 2016-12  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Version:** 3.0  \n\n[ESA CCI Cloud ECV Project website](http://www.esa-cloud-cci.org/)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/004fd44ff5124174ad3c03dd2c67d548)",
     "link": "http://..."
@@ -52,7 +52,7 @@
     "id": "ozone.atmosphere_mole_content_of_ozone",
     "name": "Ozone",
     "shortName": "Ozone",
-    "description": "Ozone is an important trace gas in the atmosphere and protects life on Earth by absorbing most of the biologically harmful ultraviolet sunlight. In the framework of ESA’s Climate Change Initiative a high-quality global total ozone data set has been generated from space-based observations that cover the period from 1995 to present. The data record can be used to investigate the long-term evolution of ozone in the atmosphere, which is intimately coupled to climate change. Of particular interest is the search for signs of recovery from the severe thinning and damage of the ozone layer, that was caused by human activities.\n\n\n**Variable Shown:** Mean Total Ozone Column in Dobson Units  \n**Time Span:** 1996-03 – 2011-06  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Version:** 1  \n\n[ESA CCI Ozone ECV Project website](http://cci.esa.int/ozone)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/0d2260ad4e2c42b6b14fe5b3308f5eaa)",
+    "description": "Ozone is an important trace gas in the atmosphere and protects life on Earth by absorbing most of the biologically harmful ultraviolet sunlight. In the framework of ESA’s Climate Change Initiative a high-quality global total ozone data set has been generated from space-based observations that cover the period from 1995 to present. The data record can be used to investigate the long-term evolution of ozone in the atmosphere, which is intimately coupled to climate change. Of particular interest is the search for signs of recovery from the severe thinning and damage of the ozone layer, that was caused by human activities.\n\n\n**Variable Shown:** Mean Total Ozone Column in Dobson  ts  \n**Time Span:** 1996-03 – 2011-06  \n**Temporal resolution:** monthly  \n**Geographic Extent:** global  \n**Version:** 1  \n\n[ESA CCI Ozone ECV Project website](http://cci.esa.int/ozone)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/0d2260ad4e2c42b6b14fe5b3308f5eaa)",
     "link": "http://..."
   },
   {
@@ -113,9 +113,9 @@
   },
   {
     "id": "biomass.agb",
-    "name": "Biomass",
+    "name": "Above Ground Biomass",
     "shortName": "Biomass",
-    "description": "**Variable Shown:** Above-ground biomass in Mg/ha  \n**Time Span:** 2017  \n**Temporal resolution:** yearly  \n**Geographic Extent:** global\n**Spatial Resolution:**   \n**Version:** 1  \n\n[ESA CCI Biomass ECV Project website](http://cci.esa.int/biomass)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/bedc59f37c9545c981a839eb552e4084)",
+    "description": "Biomass is the weight of living material in vegetation, which for forests is mainly contained in the\nwoody parts of the trees. Only above-ground biomass (AGB) can be measured from space (and in\npractice also for most on-ground measurements). Quantitative information on forest AGB is crucial\nfor understanding climate change, since loss of AGB caused by deforestation and forest degradation\nis second only to fossil fuel burning as a source of greenhouse gases, while CO₂ taken from the\natmosphere by forest growth and stored in woody biomass helps to slow climate warming.\n\nThe map shows estimated forest AGB in 2017 derived mainly from the combination of the ALOS\nPALSAR-2 L-band radar and the Sentinel-1 C-band radars, with support from a range of other sensors\nand environmental datasets.\n\n**Variable Shown:** Above-ground biomass in Mg/ha  \n**Time Span:** 2017  \n**Temporal resolution:** yearly  \n**Geographic Extent:** global  \n**Spatial Resolution:** 100m  \n**Version:** 1  \n**DOI:** [doi:10.5285/bedc59f37c9545c981a839eb552e4084](http://dx.doi.org/10.5285/bedc59f37c9545c981a839eb552e4084)\n\n[ESA CCI Biomass ECV Project website](http://cci.esa.int/biomass)  \n[Data in the Open Data Portal](https://catalogue.ceda.ac.uk/uuid/bedc59f37c9545c981a839eb552e4084)",
     "link": "http://..."
   },
   {